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Project ID 604674 FITMAN – Future Internet Technologies for MANufacturing
23/12/2013 Deliverable D1.5: FITMAN Reference Architecture
FITMAN Consortium Dissemination: Public 1/60
D1.5
FITMAN Reference Architecture
Document Owner: Domenico Rotondi (TXT)
Contributors: Jesus Benedicto (ATOS), Óscar Lázaro (INNOVALIA), Michele Sesana (TXT), Sergio
Gusmeroli (TXT)
Dissemination: Public
Contributing to: WP1
Date: 23/12/2013
Revision: 1.0
Project ID 604674 FITMAN – Future Internet Technologies for MANufacturing
23/12/2013 Deliverable D1.5: FITMAN Reference Architecture
FITMAN Consortium Dissemination: Public 2/60
VERSION HISTORY
VERSION DATE NOTES AND COMMENTS
0.1 01/07/2013 TOC AND INITIAL DRAFT
0.2 19/07/2013 TOC REVISION AFTER FITMAN MEETING IN MADRID
0.3 29/07/2013 FIRST CONTRIBUTIONS ON FITMAN TRIALS
0.4 30/08/2013 NEW DRAFT
0.5 19/09/2013 PARTNERS CONTRIBUTIONS OF FITMAN TRIALS AND SECTION 2
0.6 27/10/2013 DOCUMENT REVISION AFTER FITMAN ATHENS MEETING
0.7 07/10/2013 DOCUMENT OBJECTIVES AND STRUCTURE REVISION
0.8 15/10/2013 FIRST COMPLETE DRAFT OF SECTION 3
0.9 29/11/2013 FIRST COMPLETE VERSION FOR INTERNAL REVIEW
1.0 23/12/2013 VERSION 1.0
DELIVERABLE PEER REVIEW SUMMARY
ID Comments Addressed ()
Answered (A)
1 Refer to other deliverables for trials IT
infrastructures and requirements Removed the section with the trials IT
requirements and infrastructures description
2 Add FITMAN cloud computing relevance
and Cloud Chapter GEs selection rationale Added Section 3.5.6
3
Project ID 604674 FITMAN – Future Internet Technologies for MANufacturing
23/12/2013 Deliverable D1.5: FITMAN Reference Architecture
FITMAN Consortium Dissemination: Public 3/60
Table of Contents
EXECUTIVE SUMMARY ................................................................................................................................... 5
1. INTRODUCTION ....................................................................................................................................... 7
1.1. DELIVERABLE OBJECTIVES ................................................................................................................... 7 1.2. DELIVERABLE ORGANIZATION ............................................................................................................... 8
2. THE MANUFACTURING DOMAINS AND THE FITMAN TRIALS ................................................. 9
2.1. THE FITMAN MANUFACTURING DOMAINS ........................................................................................... 9 2.1.1. Manufacturing Challenges........................................................................................................... 9 2.1.2. Manufacturing Characteristics .................................................................................................. 12 2.1.3. Smart Factories ........................................................................................................................... 13 2.1.4. Digital Factories ......................................................................................................................... 14 2.1.5. Virtual Factories ......................................................................................................................... 15
2.2. THE FITMAN SMART FACTORY TRIALS ............................................................................................... 16 2.2.1. Automotive Supplier (Spain) ...................................................................................................... 16 2.2.2. White Goods OEM (Italy) ........................................................................................................... 17 2.2.3. Textile/Clothing (Italy) ............................................................................................................... 18 2.2.4. Aeronautics OEM (Italy) ............................................................................................................ 18
2.3. THE FITMAN DIGITAL FACTORY TRIALS ............................................................................................ 19 2.3.1. Automotive OEM (Germany) ..................................................................................................... 19 2.3.2. Aeronautics OEM (Italy) ............................................................................................................ 20 2.3.3. Construction Industry (Portugal) ............................................................................................... 21 2.3.4. Furniture (Spain)........................................................................................................................ 22
2.4. THE FITMAN VIRTUAL FACTORY TRIALS ............................................................................................ 22 2.4.1. Plastic Industry (France)............................................................................................................ 23 2.4.2. Manufacturing Resource Management (UK) ............................................................................ 23 2.4.3. LED Lighting (Germany) ........................................................................................................... 24 2.4.4. Machinery for Wood (France) ................................................................................................... 25
3. THE FITMAN REFERENCE ARCHITECTURE ................................................................................. 26
3.1. WHY A REFERENCE ARCHITECTURE .................................................................................................... 26 3.2. THE FITMAN SMART FACTORY REFERENCE ARCHITECTURE ............................................................... 30 3.3. THE FITMAN DIGITAL FACTORY REFERENCE ARCHITECTURE ............................................................ 35 3.4. THE FITMAN VIRTUAL FACTORY REFERENCE ARCHITECTURE ............................................................ 39 3.5. THE FITMAN MANUFACTURING DOMAINS ARCHITECTURES AND FI-WARE GES ................................ 44
3.5.1. The FITMAN Enablers .............................................................................................................. 44 3.5.2. The FITMAN Reference Architectures and GEs /SEs .............................................................. 44 3.5.3. The FITMAN Smart Factory GEs/SEs ...................................................................................... 45 3.5.4. The FITMAN Digital Factory GEs/SEs .................................................................................... 48 3.5.5. The FITMAN Virtual Factory GEs/SEs .................................................................................... 51 3.5.6. The FI-WARE Cloud Hosting GEs in FITMAN ....................................................................... 55
4. CONCLUSIONS AND NEXT STEPS ..................................................................................................... 57
5. REFERENCES ........................................................................................................................................... 58
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Table of Figures
Fig. 3-1: Role of a Reference Architecture............................................................................. 27 Fig. 3-2: Derivation of specific architectures and implementations ....................................... 27
Fig. 3-3: Industrie 4.0 Reference Architecture for connecting the IoT with the IoS.............. 28 Fig. 3-4: FITMAN DoW draft Reference Architecture .......................................................... 29 Fig. 3-5: The FITMAN Smart Factory Reference Architecture ............................................. 31 Fig. 3-6: The FITMAN Smart Factory Gateway Layer Architecture..................................... 33 Fig. 3-7: The FITMAN Smart Factory Back End Layer Architecture ................................... 33
Fig. 3-8: The FITMAN Digital Factory Reference Architecture ........................................... 36 Fig. 3-9: The FITMAN Digital Factory PL Data Management Layer Architecture .............. 37 Fig. 3-10: The FITMAN Digital Factory PL Data Visualization & Manipulation Layer
Architecture ............................................................................................................................ 39 Fig. 3-11: The FITMAN Virtual Factory Overall Architecture ............................................. 41
Fig. 3-12: The FITMAN Virtual Factory Assets Management Layer Architecture ............... 42 Fig. 3-13: The FITMAN Virtual Factory Interoperability & Collaboration layer Architecture
................................................................................................................................................ 43 Fig. 3-14: The GEs / SEs graphical representations ............................................................... 45 Fig. 3-15: The FITMAN Smart Factory Reference Architecture and GEs / SEs ................... 47 Fig. 3-16: The FITMAN Digital Factory Reference Architecture and GEs / SEs ................. 50
Fig. 3-17: The FITMAN Virtual Factory Reference Architecture and GEs / SEs ................. 54
Project ID 604674 FITMAN – Future Internet Technologies for MANufacturing
23/12/2013 Deliverable D1.5: FITMAN Reference Architecture
FITMAN Consortium Dissemination: Public 5/60
EXECUTIVE SUMMARY
The FITMAN D1.5 “FITMAN Reference Architecture” is a public document delivered in the
context of WP1 Task 1.5 that reports, as the title implies, the structure and rationale of the
FITMAN reference architecture, based on Future Internet technologies, for each of the three
manufacturing domains identified by the EFFRA (European Factory of the Future Research
Association) and addressed by the project:
Smart Factory that focuses on agile manufacturing, process automation control, and
tools for sustainable manufacturing;
Digital Factory in which ICT is focused on improving the design of production and
manufacturing systems, the product life cycle management;
Virtual Factory that addresses supply chain management, product-service linkage
and management of distributed manufacturing.
An architecture is meant to capture and identify the high-level structure of a system and
assure that the identified architectural elements and their relationships meet the needs and
objective of the system or domain to be modelled. The manufacturing domain is quite wide,
as is reflected in the FITMAN project, to be effectively modelled by one architecture, even
by three architectures one for each of the EFFRA manufacturing domains. Therefore, the
design of one single architecture for the whole Future Internet for Manufacturing domain is
not reasonable if it has to be effective.
A better approach is to design a Reference Model, or Reference Architecture, that provides a
more abstract description from which several concrete architectures for the specific real
systems can be actually drawn. A Reference Architecture focuses on capturing the main
architectural characteristics of a set of systems, providing indications and guidelines for the
design of actual architectures for a specific system.
A Reference Architecture is normally focused on providing:
a common lexicon or taxonomy that is tied to the application domain (i.e., automation
in the FITMAN case);
a common architectural vision that helps in focusing common elements and in
deriving synergic actual architectures;
modularization that helps in focusing subsequent refinement activities and in assuring
integration and, to some extent, interoperability.
Reference Architectures facilitate the design and management of product family architecting
and evolution, smoothing impacts due to market changes in contexts and needs.
This document therefore first tries to characterize the envisaged main evolutionary trends of
the manufacturing domain, in terms of envisaged key functionalities and technologies, taking
into account analysis and forecasts from authoritative documents such as the Industrial
Internet, the German Industrie 4.0 initiative, FInES (Future Internet Enterprise System),
EFFRA and ActionPlanT roadmaps and documents, as well as other documents available in
literature.
Afterwards it better characterizes the three EFFRA manufacturing domains, and provides a
quick overview of the FITMAN trials to provide to the reader evidence of how these trials
cover the three EFFRA manufacturing domains, as well as how to match and interpret the
key trends that are expected to characterize the future on manufacturing.
The document then describes the three Reference Architectures identifying their layering and
functional components and their relationships, as well as the rationale behind them. Each of
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FITMAN Consortium Dissemination: Public 6/60
the three Reference Architectures is structured in two or three sub-layers, the lowest one
interfacing the data sources specific for the manufacturing domain at hand, and each sub-
layer is furthermore structured in modular components focused on specific functionalities.
Finally the three Reference Architectures are revisited taking into account the FI-WARE
Generic Enablers (GEs) and the FITMAN Specific Enablers (SEs) and how these enablers
are positioned in them and could fulfill the functionalities envisaged for the architectural
components.
Cloud computing technologies are expected to play a relevant role in the near future for
manufacturing, especially to support SMEs. Therefore the three Reference Architectures
must be read taking into account that the envisaged functional components will be, sooner or
later, provided by software elements deployed and running on cloud infrastructures.
Unfortunately, the cloud IaaS, PaaS and SaaS are simple service models that applies to any
application domain and therefore their functional elements cannot be identified as explicitly
contributing to one application domain’s specific architectures and to the FITMAN
Reference Architectures in particular.
Anyway, the final section that reviews the FITMAN Reference Architectures in the light of
the FI-WARE GEs and FITMAN SEs is completed with a survey of the selected GEs from
the FI-WARE Cloud Chapter to better highlight the contribution the FITMAN trials can
provide to assess the FI-PPP provided Future Internet technologies in the manufacturing
area.
A final consideration is required on the use of the FITMAN Reference Architectures, and of
their related GEs/SEs, by each of the FITMAN trials, or other manufacturing contexts
outside the FITMAN project.
As highlighted above, a Reference Architecture captures the main characteristics of a
specific system or domain and only provides a framework for the actual architecture of a
specific context (e.g., a FITMAN trial). A similar consideration is valid for the identified
GEs and SEs; the GEs and SEs aggregation and positioning in the Reference Architectures is
intended just to fulfil the envisaged functional requirements and therefore must be
considered just as indicative of the real implementation in a specific manufacturing context.
Therefore, in the respective T4.1-T5.1-T6.1 tasks, each FITMAN trial or manufacturing
context must draw its own specific architecture finalizing one or more of the three FITMAN
Reference Architectures and must pick up the mix of the identified GEs and SEs that best fit
its needs, requirements and constraints complementing the picture with Trial, or context,
Specific Components (TSCs).
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1. INTRODUCTION
1.1. Deliverable Objectives
The FITMAN objective is to provide industry-led use case trials in the Smart, Digital and
Virtual Factories, as defined by the EFFRA roadmap for the Factory of the Future, based on
Future Internet technologies as made available within the EU FI-PPP programme (FI-WARE
GEs) or provided by the FITMAN project itself (FITMAN Specific Enablers – SEs, or Trial
Specific Components –TSCs).
Each trial will combine suitable sets of GEs and SEs, and will develop its own TSCs, to
develop and deploy its own service platform to provide services to the community envisaged
by each specific trial and assess, in real contexts, the suitability of the identified Future
Itnernet technologies.
This deliverable, as envisaged in the DoW, describes the FITMAN Reference Architecture
taking into account the following elements:
the draft FITMAN architecture s reported in the Description of Work (DoW);
the IT requirements collection and analysis performed in the start phase of the
FITMAN project and reported in the FITMAN D1.2 [48] deliverable;
the analysis performed and reported in the FITMAN D1.3 deliverable [47] regarding
the FI-WARE GEs and their functionalities.
This deliverable consolidates the above elements and structures a set of reference
architectures for each of the 11 FITMAN trials relating them to the three layers envisaged by
the FITMAN Reference Architecture and to the FI-WARE GEs, identifies commonalities
among them, and tries to sketch the FITMAN Reference Platforms for the three different
manufacturing areas (Smart, Digital and Virtual factory).
The following sections, in line with the FITMAN DoW, report and analyze the needs and
architectural choices according to the three manufacturing systems’ levels identified by the
EFFRA (European Factory of the Future Research Association) documents [1] where ICT is
having, and will have, a key role:
Smart Factories: characterized by “agile manufacturing and customisation involving
process automation control, planning, simulation and optimization technologies,
robotics, and tools for sustainable manufacturing”;
Virtual Factories: where is relevant the “value creation from global networked
operations involving global supply chain management, product-service linkage and
management of distributed manufacturing assets”;
Digital Factories: in which ICT is focused on supporting “a better understanding
and design of production and manufacturing systems for better product life cycle
management involving simulation, modelling and knowledge management from the
product conception level down to manufacturing, maintenance and
disassembly/recycling”.
These three EFFRA areas in the following are for brevity identified with the term
manufacturing domains.
The deliverable, therefore, provides details on the FITMAN reference architecture for each
of these manufacturing domains starting from the needs and architectural designs of each of
the project’s trials and details and rationalizes the mapping between each of the designed
Reference Architectures and the identified set of FI-WARE GEs and FITMAN SEs.
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1.2. Deliverable Organization
The deliverable is structured in three sections (in addition to this section 1):
Section 2 is devoted to characterize the manufacturing domain and the key challenges
(see section 2.1.1) and elements (see section 2.1.2) that will characterize it in the near
future. After an overall analysis specific ones are provided for each of the three
EFFRA defined manufacturing domains (see sections 2.1.3 - 2.1.5). Section 2
completes the scenario providing a quick overview of the FITMAN 11 trials (see
sections 2.2 - 2.4) o that the reader has the elements to evaluate the identified
Reference Architectures and their potential both to assess the proposed Future
Internet technologies, as well as the potential as sources for solutions in the
manufacturing domains and addressed manufacturing needs;
Section 3 is the main section devoted to provide the rationale and structuring of the
three Reference Architectures, as well as of their relationships with the selected GEs
and SEs. More specifically, section 3.1 is devoted to provide the rationale behind the
Reference Architecture approach, while sections 3.2 - 3.4 presents and analyze the
Reference Architectures for the Smart, Digital and Virtual Factories, respectively.
Finally, section 3.5 describes how the FI-WARE GEs and FITMAN SEs contribute to
the implementation of each of the identified Reference Architectures, Section 3.5 is
structured into a set of subchapters to better analyze the mappings of each of the three
Reference Architectures with the FI-WARE GES and FITMAN SEs. A specific
subchapter (see section 3.5.6) is devoted to describe how the FI-WARE Cloud
Chapter GEs are expected to contribute to the implementation of the reference
architectures;
Section 4 reports the conclusions.
Care has been taken to provide references to documents and literature (see section 5) that
support the analysis, approaches and choices reported in this document so to provide to the
reader the possibility to directly check design approaches and to further deepen the topics
addressed in this document.
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2. THE MANUFACTURING DOMAINS AND THE FITMAN TRIALS
2.1. The FITMAN Manufacturing Domains
2.1.1. Manufacturing Challenges
Manufacturing is a significant element for the European economy accounting for around
10% of all enterprises in the EU-27’s non-financial business economy in 2010, with figures
like: 2 million enterprises, 30 million employed people (around 22% of EU’27 employment),
and an annual value added around 1.600 billion Euro (around 27% of the EU’27 non-
financial business economy value added) (source: Eurostat).
The European manufacturing sector envisages a huge presence of SMEs that account for
around of 45% of the whole EU manufacturing added value, and around 59% of the
manufacturing employment (source: Eurostat).
These figures make evident how critical is for Europe this sector and the relevance of
promoting its innovation both to maintain and possibly expand its economic relevance, as
well as a way to promote innovation in other sectors (like ICT) that provide products and
services to the manufacturing sector. Indeed, manufacturing is an R&D&I intensive activity
with R&D investments that represent 66% of the European R&D private expenditure.
Many analysts state that the manufacturing sector is moving to a new phase. Indeed, the
General Electric document on Industrial Internet [1] states the twenty-first century will see
a 3rd
wave after the Industrial (1st wave) and Internet (2
nd wave) revolutions. This wave, the
authors call Industrial Internet, is characterized by “… the melding of the global industrial
system that was made possible as a result of the Industrial Revolution, with the open
computing and communication systems developed as part of the Internet Revolution, opens
up new frontiers to accelerate productivity, reduce inefficiency and waste, and enhance the
human work experience”.
A similar position is reported by the German Industrie 4.0 programme [3] that states “the
first three industrial revolutions came about as a result of mechanisation, electricity and IT.
Now, the introduction of the Internet of Things and Services into the manufacturing
environment is ushering in a fourth industrial revolution”.
Several elements are behind the evolution that is making machines and the Cyber Physical
Systems (CPS) in which they are integrated more intelligent. The most relevant elements are:
costs: instrumentation costs have declined dramatically, therefore making possible to
more economically equip industrial machines;
computing power: improvements in microprocessor chips make it possible to add
digital intelligence to machines;
data analytics: advances in software tools and analytic techniques provide the means
to actually manage and understand the massive quantities of data that intelligent
devices generate.
Additionally, this evolution is also promoting new approaches to production [3] “smart
products are uniquely identifiable, may be located at all times and know their own history,
current status and alternative routes to achieving their target state. The embedded
manufacturing systems are vertically networked with business processes within factories and
enterprises and horizontally connected to dispersed value networks that can be managed in
real time – from the moment an order is placed right through to outbound logistics”.
Moreover, as stated in FInES) position paper [4], “… Future Internet (FI) technologies and
infrastructures (including cloud and mobile computing, Internet of Things, Big Data
analytics, IPv6 and next generation networks and computational and storage architectures),
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when embedded and integrated in vital and critical business processes in a transparent and
seamless way, are envisioned to constitute the most prominent drivers for enterprise business
innovation”.
All these analysis assign a central role to ICT technologies; therefore, the Europe 2020
Strategy underlines the role of technology as the key solution-provider for tackling the
challenges Europe has to face in the coming years and help in promoting innovative ideas,
new products and services to assure EU growth, high-skilled jobs, and address European and
global societal challenges.
To address the challenges envisaged by the Europe 2020 Strategy, the European
manufacturing sectors have to undergo the following structural transformations [5]:
Manufacturing the products of the future, addressing the ever changing needs of
society and offering the potential of opening new markets.
Economic sustainability of manufacturing, combining high-performance and quality
with cost-effective productivity, realising reconfigurable, adaptive and evolving
factories capable of small-scale production in an economically viable way, herewith
facing better and promptly the uncertain evolution of the market or the effect of
disruptive events.
Social sustainability of manufacturing, integrating human skills with technology.
Environmental sustainability of manufacturing, reducing resource consumption and
waste generation.
From an ICT point of view, the EFFRA roadmap envisages the following major challenges:
Collaboration: as a way to support:
o collaborative manufacturing where ICT has to support a constant feedback
loop among product designers, engineers, state-of-the-art production facilities
and customers;
o collaborative supply networks where ICT has to support OEMs to offer
value-added services (e.g., maintenance, upgrade) or even sell their “products
as a service”
o customer collaboration where ICT solutions must enable extraction of
customer and after-sales information from disparate sources (e.g., social
networks) and feed the manufacturing process to develop personalized or
highly customized products;
Connectivity to support seamless, bi-directional interactions with real-world objects
and environments (e.g., IoT) on a global scale, across different application domains
and stakeholders. The manufacturing Enterprise Information Systems (EIS) must be
opened adopting widely used standards and be able to inter-operate across multiple
organisations, as well as manufacturing systems and devices must become more
intelligent and have advanced self-configuration, self-monitoring, and self-healing
features to support the dynamics and the large and growing number of devices and
data of future manufacturing processes;
Mobility to provide workers, supervisors and managers with critical data at their
fingertips and foster the development of next-generation of mobility assisted
manufacturing applications (in fields like: manufacturing & logistics traceability,
real-time data analysis, and forecasting);
Intelligence to support the processing the huge amount of data originating as a result
of the above points. Significant progress beyond the state-of-the art will be required
in areas like: complex event processing, real-time data analysis and forecasting.
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Similarly, the roadmap [6] designed by the ActionPlanT project within the EU Factory of the
Future PPP Action identifies the following elements are central for the European
manufacturing future:
three key ICT elements:
I. the need to “bridge the gap between process- and commercially-oriented
manufacturing operations by leveraging advances in the ICT world – notably
in collaboration, connectivity, mobility and intelligence”;
II. the need to use “ICT to integrate the human element – workers and customers
– to a greater degree in their day-to-day operations and businesses”;
III. the systematic use of ICT innovation as a fundamental success factor for
future European manufacturing operations in Europe, where “enterprises have
to be agile and swift when it comes to being innovative and applying
innovation in practice”;
five essential ambitions for ICT-enabled manufacturing:
I. On-demand: “… manufacturing 2.0 should accommodate changing demands
from a new customer base and deliver customised products on-demand. … it
is important that European manufacturers are able to deliver products to
customers quickly by collaborating with suppliers and subcontractors using
agile supply chains which are interoperable, collaborative and manageable”;
II. Optimal: “… the next generation of product lifecycle management solutions
should not only focus on designing the best products but consider the service
life of products with special emphasis on value added and after-sales
services”;
III. Innovative: “… introduction of collective innovation is one of the three key
growth factors together with human capital and infrastructures”;
IV. Green: “… Manufacturing 2.0 needs focused initiatives to reduce energy
footprints on shop floors and increase awareness of end-of-life (EoL) product
use”;
V. Human-centric: “… manufacturing 2.0 will evolve from being perceived as
production centred to human centred”.
As evident from the above analysis and future manufacturing scenario, the European
industries has to: on the one hand put workers at the forefront (improving knowledge
delivery mechanisms, supporting continuous skills enhancement, providing assistive tools
for aged workers, developing and deploying intuitive e-learning tools for all), and, on the
other hand,
Put customers in-the-loop (quality and sustainable products for customers, design thinking
and customizations, customer collaboration). To this end the ActionPlanT document
introduces the concept of Manufacturing Business Web (MBW) as a “melting pot where
disparate solutions for process- and commercially-oriented technologies converge”. This
concept will encourage technology developers and manufacturing service providers to build
new solutions with minimal time-to-market, while customers will significantly reduce their
investments to develop new services, and will have the possibility to compose and configure
manufacturing services in-situ.
The FITMAN project, which is not focused on R&D activities devoted to develop new
technologies for manufacturing, nevertheless has to move along the lines depicted above and,
roughly speaking, position itself within the Industrial Internet wave or as a forerunner of the
Industrie 4.0 4th
industrial revolution. Indeed FITMAN envisages as key elements:
the horizontal integration through value networks,
support for end-to-end engineering across the entire value chain,
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vertically integrated and networked manufacturing systems.
2.1.2. Manufacturing Characteristics
The previous section shed some light on the challenges manufacturers and ICT solutions
providers have to face in the coming years.
As the IoT becomes widely deployed in smart factories, the volume and the level of detail of
the generated data will increase, and, at the same time, the business models will no longer
involve just one or a few companies, but will instead comprise highly dynamic networks of
companies and completely new value chains. Smart machines will autonomously generate
and transmit data that will inevitably cross company boundaries. A number of specific
dangers are associated with this new context, and new instruments will be required these
issues.
Information will also be shared across machines, individuals or companies to facilitate
intelligent collaboration and better decision making [1]: “This enables a broader group of
stakeholders to engage in asset maintenance, management and optimization. It also ensures
that local and remote individuals that have machine specific expertise are brought into the
fold at the right time. Intelligent information can also be fed back to the originating machine.
This not only includes data that was produced by the originating machine, but also external
data that can enhance the operation or maintenance of machines, fleets and larger systems”.
The scenarios and challenges highlighted in the previous sections must be taken into account
in the design of the FITMAN architecture and FI-WARE GEs evaluation. The following list
tries to structure the most relevant elements:
Safety: technological systems (machines, production facilities, products, etc.) should
not create danger to people, the environment or even to other machines. Safety [3]
“requires both operational safety and a high degree of reliability. … Operational
safety refers to the aspects of safety that are dependent on the correct operation of
the system or that are provided by the system itself. The elements required to deliver
operational safety include low fault rates, high fault tolerance (i.e. the ability to keep
operating correctly even when faults occur) and robustness (the ability to guarantee
basic functionality in the event of a fault). Reliability refers to the probability of a
(technological) system operating correctly for a given period of time in a given
environment”. This requirement therefore impact the ability, reliability, and reactivity
of the production systems as a whole, as well as on the smart objects and services
active in it;
Security: data and services need to be protected against misuse (e.g. unauthorised
access, modification or destruction). The manufacturing system has to provide
advanced security features to increase confidentiality (restrict access to data and
services to specific machines/human users), integrity (accuracy/completeness of data
and correct operation of services) and availability (system’s ability to perform a
function in a particular time);
Information protection: all manufacturing systems manage highly confidential
information being it information related to shop floor activities, product technical or
production processes details, etc. In a global market, intellectual property protection
is therefore key to the manufacturers’ survival due to its impacts not only on sales,
but also on corporate image and loss of know-how. This issue will increase its
importance in view of the much higher degree of cooperation between the different
partners in the value network. It is therefore necessary to assure the deployment of
highly flexible, scalable and efficient information protection features (e.g., access
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control and data integrity), as well as highly secure and controllable ICT
environments to guarantee trust and transparency to protect critical business
knowhow;
Liability: the Industrial Internet, Industrie 4.0 4th
wave, Manufacturing 2.0 envisage
a substantial increase on the exchange of sensitive data between different companies,
with a corresponding increase of the risks that these data may be used and/or
disclosed illicitly, or that they may be hacked by third parties. In the immediate future
therefore, the issue of liability and responsibility becomes even more important and
specific measures have to be set up to manage correct attribution of liability and
precise documentary evidence in all manufacturing steps and system statuses;
Handling of personal data: the interaction between employees and the production
system will increase both to improve safety of people on the working place, as well
as to support the new production processes. The volume and level of detail regarding
the workers and employees will therefore increase too. This issue poses a threat [3]
“… to employees’ right to informational self-determination. … Current regulation
fails to adequately address these problems. Outsourced data processing models are
already encountering difficulties (e.g. in the realm of cloud computing), since local
data protection standards are generally not applicable in countries outside of
Europe, meaning that in practice it is impossible for client companies to comply with
their data protection responsibilities”;
Time constraints: production lines and cells, in particular, need communication
infrastructures with low delay and jitter (often able to assure real-time
communication), as well as event processing services able to quickly react to events;
Integrability: a manufacturing environment envisages many hardware (sensors,
actuators, conveyors, robots, etc.) and software components (PLCs, SCADA systems,
MES, ERP, etc.) normally provided by a wide set of suppliers or managed by
different subjects (e.g., suppliers, maintainers, retailers, etc.). The integrability issue
both impacts on the information representation, as well as on features or protocols to
be provided or supported (e.g., authentication based on LDAP, Kerberos, Microsoft
Active Directory);
Predictability: production is characterized by well-defined processes and procedures
that, often, have to be executed according to a given pace (e.g., takt time) and always
according to what envisaged in the design phase. This implies that elements like
continuity, scalability, responsiveness, etc. must be assured at all levels of the ICT
production stack, and that these elements are key elements of the contracts with
external subjects. On the ICT side this implies that ICT related contracts must
provide assurance for QoS, SLA, etc.
The following sections further characterize each on the manufacturing domains envisaged by
the FITMAN project.
2.1.3. Smart Factories
Smart Manufacturing (or Smart Factory), as stated, deals with the optimization of the
production processes (in terms of production costs reduction, efficient energy usage,
improvement in production reliability, production machines usage, etc.) via the monitoring
and management of the production process and of its components. Smart factories therefore
[3] “… are capable of managing complexity, are less prone to disruption and are able to
manufacture goods more efficiently.
In the smart factory, human beings, machines and resources communicate with each other as
naturally as in a social network”.
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These contexts need technologies that supports [6]: seamless integration of disparate systems
and robots, real-time enforcement of engineering changes, quality, regulatory, requirements
in the frontline, advanced algorithms on large data sets (e.g., for analyses and forecasting on
productivity, throughput, downtime), event driven architecture, as well as standardized
interfaces for data exchange. Additionally smart factories need to provide, in an effective and
efficient way, to workers and plant managers a disparate set of information to support them
in their daily operations and decisions. Furthermore, managers would be able to [6] “… drill
down into any production area and observe throughput, use and consumption through
intuitive key performance indicators (KPIs) even when on the move”.
Smart factory therefore envisages the deployment and management of technologies at the
level of the shop floor, the supply chain optimization, robotics, automation, production
planning and optimisation. Additionally, it envisages smart devices, adaptive and fault
tolerant process automation, control and optimisation technologies and tools, plug&produce
connection of automation equipment, new metrology tools and methods for large-scale and
real-time handling and processing of manufacturing information.
2.1.4. Digital Factories
Digital factories address [1] “… the front-end stages of manufacturing, in particular early
concept modelling, simulation and evaluation, as well as the transformation of the
knowledge-time curve, thus ensuring greater acquisition of knowledge earlier so that better
informed manufacturing decisions can be taken. The handling of uncertainty is also a crucial
area”.
As such digital factory’s platforms must [3] “… connect people, objects and systems to each
other … and will possess the following features:
Flexibility provided by rapid and simple orchestration of services and applications,
including CPS-based software
Simple allocation and deployment of business processes along the lines of the App
Stores model
Comprehensive, secure and reliable backup of the entire business process
Safety, security and reliability for everything from sensors to user interfaces
Support for mobile end devices
Support for collaborative manufacturing, service, analysis and forecasting processes
in business networks.”
Additional aspects that digital factory’s ICT platforms have to provide are related to:
intelligent system maintenance and maintenance optimization across machines,
components and individual parts providing a line of sight on the status of these
devices and assuring required parts to be delivered at the right time to the correct
location. This includes also learning capabilities and predictive analytics to allow
preventive and predictive maintenance programs that [2] “… have the potential to lift
machine reliability rates to unprecedented levels”;
the collected data could be aggregated and analysed to obtain [2] “… a continuously
expanding, self-learning system that grows smarter over time”.
provide intelligent decision making gathering data from intelligent devices and
systems to [2] “… facilitate data-driven learning, which in turn enables a subset of
machine and network-level operational functions to be transferred from operators to
secure digital systems. This element of the Industrial Internet is essential to grapple
with the increasing complexity of interconnected machines, facilities, fleets and
networks”.
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The Digital Factory domain, therefore, envisages the integration of digital methodologies
and tools in the field of production engineering spanning from modelling, simulation,
3D/Virtual Reality visualization, continuous data management, predictive and condition
based maintenance, KPI evaluation and on-demand provision of information (even on mobile
devices) for decision makers.
The aim of the Digital factory is to set up an efficient and comprehensive environment able
to support and optimize the design, modelling, simulation, and evaluation of products,
processes and systems before a new factory is built or any modification are made on existing
systems, as well as to in order to improve quality and reduce time. Additionally, this
manufacturing area covers also the life-cycle management of products, from the design
phase all the way through to production, maintenance, disassembly and recycling.
The Digital Factory domain, in short, has to face two main challenges to improve (in terms
of speed, quality, accuracy and effectiveness) the decision making process:
provide a consolidated and integrated access to product life-cycle information
managed by the various systems, tools and sources available in the factory;
provide a contextualised, personalised presentation of such information based on
advanced data analytics and (3D) visualisation capabilities also while on the move.
To this end, the FITMAN Digital Factory trials focus on particular needs of better
knowledge management and exploitation of product lifecycle information identified in a
variety of departments that range from production planning departments, maintenance,
design or teams working in the production field. All share the same interest to access to
technologies and platforms that allow them experience a more natural flow of information
and a better presentation of information for adapting their decisions and systems towards
more productive scenarios.
2.1.5. Virtual Factories
The Virtual Factory domain can be simply characterized in term of setting up and managing
collaborative supply networks based on [6]:
Great collaboration between OEMs and subcontracts through standardized
interfaces
Total visibility of production, inventory, and materials
Quick response in supply chain planning
New paradigms such as “production as a service” and “after-sales services”
The final, future objective is to [3] “… incorporate individual customer- and product specific
features into the design, configuration, ordering, planning, production, operation and
recycling phases. It will even be possible to incorporate last-minute requests for changes
immediately before or even during manufacturing and potentially also during operation”.
ICT technologies in this area have to support the development and management of inter-
company value chains and networks through horizontal integration, digital end-to-end
engineering across the entire value chain of both the product and the associated
manufacturing system, and the vertical integration of flexible and reconfigurable
manufacturing systems within businesses.
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Key ICT elements in this domain are [1]: “(a) improved efficiency of (embedded) product
intelligence enabling advanced product-centric services (e.g. product authentication, IPR
security, ICT-facilitated diagnosis and repair/resetting, remote performance/energy
monitoring and logistics); (b) new business models and capabilities for improved
management of global networked operations”.
The Virtual Factory ICT domain therefore deals with the realization and management of
complex, end-to-end, collaborative production environments therefore including complex
and extended supply chain, collaborative design and production, M2M communication, etc.
In this domain ICT solutions are integrated end-to-end and across company boundaries, with
the aim to support the exchange and integration of data and physical assets, to provide clear
insight and exact, useful knowledge, while facilitating and supporting decision making and
creating value from global networked operations
2.2. The FITMAN Smart Factory Trials
In line with the characterization of the Smart Factory manufacturing domain, the related
FITMAN trials are essentially focused in reducing production costs, increasing production
capacity and increasing the usefulness of information, even if they could have some
characteristics pertaining to the other manufacturing domains as is usual in real contexts.
The objective of the these trials is to assess FI-WARE technologies in real or realistic Smart
Factory contexts in their ability to improve and speed up the production processes; therefore
supporting exploitation of FI-WARE and Future Internet technologies by a large and diverse
set of service ecosystems for improved production in the manufacturing context.
FITMAN Smart Factory trials will significantly improve the management of sensors and
services, facilitating a simpler deployment of smart objects in the factory shop-floor and
more intelligent production practices. The final objective is to demonstrate how different
business domains could plug highly diverse sensors, machines and process information over
a unified information interoperability framework.
In the following we provide a very short description of the FITMAN Smart Factory trials
with the main objective to provide to the reader a short overview of these trials. More
extensive information are provided in D1.1 [55].
2.2.1. Automotive Supplier (Spain)
FITMAN Partners
Manufacturer Partner(s): TRW Automotive
Manufacturer Nature: Large Enterprise
Technological Partner(s): Innovalia Association
The TRW, a Spanish large enterprise, automotive trial is focused on improving the health
and safety of workers in production workplaces combining FI-WARE and FITMAN specific
technologies to support risk prevention and management developing systems able to
continuously monitor workers on their workplaces and process in real-time the acquired
information in order to predict and prevent accidents and incidents, achieving the zero
accident factory.
The trial expects to see significant impacts on the following aspects:
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improvement of workers safety and security: death and health injuries on the
workplace is still an issue in Europe. Most of them are generated by the workers
themselves. The trial expects to achieve a zero accident factory;
enhancement of the competiveness: the human-centred production model fostered
within this trial will allow getting a significant increase in the companies’
productivity by the reduction of accidents and incidents;
reduction of costs and increase of benefits in production: thanks to the decrease in the
number of accidents and incidents, it is expected a significant drop of costs related to
times off sick, losses in materials due to the stop in the line, the funding and rewards
due to secure and safety factory, substitute workers training, as well as increase in the
production and the enterprise reputation and image;
increase of effectiveness in the industrial processes: the assessment and control of the
factors that are causing accidents will improve the effectiveness of the production
processes, as well as these the training and skills of workers;
improvement in company image: the improvement of the working conditions will
have a positive effects on the workers, the factory and the enterprise perception.
2.2.2. White Goods OEM (Italy)
FITMAN Partners
Manufacturer Partner(s): Whirlpool Europe Srl
Manufacturer Nature: Large Enterprise
Technological Partner(s): Engineering Ingegneria Informatica SpA
The Whirlpool trial aims at assessing the improvement Future Internet technologies can
provide to production processes via more effective and fast decisions by workers. In
particular this trial expects to have significant improvements on these three aspects:
improvement of decision process at the shop floor level, in terms of faster reaction
time (normally within the production takt1 time; i.e. 40-60 sec), supporting data and
event based;
improvement of decision process of supervisors, characterized by medium reaction
time (usually within day/shift) and pattern driven;
improvement of decision process of managers, characterized by long time reaction (
usually weeks/month) and systemic driven.
The benefits Whirlpool expects from the deployment of Future Internet technologies are the
following:
improvement of the product quality: the deployed ICT technologies are focused on
improving the fault detection ability and the reaction time, elements that directly
impact on the quality deterioration state and on the reduction of costs of non-quality
(rework, scraps, warranty cost, services etc.);
productivity: the reduction in the detection, decision and reaction time will improve
the overall efficiency of the production system;
waste reduction: a better and more informed decision process will hopefully reduce
one or more of the Lean Principles’ seven manufacturing wastes2;
1 Takt Time: The available production time divided by customer demand (see
http://www.lean.org/Common/LexiconTerm.aspx?termid=337) 2 http://www.emsstrategies.com/dm090203article2.html
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cost reduction: more effective decision process could lead to a direct decrease of
TCQ (Total Cost of Quality);
people engagement: a more effective integration of workers in the decision processes
is expected to improve people engagement with all the related benefits.
2.2.3. Textile/Clothing (Italy)
FITMAN Partners
Manufacturer Partner(s): Fratelli Piacenza SpA
Manufacturer Nature: SME
Technological Partner(s): Softeco
Even if a traditional sector, the Textile and Clothing (T&C) sector is one of the most
fragmented and challenging sectors in EU. Indeed, there are more than 70 production steps
(some very specialized), extremely wide variety of raw materials, very short product life
cycle (6 months), pro cyclic and seasonable fashion demand. Due to this peculiarities it is not
convenient (and hardly impossible) to organize a fully integrated company from raw
materials to finished product and the business ecosystem is based on a sub-supplying
organization, where some large subject (fabric, clothing producers and retailers) collect
orders, take care of designs and sales and carry on some central steps of production,
delegating all the other ones to, normally, smaller and more specialized suppliers. The T&C
sector is therefore centred on industrial clusters, where different subjects interact and share a
same common industrial culture.
The production cycles in this sector is normally characterised by periods of calm and periods
of peak demand not equally distributed or synchronised among the companies in the
ecosystem. Therefore, there may happen that at a given point in time a company is
overloaded by orders while another one is underexploited. The business ecosystem is starting
to create agreements between competitors to share production facilities to manage these
peaks of demand, improve the machineries utilization and reduce investment costs. This
sharing approach can be identified as “cloud manufacturing” if supported by specific ICT
technologies, including IoT ones, to trace the products and the machinery availability.
The objective of the Piacenza trial is to demonstrate and assess that Future Internet
technologies can actually foster the T&C “cloud manufacturing”. The trial will deploy
sensors (e.g., RFID tags and readers) in the shop floor to collect and monitor production and
process the collected data to improve the exploitation of the production machineries, labour
force and infrastructures.
2.2.4. Aeronautics OEM (Italy)
FITMAN Partners
Manufacturer Partner(s): AgustaWestland
Manufacturer Nature: Large Enterprise
Technological Partner(s): TXT e-solutions SpA
This actually is a trial contributing to two different manufacturing domains: the Smart
Factory and Digital Factory ones. In this section the focus is on the AgustaWestland Smart
Factory issues and objectives, while section 2.3.2 reports the Digital Factory trial’s elements.
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The focus of the Smart Factory Agusta trial is on using Future Internet technologies to
improve the compliance of tools management to the FOD3 (Foreign Object Damage)
normative in the Helicopter Final Assembly Line and Service Stations.
Indeed, workers in these production areas receive specific training, are subject to specific
assembly/maintenance procedures, and use peculiar toolboxes to properly use tools so to
avoid forgetting some of them in helicopters and create risks for damages to vehicles or
injuries to people as mandated by the FOD international normative. The normative envisages
also dedicated inspections by certified people to assure the assembly or maintenance
procedures were correctly executed and the vehicle can be delivered.
The objective of the trial is to further support the technicians via the deployment on the shop
floor of new instruments (e.g., Snap-on smart toolbox4 by Tools Italia S.r.l.) as data source
and analyse in (near-) real time the collected data to support continuous improvement of
workers skills, assure the best level of flight safety assurance, as well as improve the training
material and activities.
2.3. The FITMAN Digital Factory Trials
In line with the elements highlighted in section 2.1, the FITMAN Digital Factory trials focus
on the management of enterprise knowledge and therefore aim at providing, or enhancing,
tools and services able to support engineers, managers, designers, etc. in managing the whole
life cycle of a product or of a production facility and to reduce time to market, speed up
project ramp-up and reduce costs. The information managed in Digital Factory contexts, and
in the related FITMAN trials, is very sensitive being, in essence, the company know how
and/or its ability to do. In these contexts, therefore, the requirement to have specific
mechanisms to protect access to this knowledge or avoid its misuse is higher than in other
manufacturing contexts.
The FITMAN Digital Factory trials are, therefore, focused on improving, thanks to the
deployment of suitable FI-WARE GEs and FITMAN SEs, the access, sharing and processing
of the enterprise knowledge across the enterprise teams and subjects, and, at the same time,
reduce the need to develop new applications or procedures and the “knowledge provision”
time (i.e., the time required to make accessible to a subject available knowledge – for
example stored in the design engineering data silo but needed by production engineers -, or
generating new knowledge from available/acquired data).
In the following we provide a very short description of the FITMAN Digital Factory trials
with the main objective to provide to the reader a short overview of these trials. More
extensive information are provided in D1.1 [55].
2.3.1. Automotive OEM (Germany)
FITMAN Partners
Manufacturer Partner(s): Volkswagen
Manufacturer Nature: Large Enterprise
Technological Partner(s): Fraunhofer IPK
3 http://en.wikipedia.org/wiki/Foreign_object_damage 4 http://digimag.rrd.com/CAT1000a/
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The Volkswagen trial is focused on significantly improving estimates of in-house production
costs at early phases of the product development process. Indeed, in new car projects,
Volkswagen does a thorough analysis to ascertain if it is more convenient to adapt an
existing production line, or establish a new one. These estimates are based on information
grabbed from the Volkswagen digital factory system, tools and planning environment.
In particular, in Volkswagen the required information is stored in the Machine Repository
(MR) that references detailed production equipment information stored in a variety of
Planning Systems' databases (e.g. TeamCenter).
The trial focuses on the early phase “Product concept – product design”. The information
from the Machine Repository is used by the design engineering team to consider
technological standards in order to evaluate and minimize the investment costs.
2.3.2. Aeronautics OEM (Italy)
FITMAN Partners
Manufacturer Partner(s): AgustaWestland
Manufacturer Nature: Large Enterprise
Technological Partner(s): TXT e-solutions SpA
As anticipated in section 2.2.4, the Agusta trial actually contributes to the Smart Factory and
Digital Factory domains. In this section the focus is on the AgustaWestland Digital Factory
trial’s elements.
The trial deals with the helicopters’ manufacturing process and, in particular, with the last
stage (i.e., the final assembly) of this process that takes place in the Final Assembly Line
(FAL).
In the FAL area specialised workers assemble helicopter components produced in other
AgustaWestland plants or provided by external suppliers, and assembly the helicopter
following a process divided in several steps. Each of these step envisages the compilation of
specific documents that collect information specific to the assembly step, and to the
assembled components and performed activities. Each of these document is signed by the
persons involved in that step.
All these documents are finally collected, checked and delivered by the dedicated quality
departments. These documents contribute to the set-up of the “Helicopter logbook”,
containing all the information referring to the manufactured helicopter with details on all
components and subcomponents (with their serial identifiers) mounted on that helicopter.
The selection, and the processing, of the documents produced during the assembly process to
produce the “logbook” is a complex activity because these documents are spread across
different data silos (managed by different applications, using different data structures and
access methods). The objective of the trial is to improve this “logbook” production phase
thanks to technologies that easy the access and processing of information managed by
different sub-systems.
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2.3.3. Construction Industry (Portugal)
FITMAN Partners
Manufacturer Partner(s): CONSULGAL
Manufacturer Nature: SME
Technological Partner(s): UNINOVA Institute
The CONSULGAL construction trial is focused on the concrete certification process. In any
construction process the concrete handling and testing is subject to specific procedures
finalized to ensure that the design characteristics (e.g., structural resistance, durability,
structural safety, resistance to environmental conditions) set for this component, and for the
item in which it will be used, are satisfied by each load arriving at the work site.
The concrete testing procedure envisages the collection of several samples of concrete for
each truck load arriving at the work site and a set of tests (e.g., visual inspection at arrival
time to check the concrete consistency, compression resistance after 7 and 28 days).
In complex construction works (e.g., dam construction) the number of tests, and of the
related data, is significant (e.g., in the order of thousands).
The FITMAN construction trial is within the construction of the Baixo Sabor Dam
(Northeast Portugal). This dam is divided into different sections and concrete is applied to
each section separately, as planned by the Works Contractor.
It is evident that in such kind of construction, concrete noncompliance with the design
parameters may have tremendous consequence, including, for example, the risk to have to
demolish a noncompliant section and rebuild it, or to compromise the dam’s structural
resistance.
It is therefore critical to be able to properly store, quickly relate the concrete test results to
specific areas of the dam, as well as to quickly evaluate the impacts of one or more abnormal
results in the overall dam wall resistance.
Currently, all these data are recorded and circulated in paper and/or in electronic files,
analyzed using Microsoft Excel, and made available to the client on a monthly basis, while
typically on a weekly base to the supervisor.
The deployment of Future Internet technologies in this trial and context is expected to
provide the following benefits:
near real time availability to, and accessibility by, the stakeholders of the information
regarding to the project status and the concrete tests;
more efficient and effective decision processes;
automatic test results analyses comparing the test outcomes with the concrete
characteristics envisaged in the dam design;
possibility to visualize the concrete zones and related information (e.g., operation
schedule, concrete classes distribution, concrete stress values, full samples history);
paper load reduction;
documentation of access to the test conditions;
possibility to tag, for identification, the concrete samples to allow their tracking.
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2.3.4. Furniture (Spain)
FITMAN Partners
Manufacturer Partner(s): AIDIMA
Manufacturer Nature: SME
Technological Partner(s): Universitat Politècnica de València
The FITMAN furniture trial is focused on improving the responsiveness of furniture
manufacturers to customer needs and market trends through the collection and analysis of
information form data sources related to the furniture sector or, for end users (i.e., customers)
related information from the open Internet (i.e., social networks, blogs, etc.).
More specifically, the trial explores the following three areas:
furniture trends forecasting: the objective is to early detect and identify trends for
new products;
customers’ requirements management: the expectation is to identify customers latent,
collect opinions and suggestions to improve products, as well as perform sentiment
analysis;
collaborative work for product innovation: on this area there are two specific
objectives. The 1st one is to try to involve the customers in the design of new
products setting up un iterative process that collects needs and expectations, design
and proposes new products accordingly, and solicits and collects feedbacks to refine
the design. The 2nd
objective is to use Future Internet technologies to speed up the
involvement of different teams and professional skills in the product’s and production
design processes in order to both reduce the time-to-market, detect and avoid
complex or expensive manufacturing processes, and speed up the supply chain
activation.
The final objective of the trial is therefore to have products that better meet, and anticipate,
customers’ needs, provided on the market more quickly and with more efficient and effective
production processes.
2.4. The FITMAN Virtual Factory Trials
As for the previous manufacturing domains, the FITMAN Virtual Factory trials take into
account the requirements and issues elements highlighted in section 2.1 and, therefore, focus
on development and management of inter-company value chains and networks through
horizontal integration, digital end-to-end engineering across the entire value chain, and
integration of flexible and reconfigurable manufacturing systems within businesses.
The main objective of the Virtual Factory trials is to assess if and how Future Internet
technologies can affect the today’s value chains, which are relatively static and do not
provide a global manufacturing overview, to become more responsive and effective to satisfy
customer needs, as well as to meet manufacturers and citizen’s needs (e.g., more efficient
production processes, added value products, pollution reduction, waste reduction).
The provision of ICT tools and services able to improve the tangible and intangible assets of
enterprises and their value chains, and to support engineers, blue and white collars,
managers, designers, etc. in managing the whole life cycle of a product or of a production
facility is the operative approach the FITMAN project is pushing, and its Virtual Factory
trials will deploy and assess, to achieve the above objective.
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As for the previous manufacturing domains, in the following we provide a very short
description of the FITMAN Virtual Factory trials that provides to the reader a short overview
of the validation contexts and addressed needs.
More extensive information are provided in D1.1 [55].
2.4.1. Plastic Industry (France)
FITMAN Partners
Manufacturer Partner(s): Applications Plastiques du Rhône (APR)
Manufacturer Nature: Large Enterprise
Technological Partner(s): University Lumiere of Lyon 2
The plastic industry FITMAN trial aims at assessing Future Internet technologies in a market
sector where value chains play a relevant role and the European manufacturers are under
pressure to maintain their market and leading positions.
This trial is leaded by APR, a competitive actor in plastic industry in France, that aims at
enhancing the relation with its customers, suppliers and producers.
The trial expected benefits and impacts can be summarized as follows:
improve the effectiveness of business collaboration assuring better reactivity to
requests for quotation and delivery, improving the procurement process of raw
materials, and increasing the confidence of APR customers concerning products
quality and its timely delivery;
improve the production processes in terms raw material procurement, quality of
information processing, reduction of processing times;
reduction of information integration costs to face the huge amount (more than 2500
business projects per year) and diversity of customers’ projects;
improve the quality and effectiveness of the investment strategies;
enhance customer satisfaction and develop or strengthen partnerships with the top 50
customers.
From an operative point of view this FITMAN trial aims at “maximizing information quality
as support for successful business collaboration” and at upgrading existing business
collaboration processes by proposing more integrated, service-enabled and fully automated
processes.
2.4.2. Manufacturing Resource Management (UK)
FITMAN Partners
Manufacturer Partner(s): Sematronix Limited
Manufacturer Nature: SME
Technological Partner(s): Coventry University
The overall aim of this trial is to enhance the services offered by Sematronix to its clients
through the deployment of Future Internet technologies.
The Sematronix client base consists of clusters of SME (called members), who subscribe to
the clusters in order to access services which may provide support to individual members, or
to cooperating members that establish virtual organizations (VOs) to better compete with
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larger enterprises. The services offered span from identification of new business
opportunities, tenders selection and SMEs consortium matching, manufacturing sensor
monitoring applications.
The current services present some weaknesses like:
a consistent volume of custom code that implies higher costs for service
development/customization and code maintenance, as well as to align services to new
technologies and platforms updates;
the selection and management of tender sources is mainly performed by human
operators, which limits the possibility to set up new client clusters (or makes this set
up costly);
member’s capability knowledge base management is not fully automated and
negatively impacts tender opportunities;
the selection and prioritisation of tender opportunities still requires human
intervention to achieve an acceptable precision level;
identification of consortia that better match tender opportunities suffers a similar
problem;
sensors integration is heavily based on customised software which means the need to
do ad hoc developments to support new protocols or technologies;
complex event processing is performed using a prototype CEP system that does not
provide advanced features for the definition and management of the required event
patterns.
Therefore the trial objective is to embed Future Internet technologies within the Sematronix
services to solve some of the above issues (e.g., reduce custom software development,
simplify the integration of new protocols and sensors, reduce the deployment costs for new
clusters, be able to perform more complex events and data analysis, increase the flexibility
and adaptability of the service platform) and increase the effectiveness of the support
Sematronix provides to members and their VOs.
2.4.3. LED Lighting (Germany)
FITMAN Partners
Manufacturer Partner(s): COMplus Automation GmbH
Manufacturer Nature: SME
Technological Partner(s): Fraunhofer IPK Berlin, COMplus Automation
GmbH
Also this trial is based on a cluster of SMEs that produce LED based lighting systems for
private, industrial or public use. These enterprises already collaborate to share their
capabilities, jointly design new products (or satisfy customers’ orders), and perform the
production of required components using an IT service platform essentially developed within
the Supply Network Mapping and FACIT-SME (Facilitate IT-providing SMEs by Operation-
related Models and Methods) research projects.
The current solution presents the following issues:
difficulties in predicting the time span of collaboration on specific activities;
difficulties in efficiently and quickly adapt business plans to take into account new
requirements or technologies, as well as new possible applications;
difficulties in identify and access the right, most appropriate and most up to date
information;
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difficulties in actually collect and share the exchanged information because most of
the communications are between individuals and via phone;
the knowledge is not effectively shared due to the availability in time of partners or
experts;
differences in IT landscapes among the networked enterprises and lack of common
standards;
lack of widespread sufficient skill in using the application services.
The trial’s objectives are to deploy Future Internet technologies and assess them in solving
the above issues and, specifically, improve the knowledge sharing among the networked
enterprises, accelerate and enhance the identification of the partnerships for specific
products, dramatically speed up the early phases of the engineering project, as well as to
more effectively and efficiently insure the compliance of the systems to requirements and
constrains since the early design phase and across all involved partners (supplier).
2.4.4. Machinery for Wood (France)
FITMAN Partners
Manufacturer Partner(s): GEOLOC System
Manufacturer Nature: SME
Technological Partner(s): Université Bordeaux 1
The FITMAN machinery for wood trial deals with improving the collaboration among a set
of subjects (e.g., final customers, product engineers, suppliers) and SEGEM-Macbo, an SME
developing special machinery for the wood industry. This market is more and more based on
multi-actors partnerships to address customers’ needs.
As for other market segments, these actors have the need to reduce costs and engineering
delays (Time-to-market).
The trial will specifically focus the order entry and order tracking processes that involves
many actors (e.g., customers with their orders, suppliers that have to provide specific
components), and is currently managed using a set of non-integrated applications (e.g.,
Microsoft Excel, SAP BusinessObjects), communication technologies (e.g., fax, email, FTP)
and order formats (e.g., PDF or Word documents, Excel spreadsheets). This approach, as
evident, requires a lot of human interventions to process the exchanged information and to
manually insert it into the main applications (e.g., SAP BusinessObjects).
The deployment of Future Internet technologies in this trial is finalised to implement and
experiment an open platform providing collaborative services to support the above actors and
implement workflows to support the order entry and tracking processes integrating processes
cross-enterprises and internal processes and automate the flow of information across the
whole set of phases (commercial, design, manufacturing and installation).
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3. THE FITMAN REFERENCE ARCHITECTURE
3.1. Why a Reference Architecture
As the size and complexity of a system increases, its design, in terms of overall system
structures and interactions, becomes the central problem. An architecture, therefore, is meant
to design the high-level structure of a system in order to assure that the identified
architectural components and their interactions are able to satisfy the needs and goals of the
system [30]. The design of an architecture is based on a thorough understanding of the
domain to be modelled and to its specific needs and goals.
Even if focused on the manufacturing domain, the FITMAN project actually addresses issues
relative to a wide set of manufacturing systems, as made evident from its trials. Therefore,
the design of a specific architecture is not reasonable due to the lack of needs and goals of a
specific system. In situation like this, the best approach is to design a Reference Model or
Reference Architecture that provides a more abstract description from which concrete
architectures for the specific realities (e.g., FITMAN trials) can be actually derived.
Reference architectures start to appear in contexts where the multiplicity reached a critical
mass triggering a need to facilitate system design and life-cycle support.
A Reference Architecture captures the main characteristics of the architecture of a set of
systems. Reference Architectures [31] “start to have value when the multi-* factor is large
enough. When creating a single system, we need engineering, design and architecting
competencies. However, when the scope increases and multiple product creations are
coupled, then Reference architectures are indicated. For small stand-alone developments
Reference Architectures are overkill”.
The purpose of a Reference Architecture, therefore, is to provide directions for the
development of actual architectures for these systems, or their new or extended versions.
A Reference Architecture is normally characterized by the following three elements:
a common lexicon and taxonomy that is tied to the application domain (e.g.
automation in the FITMAN case);
a common architectural vision that helps in focusing common elements and in
deriving synergic actual architectures;
modularization that helps in focusing subsequent refinement activities and in assuring
integration and, to some extent, interoperability.
Reference Architectures facilitate the design and management of product family architecting
and evolution, smoothing impacts due to market changes in contexts and needs.
As depicted in Fig. 3-1 (source [31]), a Reference Architecture is an elaboration of a mission,
vision and strategy within a specific application domain (as in FITMAN) or context that
takes into account the requirements expressed by the customers or reference markets, as well
as the technological opportunities.
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Fig. 3-1: Role of a Reference Architecture
A Reference Architecture, therefore, provides a description that, on the one hand, is more
abstract and general than a concrete architecture designed for a specific context, but, on the
other hand, it provides a better understanding of the system constraints, evolvability and
reusability, and a specific guide to design concrete architectures that exploit synergies,
evolvability and integrability.
The process of deriving specific architectures and implementations from a Reference
Architecture is depicted in Fig. 3-2. The actual architecture for a specific context (e.g., a
FITMAN trial) is obtained refining the Reference Architecture taking into account the
specific needs and requirements, as well as the specific constraints and opportunities of the
context at hand [32].
Fig. 3-2: Derivation of specific architectures and implementations
TechnologyCustomers
Market
Mission
Vision
Strategy
existing architecturesnew or evolved
architectures
ReferenceArchitecture
Organization A
Organization B
Organization …
elaboration
guid
ance
Context specificconstraints & opportunities
ReferenceArchitecture
Context specificArchitecture
Context specificneeds & requirements
Transformation Transformation
Context specifictechnologies
Context deploymentconstraints
Context specificimplementation
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The final step bringing to the specific system implementation takes into account the actual
implementation in the light of the technologies and deployment constraints of the context at
hand.
To complete the scenario, Fig. 3-3 reports a very high level view of the Reference
Architecture envisaged by the Industrie 4.0 Working Group [3] to interconnect the physical
(IoT – Internet of Things) and digital worlds (IoS - Internet of Services). As evident from the
figure, this high level Reference Architecture addresses different business domains (e.g.,
Industry, Energy, Mobility, etc.) and meets the innovations envisaged by the Industrie 4.0
analysis and programme.
Fig. 3-3: Industrie 4.0 Reference Architecture for connecting the IoT with the IoS
A similar approach is envisaged by the Industrial Internet document [2] where the envisaged
innovation categories that a Reference Architecture has to integrate to foster the development
of the Industrial Internet can be characterized as follows:
deployment and integration of sensors (i.e. smartness) into the design of new
industrial equipment (as well as retrofitting existing equipment);
new standards to enable deeper integration of data from similar assets from different
Original Equipment Manufacturers (OEM) or from different asset categories;
new platforms that enable building specific applications using a shared
framework/architecture;
new business practices that fully integrate machine information into decision-making.
The above scenario helps positioning the FITMAN approach and Reference Architecture. To
avoid being too abstract and general the FITMAN project actually designs three Reference
Architectures one for each of the manufacturing domains described in §2.1 (see pag. 9).
Even if a manufacturing context does not fit exclusively and exactly in one of the Smart,
Virtual and Digital Factory domains, nevertheless having different reference architectures
for them helps to better satisfy the requirements and characteristics of these manufacturing
domains, identify architectural components and interaction/integration patterns that more
specifically characterize them. This approach, therefore, provides more effective indications
Compiling & networking of functions, data & processesManagement of end devices and systems
Business Processes
Services Services
Business Processes
Services ServicesApp.
Solutions
Mobility Energy Industry Buildings
Town CompanyLevel
Internet-basedSystem
& service platforms
Internetof Things
Internetof services
Applications
Requirements
Model-based development
platforms
Connectivity(IPV6)
Knowledge of business areas
and applications
Access to marketsAnd customers
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and guidelines for the design of specific architectures addressing actual operational contexts
(e.g., FITMAN trials) as discussed above and indicated in Fig. 3-2.
Before moving to the description of the FITMAN Reference Architectures for the three
automation domains, we have to review the draft Reference Architecture reported in the
project’ DoW (see Fig. 3-4). This picture tries to simply characterize next generation FI-
based enterprise ICT systems and applications as analysed and reported by the FInES Cluster
Architecture Task Force5 and the MSEE project
6. The DoW draft architecture highlights the
requirement to design and develop collaborative and interoperable enterprise systems for the
next generation manufacturing systems, and that these next-generation systems must be able
to address he needs of an ecosystem of enterprises rather than the specific requirements of a
single subject (manufacturing enterprise or OEM).
The three layers depicted in Fig. 3-4 essentially try to highlight both the different “contexts”
(e.g., single enterprise/factory premise, business ecosystem, and the extended-ecosystem7 –
identified as FI level in the picture) and the essential data, models, knowledge and
ontologies, integration and interoperability requirements the future manufacturing systems
must address.
Fig. 3-4: FITMAN DoW draft Reference Architecture
5 FInES Architectural Design Principles (ttp://www.fines-cluster.eu/fines/jm/FInES-Task-Forces/fines-architectural-design-
principles.html) 6 Manufacturing Service Ecosystem (http://www.msee-ip.eu) 7 This is the level that will characterize the Cyber-Physical Systems (CPS) as depicted in the German Industrie 4.0
programme [3] (“In the future, businesses will establish global networks that incorporate their machinery, warehousing
systems and production facilities in the shape of Cyber-Physical Systems”)
Cloud ManufacturingKnowledge
Future Internet Core PlatformGeneric Enablers
Applications/Services Ecosystems
Service Delivery Framework
Cloud Hosting and I/face to Network Devices
Internet of Things and Data/Context Mgmt
Security, Privacy and Trust
Business Ecosystem
Individual Factory/Enterprise
Future Internet Cloud
Interoperability of
Services/PlatformsAlignment of
Knowledge/Models
Human-centric Manuf. Models
IoT-based Intelligent Manufacturing
Ecosystem Skills& Knowledge
Ecosystem Manuf. Capacity
Domain Ontologiesand Models
Ecosystem Collaboration &Innovation Platform & Services
Product Life Cycle Management Platform
Service Life Cycle Management Platform
Innovation Life Cycle Management Platform
Collaborative Business Process / Project Mgmt
Production Planning and Scheduling
Smart Factory (In)Tangible Assets
Digital Factory (In)Tangible Assets
Virtual Factory (In)Tangible Assets
Enterprise [Mobile] ApplicationsPlatform & Services
Enterprise Resource Planning ERP System
Customer Relations Management CRM System
Supply Chain Management SCM System
Manufacturing Excution System MES
Automation, Control and SCADA System
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The DoW draft reference architecture tries to highlight the main challenges business
activities, and manufacturing in particular, must address to maintain a coherent and
consistent alignment of models and data/information/knowledge across a wide set of
subjects, systems and boundaries, and at the same time assure their sharing and protection.
The blue bordered boxes and arrows in the picture represent respectively
data/information/knowledge repositories or sources and flows necessary to support business
and production processes, as well as to assure consistency and synchronisation among the
different “contexts”. The red boxes in the figure sketch the main services that characterise
each layer, while the red arrows highlight the main interaction patterns and issues.
The Smart, Digital and Virtual Factory reference architectures described in the following
take into accounts the points discussed in this section identifying the functional elements that
characterise the three manufacturing domains, as well as the strategies, requirements,
opportunities and constraints highlighted in the previous chapters.
3.2. The FITMAN Smart Factory Reference Architecture
The FITMAN Smart Factory reference architecture has to address the requirements
highlighted in the section 2.1.3 (on pag. 13) and, among the issues and challenges listed in
sections 2.1.1and 2.1.2, the ones that specifically affect this manufacturing domain. The
FITMAN Smart factory trials needs summarized in section 2.2 have, of course, to be fulfilled
by the FITMAN Smart Factory architecture even if each trial could not require and deploy
each of the envisaged functionalities.
The FITMAN Smart Factory architecture has therefore to envisage features that, on the one
hand, collects, adapts and dispatches events coming from a wide set of sources, and, on the
other hand, pre-processes, integrates, analyses and provides to users of the Smart Factory
functionalities customized views or hints to govern and improve the production processes.
Due to the need to manage a production facility (and the shop floor in particular) and react to
events occurring in this environment the FITMAN Smart Factory architecture is more an
Event Driven (EDA) architecture [8][9][10][11] than a Software Oriented (SOA) one.
The application of EDA-based solutions in manufacturing, although not consolidated and
systematic, has gained a considerable attraction in recent years [12][13]. Indeed, in the last
years many attempts [14][15][16] [17][18][19][20] have been made to specify, develop and
implement a SOA-based or EDA compliant distributed embedded control and automation
systems covering the major levels of the ISA´95 Enterprise Architecture.
The Smart Factory architecture has both an upstream flow of data and information, as well as
a downstream flow that is used to “govern” the factory production processes.
Fig. 3-5 depicts the overall FITMAN Smart Factory architecture. The picture highlights:
the users of the Smart Factory functionalities. As sketched in the figure the
functionalities are targeted to support: application services (e.g., legacy systems),
through which production processes are managed, and workers (both blue and white
collars, both to improve the workplaces and to offer them customized views of the
production facility and processes or to provide them the opportunity to act on these
elements). Application services and workers can be both within the production
facility or even outside (e.g., remote maintenance services managed by suppliers or
maintainers);
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the sources of the data required to achieve the management objectives of the Smart
Factory systems. As highlighted in the picture the data can originate from the outside
of the production plant (e.g., events coming from suppliers, logistics operators, etc.
for example carrying information about the delivery of components for Just in Time
production),, as well as from within the production facility;
two middle layers that, as detailed below, provide functionalities to manage collected
events (or received control instructions), (pre-)process them, and provide added value
to the users of the Smart Factory system.
Fig. 3-5: The FITMAN Smart Factory Reference Architecture
Fig. 3-5 differentiates the sources of data/events grouping them in four different boxes:
External Events: are events, relevant for the production processes, coming from the
outside of the production facilities (e.g., warehouses, material-tracking events). The
structures and dispatching mechanisms of these events are quite variable;
Shop Floor (Sensors, …): under this category the picture collects events generated by
commodity sensors deployed within the shop floor (e.g., smoke sensors). This
category of sensors uses communication mechanisms and protocols, data structuring
not specific of the manufacturing environment (even if we have to expect in the near
future this category to use things like CoAP);
Shop Floor (RFID readers, …): this box represents sensors used to identify and track
materials, tools, goods and other elements within the production facilities. The
communication mechanisms, protocols and data structures are normally quite
standardized ([21][22][23] [24][25]) by subjects like ISO, GS1, EPCGlobal Inc;
Shop Floor (PLCs, OPC UA complaint devices, …): this last box represents other
manufacturing components deployed within production cells and lines that are used
to monitor and control production steps. Normally these components have more
computing power and more advanced communication capabilities and exposes some
kind of API. There are currently standardization efforts to define a common set of
External Events(suppliers, …)
Shop Floor(sensors, …)
Smart Factory Back-end Layer Events Collection & Preprocessing
(Publish/subscribe, security, Complex Event Processing, …)
Shop Floor(PLCs, OPC UA complaint devices, …)
Shop Floor(RFID readers, …)
Smart Factory Gateway Layer Device Management & Data Adaptation
(M2M, GSN, GS1 EPC ALE Service, Protocol conversion, …)
Smart Factory Workplace Layer(HMI, Safety, …)
Legacy Systems(ERP, SCADA; MES, …)
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standards to support standardized APIs and in particular the OPC UA [26], promoted
by the OPC Foundation [27], and the US MTA MTConnect [28].
All these categories of events and data sources must be managed and related events
collected, translated into a common format, and made available through a common API to
avoid persist in having vertical, disjoint information silos.
Most of these sensing elements need also to receive commands (e.g., instructs an EPC Global
ALE Service to provide events related to specific RFID readers or RFID tags; activate a
specific procedure on a PLC). Therefore, a Smart Factory reference architecture has to try to
depict a common mechanism for the downstream flow of commands and control instructions.
Unfortunately, while for the upstream flow the standardization effort has achieved some of
its objectives8, a similar result is still in a very early stage for the downstream flow. For
example, the OPC UA standard on the one hand has defined a standardized API (based on
the SOA paradigm) to interface manufacturing devices, on the other hand, it has not yet
defined any standard that identifies common features and characteristics for manufacturing
device categories exposing an OPC UA interface9. Therefore, while interacting with an OPC
UA device can be performed in a quite uniform way, as well as acquiring some data from it,
controlling the same device is still strongly dependent on the device type and device
manufacturer.
The Fig. 3-6 details the FITMAN Smart Factory Gateway Layer. The objective of this layer
is to provide an interface as uniform as possible to the upper layers both for the collected
data, as well as for the downstream command flow. As depicted in the figure, this layer
envisages a Protocol Adapters component that, thanks to the use of a plug-in approach, can
interface different data source (see their description in the bullets above) and mask the
specific protocols and data exchange patterns these data source requires.
The Protocol Adapters component, therefore, provides a protocol-independent interface to a
potential wide and time evolving set of data source.
The Data Collection & Adaptation Sublayer component, instead, is in charge of both
managing the capture of the data from the deployed data sources, exposing the collected data
using a more uniform data structure format, as well as feeding the upper layer using a
uniform protocol. This component can therefore include functional elements that are
specifically tied to the deployed data sources.
Just as an example, acquiring data regarding RFID tagged goods or tools, implies the
deployment in the environment of RFID readers able to detect tagged goods in the
environment. These RFID readers, in our architecture, are part of the Protocol Adapters
component and have to support and manage the protocol and data exchange patterns
envisaged by the RIFD standards for the RFID reader to tag interaction. The RFID readers
expose a command and query interface, as specified by the GS1 EPC Global standards,
toward upper layers and, in the GS1 EPC Global architecture, specifically toward the EPC
Global ALE Service [22][23]. The ALE Service functionalities are part of the Data Collection
& Adaptation Sublayer component, so that this component can interface the RFID sources
via an interface that does not depend on the specific hardware and RFID radio protocols
used. At the same time the data collected from the RFID readers are fed to the upper layer in
our architecture using an interface that is independent from the specific source (usually via a
RESTful API).
8 For example the MTConnect standard defined by the US ATM (Association for Manufacturing Technology) is a read-
only standard that only defines the extraction of data from control devices 9 An example of a fruitful standardization to this end is the one performed defining standardized Management
Information Base (MIB) to be used in connection with the SNMP to supervise and manage network devices
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The Device Management Sublayer component in Fig. 3-6 performs similar adaptation for the
downstream command flow.
Fig. 3-6: The FITMAN Smart Factory Gateway Layer Architecture
The Fig. 3-7 depicts the FITMAN Smart Factory Back-end Layer that is in charge managing
the collection and dispatching of the events coming from the FITMAN Smart Factory
Gateway Layer, perform some pre-processing and analysis and provide data and outcomes to
the legacy systems or to the applications supporting the end-users.
Fig. 3-7: The FITMAN Smart Factory Back End Layer Architecture
As depicted in the figure, this layer envisages the following functional components:
the Security Assessment Features component that provides features to anonymise
data and check its quality. This module provides a kind of off-line functionality to be
used to assess if the adopted anonymization algorithms actually achieve their
Smart Factory Gateway Layer
Data Collection & Adaptation Sublayer
Device Management Sublayer
Protocol Adapters
GS1EPC
GSN …OPC UA
Smart Factory Back-end Layer
Security Assessment
Features
Event Collection&
DispatchingFeatures
ConfigurationManagement
Features“Syntactical”CEP Features
“Dynamic” CEP&
Reasoner FeaturesObj. a
Obj.
Obj. …
Pat. X
Pat. Y
Pat. …
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objectives and therefore make documentable and visible the compliance of the
management of business confidential or personal data to company policies or national
or European normatives. This component play a relevant role in all smart factory
contexts in which data regarding workers is collected and processed (for example to
improve the safety of workers as in the TRW trial), or contexts in which business
confidential data have to be shared, in a properly anonymised way, with external
subjects;
the Event Collection & Dispatching Features component is in charge of receiving
events from the lower layer and dispatch it to interested components. Having to
manage shop floor related events, which are characterized by their confidentiality
nature (these events are strictly related to the production, its organization, etc.) and by
their amount, timing and variability, this component has to provide advanced features
to control access to these events and to scale. This component is a key element of the
FITMAN EDA approach that promotes a unified management of events across all
levels of the automation pyramid based on the adoption of a publish/subscribe model
that pushes events to interested listeners as compared to the pull model of more
traditional SOA approaches. Push models have normally unidirectional,
asynchronous and fire-and-forget communication patterns, promoting the use of
highly decoupled systems in which the only relevant issues are related to well-
defined message semantics, as well as provide better scalability;
the “Syntactical” CEP Features component is the element in charge of performing
analysis of the event’s streams normally based on a pattern-search approach within
real-time event’ streams. The component is, therefore, able to identify anomalies in
the collected data and to generate new events (typically directed to the Event
Collection & Dispatching Features component to be pushed to interested
applications) or directly actions (normally toward the Configuration Management
Features component). This component is, therefore, one additional key element of
the FITMAN EDA approach and supports off-loading supervising and control logic
from traditional production supervision systems (e.g., SCADA and MES systems)
improving a more fast and less expensive adaptation10
of the production management
and control systems;
the “Dynamic” CEP & Reasoner Features component provides more advanced
analysis functionalities as compared to the previous component. As depicted in the
Fig. 3-7 this component has to provide events analysis capabilities that try to achieve
an objectives (e.g., reduce the energy consumption in producing goods) instead of
identify a pattern in the collected data. This component, therefore, needs more
complex reasoning capabilities to achieve the provided objectives, and normally
needs to process a wider set of data. As for the previous component the outcomes of
this component can be new events (normally to be dispatched via the Event
Collection & Dispatching Features component), or actions to be normally managed
via the Configuration Management Features component;
the Configuration Management Features component is in charge of supporting the
management of the configuration of devices and components in the lower layer. As
depicted in Fig. 3-7, this component can be fed by the upper components (e.g., the
legacy systems), as well as by the two CEPs. This component in charge of managing,
with the limitation and issues highlighted in the previous pages, the conversion of the
10 Indeed CEP engines provide functionalities to structure and deploy the pattern to be searched, as well as to design the
actions to be performed when a pattern is identified. Setting up new analysis, or modifying existing ones, requires simple to
properly structure the pattern to be searched and the related actions, testing and deploying them, as compared to changes of,
or integration to, the SCADA or MES systems software
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downstream control flow, or actions received by the CEP components, into
operations and command toward the lower layer components.
A final element to be described is the Smart Factory Workplace Layer component that is in
charge of interacting with, and supporting, the workers (both blue and white collars) in their
daily activities within the production facilities. This component has to support next
generation, attractive human-machine interaction (Human-centred Manufacturing), through a
disparate set of devices (e.g., mobile devices, 3D visors, wearable devices, etc.) and
modalities (graphical rendering, Augmented Reality, Virtual Reality, etc.). It is expected that
this component will be heavily based on new HTML-centred standards (e.g., HTML5,
XML3D, Web Components, etc.), and approaches to improve usability across disparate
platforms, integrability, flexibility and data access on the move. The final objective of this
component is therefore to substantially increase the efficiency and workers’ safety as well as
a user-friendly, ergonomic and intuitive interaction between workers and machines.
3.3. The FITMAN Digital Factory Reference Architecture
As for the Smart Factory, the FITMAN Digital Factory reference architecture has to address
the specific requirements highlighted in the section 2.1.4 (on pag. 14), as well as the related
issues and challenges listed in sections 2.1.1and 2.1.2.
As stated in previous sections, a manufacturing context referring to, or implementing, the
FITMAN Digital Factory architecture, and specifically the FITMAN Digital Factory trials,
have to refine this reference architecture and can deploy and implement only a subset of the
envisaged functionalities. The Digital Factory domain needs functionalities to make a more
intelligent and informed decisions at the various levels (strategic, planning, operational, shop
floor) accessing and processing all the required information that is currently kept in isolated
silos, therefore making difficult to streamline the work based on a natural and controlled
flow of information. The main issue that the Digital Factory Reference Architecture has to
address is to envisage functional elements able to provide effective means to consolidate a
view on Product Life Cycle Information, so that more flexible and contextual access, query
and analysis can be performed on the distributed product information. This implies that
Digital Factory architecture should provide means to represent and expose data coming from
multiple sources, so that the information in legacy systems (planning tools, ERPs, CRM,
etc.) and also in open contexts like social networks can be exploited. To this end it is
worthwhile to highlight the recent explosion of data entering into the landscape of business
companies, with an entirely new class of data that was never envisioned before and by legacy
systems. Therefore, one of the objective of the FITMAN Digital Factory reference
architecture is to enable organization to incorporate these new data sources into their
business and analytics applications.
Moreover, industrial competitiveness depends not simply on the information availability, but
also on its quick and effective presentation of such information in the required format for
proper decision-making.
To this end, the FITMAN Digital Factory Reference Architecture reported in Fig. 3-8
envisages:
a set of data sources as provided by legacy systems or acquired from external sources
(e.g., Internet social networks). These data sources, as stated above, have direct
relations with the produced goods, marketing or brand strategies, trends discovery,
etc. In Fig. 3-8 legacy systems actually have a double role: as storage systems that
manage products related data, which have to be suitably accessed, processed and
integrated to fulfil the objectives of the Digital Factory architecture (see the bottom
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data sources icons in the figure); as well as services (see the azure Legacy Systems
box in the figure) to be integrated within the overall functional architecture;
the users of the Digital Factory functionalities. As sketched in the figure the
functionalities are targeted to support end-users (blue and white collars, individually
or in teams) in their daily activities, both within and outside the manufacturing
company, and along the whole lifecycle of produced goods (e.g., since the product
design phase, till its disposal; production line design, operation, maintenance,
restructuring or disposal, etc.);
two middle layers that, as detailed below, provide functionalities to access the data
silos, aggregate and manipulate these data, process and render them using rich and
effective presentation and visualization features to support advanced business
processes.
Fig. 3-8: The FITMAN Digital Factory Reference Architecture
Fig. 3-9 details the functional components of the lowest layer envisaged by the FITMAN
Digital Factory Reference Architecture. As indicated in the picture, this layer envisages two
different pillars:
the Product Lifecycle & Metadata Management Sublayer: this component collects
functionalities to manage access to a disparate set of, normally structured, PLM
related data and metadata and has the objective of providing a consistent, integrated
and uniform representation and interface to them. This includes the capability to
perform syntactical and semantic transformation of the available data and metadata in
order to assure interoperability and the accessibility from a wide set of services and
systems;
the Unstructured & Social Data Analysis Sublayer: this component, instead, is
focused on providing access to information, usually unstructured, as available in
outside and open systems (e.g., social networks).
Product Lifecycle Data Visualisation & Manipulation Layer Product Lifecycle Data Visualisation, Presentation, Rendering
Product Lifecycle Data & Analysis Management LayerProduct Lifecycle Data Management, Access, Query, Analytics
Legacy Systems(ERP, LMS, PLM, PDM, CAD, …)
Product Data
Process Data
MKT Data
XXX Data Social Net
Data
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As for the Smart Factory reference architecture, these Digital Factory sublayers envisage a
set of plug-ins at the lowest level that interface the different data sources. In particular, the
Product Lifecycle & Metadata Management Features component will take responsibility for
interfacing the different PLM data sources, while the Social Media Connectors component
will be in charge of feeding the Unstructured & Social Data Analysis Sublayer picking data
from the social networks or web sites.
Both components therefore mimic the approach envisaged by the Java Service Provider
Interface (SPI) [33] decoupling the upper components from the details of the accessed data
sources. This approach will be further enhanced by the Interoperability Services component
so that upper components get a uniform access interface and uniform data and metadata
formats. The final objective of these components is to support the adoption of standard
metadata for product data and knowledge representation, support interoperability among
systems and data format standards thanks to the support of different access protocol toward
the data sources, syntactical and semantically enriched data transformation, uniform browse
and query functionalities.
Fig. 3-9: The FITMAN Digital Factory PL Data Management Layer Architecture
In addition, on the Unstructured & Social Data Analysis Sublayer side, the FITMAN Digital
Factory reference architecture envisages two additional components. The first of these
components (see the Processing/Querying Engine in Fig. 3-9) supports the pre-processing
the acquired unstructured data, and the provision of a first set of query functionalities. The
second component (see the Trend & Sentiment Analysis Engine in Fig. 3-9) focuses on
performing specific analysis of the acquired data to support trend and sentiment analysis.
These kind of analysis are becoming particularly relevant [34] [35] in many manufacturing
contexts, and in some of the FITMAN trials.
Product Lifecycle Data & Analysis Management Layer
Product Lifecycle & Metadata Management Sublayer
Product Data
Process Data
MKT Data
XXX Data Social Net
Data
Product Lifecycle & MetadataManagement Features
Interoperability Services
Unstructured & Social Data Analysis Sublayer
Social Media Connectors
Twitter …FBRSS
Processing /Querying Engine
Trend & Sentiment Analysis Engine
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Fig. 3-10 depicts the functional components envisaged by the FITMAN Digital Factory
architecture Product Lifecycle Data Visualisation & Manipulation Layer whose main
objective is to support the effective, efficient and customized access and rendering of the
required and available information to the white and blue-collars involved in the
manufacturing phases and processes.
As indicated in the figure this layer envisages a set of functional components that, on the one
hand, enhance the analysis and query features provided by the underlying components, on
the other hand, are able to support end-users in effectively using the available services and
efficiently selecting and accessing the information required and necessary for their activities.
To this end the envisaged functional components are:
the Unstructured Data Analysis Features component complements the features on the
underlying components to extract knowledge from structured and unstructured data,
even supporting the management of data analysis pipelines for data and knowledge
transformations and interpretation;
the Application Mashup Features component supports the integration and
composition of services, data sources and workflows to satisfy end-users needs.
Among its features this functional component has to provide support the DIY (Do-It-
Yourself) metaphor so that end-users with minimal skills can design and create new
services or workflows to satisfy their needs as they emerge;
the Unstructured & Social Data Analysis Features component complements and
completes the functionalities of the homonymous underlying component on issues
related to the design and management of reports, as well as to support data
visualization, usually, but not restricted, related to the trend and sentiment analysis;
the 3D Rendering Features component is focused on providing functionalities to
support web based 2D and 3D rendering and interaction to access and manipulate
data and digital objects (e.g., CAD models, technical sheets, assembly procedures,
etc.) as requested by end users. This component has to possibly support web related
2D and 3D standards, as well as the possibility for services in the FITMAN platform
to interact with the 2D and 3D environments and objects so to support more dynamic
and interactive interaction experiences;
finally the Advanced Data Visualization & Manipulation Features component has to
provide a uniform access to the services, data and objects and to support a possibly
wide set of rendering devices (including mobile and wearable ones), and
collaborative visualization so that end-users can use the features provided by this
component to perform both their personal, as well as joint activities.
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Fig. 3-10: The FITMAN Digital Factory PL Data Visualization & Manipulation Layer Architecture
Even if not strictly required, it is expected that the standards adopted for the rendering and
interactions be aligned with the ones envisaged for the FITMAN Smart Factory reference
architecture. Therefore focused on the mentioned new HTML-centred standards (e.g.,
HTML5, XML3D, Web Components, etc.), both to improve usability across disparate
platforms, integrability and flexibility, as well as to support contexts and trials with needs
pertaining to the smart and digital manufacturing domains.
3.4. The FITMAN Virtual Factory Reference Architecture
As for the previous reference architectures, the FITMAN Virtual Factory architecture has to
address the specific requirements highlighted in the section 2.1.5 (pag. 15), as well as the
related issues and challenges listed in sections 2.1.1 and 2.1.2.
The Virtual Factory architecture, according to the analysis in § 2.1.52.1.4, has to envisage
ICT functional elements able to support collaborative supply networks, and, therefore,
essentially focused on assuring inter-company communication, integration, collaboration and
interoperability, as well as on managing tangible and intangible assets [36] [37]. As indicated
in Fig. 3-11, the main beneficiaries of the Virtual Factory functionalities are the legacy
systems through which the end-users will normally manage the business processes envisaged
by the Virtual Factory domain.
The FITMAN Virtual Factory Reference Architecture reported in Fig. 3-11 envisages:
a set of sources of information and data related to tangible and intangible assets that
span from supply chains (through which structured data like: orders, invoices,
packing lists, transportation statuses, etc. are exchanged), value networks (through
which knowledge and value is created and exchanged [36] [38] [39]), and, more
generally, the business ecosystems (through which suppliers, distributors,
competitors and customers compete and cooperate to produce goods, improve them
and create new ones [40] [41] [42]);
Legacy Systems(ERP, LMS, PLM, PDM, CAD, …)
Product Lifecycle Data Visualisation & Manipulation Layer
Unstructured & Social Data Analysis Features
Visualization & ReportCreator EngineUnstructured
Data Analysis Features
Application MashupFeatures
3D RenderingFeatures
Advanced Data Visualization & Manipulation Features
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two middle layers that, as better described and detailed in the following, must, on the
one hand, manage discovery, classification and management of data pertaining to
tangible and intangible assets involved in virtual factory business processes, and, on
the other hand, support cooperative business process design and management to
assure cross-enterprise boundaries interoperability and collaboration;
on the top layer the figure reports enterprise legacy systems to stress the relevance of
the interoperability and integrability across enterprises. Indeed, end-users normally
interact and collaborate through business processes involving legacy systems within
and across enterprises.
As evident from the objectives of the virtual factory domain, standards play a key role in this
context, both to structure and exchange the exchanged information (e.g., standards like
OASIS UBL11
, RDF12
, OWL13
), to describe available services [43] [44], as well as to design
(e.g., BPMN14
, UML AD15
), exchange (e.g., XPDL16
, BPDM17
), or execute (e.g., BPEL18
)
business processes [45].
11 See the OASIS UBL Technical Committee web site for more information (https://www.oasis-
open.org/committees/tc_home.php?wg_abbrev=ubl) 12 See the W3C Resource Description Framework (RDF) status page for more information
(http://www.w3.org/standards/techs/rdf) 13 See the W3C Web Ontology Language (OWL) Working Group web site for more information
(http://www.w3.org/2007/OWL/wiki/OWL_Working_Group) 14 See the Object Management Group (OMG) web section on BPMN (http://www.omg.org/spec/BPMN/index.htm) . OMG
BPMN 2.0.1 has been published by ISO on November 2013 as ” SO/IEC 19510:2013 - Information technology - Object
Management Group Business Process Model and Notation” 15 For details on UML Activity Diagrams (UML AD) see the OMG document ”UML 2.0 Superstructure Specification”,
Mars 2011 (http://www.omg.org) 16 For references and specifications see the Workflow Management Coalition XDPL web site (http://www.xpdl.org/) 17 See the OMG web site for BPDM specification (http://www.omg.org/spec/BPDM/) 18 See the OASIS WSBPEL Technical Committee web site for more information (https://www.oasis-
open.org/committees/tc_home.php?wg_abbrev=wsbpel)
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Fig. 3-11: The FITMAN Virtual Factory Overall Architecture
Fig. 3-12 details the FITMAN VF lowest sublayer that envisages the following functional
components:
the Manufacturing Assets Management Features component that is in charge of
providing services to identify, discover, tag and provide access to tangible and
intangible assets as available within, or provided by, the depicted sources of
information. More specifically this component has to provide features to syntactically
and semantically manage discovery, tagging and access to assets, as well as to
properly represents them;
the Assets & Services Repository component that is in charge to store data and
metadata about the managed assets. This component complements the previous one
in offering a uniform, consistent and dynamic access to tangible and intangible assets
required by the VF business processes;
the Marketplace Management Features component is in charge of supporting
offering and usage of application services deployed within a VF environment. This
component therefore provides services to store data and metadata, based on standards
like USDL19
or Linked-USDL20
, about available services (e.g., service registry and
directory), discover services, match demand for services (even using semantic
matching features provided by other components in this sublayer) against the
available ones, as well as support dynamic service composition;
the Semantic Analysis Features component instead is in charge of providing
specialized semantic features to properly classify tangible and intangible assets, as
well as available services (which can be considered as assets too), cluster them
according to application needs and support composition and dynamic discovery on
the basis of semantically defined attributes and constraints;
19 See the W3C USDL Incubator Group web site for more information (http://www.w3.org/2005/Incubator/usdl) 20 See the Linked-USDL web site for documentations and tools (http://www.linked-usdl.org)
Enterprise Interoperability and Collaboration Layer
Enterprise Tangible / Intangible Assets Management Layer
Legacy Systems(ERP, SCM, CRM, PLM, …)
Supply Chains
Value NetworksBusiness Ecosystems
ERP SCM
CRM
MRP
Company A
CRM
SCM
MRP
ERP
Company B
CRM
SCM MRP
ERP
Company …
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the Supply Chains & Business Ecosystems Management component, finally, provides
functionalities to support the usage of assets in collaborative production capacity
planning and team building. On the capacity planning side this component can
support, for example, discovery on unplanned production capacity and sharing of
manufacturing equipment and production facilities. On the team building side,
instead, the component can support in identifying the most suitable combination of
people having the most appropriate skills for the activity to be performed according
to the activity plan and people availability.
Fig. 3-12: The FITMAN Virtual Factory Assets Management Layer Architecture
As described in the previous section the Enterprise Tangible / Intangible Assets Management
Layer embraces components that provide a uniform set of functionalities to manage (e.g.,
discover, search, classify, combine and access) tangible and intangible assets, where assets
can be both data (e.g., business or technical documents, people profiles), as well as services.
On top of the assets management sublayer the Enterprise Interoperability and Collaboration
Layer is in charge of enhancing the lowest layer functionalities and add new ones to support
cooperative business process design and management and cross-enterprise interoperability
and collaboration. The functional components in this sublayer, depicted in Fig. 3-13, can be
shortly characterized as follows:
the Identity Management component provides the authentication services within the
cross-enterprise environment, therefore assuring that only authenticated subjects
(e.g., people, services, devices) are involved in business processes;
the Semantic Application Support Features component is in charge of providing
features to semantically manage assets (i.e., data and services as described in the
previous sections), if necessary convert their format as requested by the application
service or the business process, provide advanced syntactical and semantic search
services and manage ontologies, taxonomies and document formats;
the Collaborative BP Management Features component provides services to design
and manage business processes as requested by the cross-enterprise environments.
Enterprise Tangible / Intangible Assets Management Layer
Supply Chains
Value NetworksBusiness Ecosystems
MarketplaceManagement Features
Supply Chains & Business Ecosystems Management
SemanticAnalysis Features
Assets & Services Repository
Manufacturing AssetsManagement Features
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The managed business processes can be also semantically characterized so to achieve
the twofold objective of composing processes on the basis of semantically based
assets (i.e., both data and services) identification and integration, as well as of
semantically tagging the business processes themselves so to make them more easily
usable and reusable;
the Interoperability Services component, finally, complements the above components
in providing interoperability (e.g., dynamic and semantic data format transformation,
data and service adaptation) so that the managed assets and defined business
processes can actually be used by, and integrate, the enterprise systems (as sketched
in Fig. 3-13).
Fig. 3-13: The FITMAN Virtual Factory Interoperability & Collaboration layer Architecture
Even if the Virtual Factory Interoperability Services component has some commonality with
the Digital Factory similarly named component (see Fig. 3-9), the two have a different
objective: the Virtual Factory Interoperability Services component has the primary objective
to support interoperability among legacy systems, as well as the setup of cross-enterprise
collaborative processes, while the Digital Factory component is focused on providing a
uniform interface to data and metadata as grabbed from the different prodct data silos.
The Virtual Factory reference architecture completes the FITMAN reference architecture
description.
As stated in section 2.1 the smart, digital and virtual manufacturing domains are abstractions
that try to characterize a manufacturing environment taking into account their most relevant
aspects. An actual manufacturing environment will, of course, envisage and require a
specific mix of smart, digital and virtual features. As described in section 3.1 each
environment (and, specifically, the FITMAN trials) has to design its own architecture taking
Enterprise Interoperability and Collaboration Layer
Semantic ApplicationSupport Features
Collaborative BP Management
Features
ERP SCM
CRM
MRP
Company A
CRM
SCM
MRP
ERP
Company B
CRM
SCM MRP
ERP
Company …
IdentityManagement
Interoperability Services
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into account the three reference architectures and its specific needs combining the features
described in sections 3.2, 3.3 and 3.4.
3.5. The FITMAN Manufacturing Domains Architectures and FI-WARE GEs
3.5.1. The FITMAN Enablers
This section, and the following ones, provides an overview on how the FI-WARE GEs and
other FITMAN components fit with the reference architectures described in the previous
sections.
According to the FI-WARE Vision and Goals [46] and to the architectural approach
analyzed in the previous sections, each of FITMAN trial architecture implementations will
combine a set of elements providing specific functionalities. These elements are classified as
follows:
FI-WARE Generic Enablers (GE): that are defined by FI-WARE as offering
“reusable and commonly shared functions serving a multiplicity of Usage Areas
across various sectors”. The GEs selected by FITMAN, and their selection
rationales, are deported in the D1.3 deliverable [47];
FITMAN Specific Enablers (SE): these are components providing functionalities
that, on the one hand, are specific to an application domain (and specifically to one or
more of the three manufacturing domains), but on the other hand are quite common
in the application domain. The FITMAN SEs requirements are detailed in the D1.2
deliverable [48];
FITMAN Trial Specific Components (TSC): these are elements that are required by
a specific context (e.g., a specific FITMAN trial) and therefore cannot be reused in
other contexts.
The following three sections are therefore devoted to describe which FI-WARE GEs and
FITMAN SEs contribute to the three reference architectures.
More or less GEs in all FI-WARE chapters [49] contribute to the FITMAN reference
architectures, with the notable exception of the FI-WARE Cloud Hosting chapter. Actually
this chapter “… offers Generic Enablers that comprise the foundation for designing a
modern cloud hosting infrastructure that can be used to develop, deploy and manage Future
Internet applications and services”21
. Therefore, the GEs in the cloud chapter do not directly
provide “application functionalities”, but are there to support the dynamic deployment and
management of applications and services, which is one of the key features envisaged for the
manufacturing environment [2][3][4][5][6].
To reflect the relevance of the Cloud Hosting GEs to deploy and provide FITMAN
compliant manufacturing systems a specific section (see section 3.5.6) has been added that
highlights the currently envisaged FI-WARE cloud GEs to be used to support FITMAN
manufacturing systems.
3.5.2. The FITMAN Reference Architectures and GEs /SEs
The following sections, as stated, will review the three manufacturing architectures mapping
the functional components in them to the selected FI-WARE GEs and envisaged FITMAN
21 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/Cloud_Hosting_Architecture
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SEs. The sections will therefore both describe the identified elements, as well as graphically
propose the mappings.
The pictures in the following sections are based on the ones used in sections 3.2 - 3.4 and
envisages three additional elements (see Fig. 3-14 for the colours’ meanings):
FI-WARE GE: the identified GE22
provides all or part of the functionalities
envisaged for the FITMAN architecture functional component;
FITMAN SE: a specific functional element has been identified as able to provide
totally or partially the functionalities of the architectural components and the
FITMAN partners are able to provide it23
;
FITMAN Open Call SE: the envisaged functional element will be acquired through
the Open Call process. The call will provide details on the expected functionalities
and positioning within the specific reference architecture.
Fig. 3-14: The GEs / SEs graphical representations
3.5.3. The FITMAN Smart Factory GEs/SEs
The Fig. 3-15 sketches the envisaged GEs and SEs for the FITMAN Smart Factory
Reference Architecture. Starting from the top the identified enablers are:
SF Open Call Topic II SE (Workers, Actuators, AmI, Smart Spaces): this SE is part of
the FITMAN Open Call for Smart Factory and, specifically, is specified as the 2nd
topic of the Smart Factory section in the call. The functionalities envisaged for this
SE are to support “SF next generation, attractive human‐machine interaction
(Human‐centered Manufacturing), including devices and software components for an
advanced automation of the shopfloor efficiency and safety as well as a user‐friendly,
ergonomic and intuitive interaction between workers and machines, including data
access on the move”. As indicated it is expected that the requested SE will cover all
the functionalities envisaged for the Smart Factory Workplace Layer architectural
component;
SF Open Call Topic I SE (Dyn. CEP, Monit. & Diagnosis): also this SE is part of the
FITMAN Open Call for Smart Factory (it is the 1st topic for the Smart Factory). The
requested SE has to support “SF monitoring and diagnosis (Advanced Intelligent
Manufacturing), including dynamic and re‐configurable filtering and processing of
real world events, coming from sensor networks embedded in machinery and
22 The FI-WARE GE is normally a FI-WARE release I GE. FI-WARE Release II and III have also been tentatively
identified based on their description as available on the WI-FWARE web site 23 For example reusing, enhancing or customizing outcomes of previous projects
Legend
...…
FITMANOpen Call SE
……
FI-WARE GE
...…
FITMAN SE
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workplaces, shopfloor smart objects and tools, in‐bound logistics of tagged products
and materials, manual operations and workers wellbeing monitoring and control”.
As for the previous point it is expected that the requested SE will cover all the
functionalities envisaged by the “Dynamic” CEP & Reasoner Features architectural
component;
Config. Manag. GE: is part of the FI-WARE IoT Backend and is in charge of IoT
agents’ context management24
. This GE contributes to the provision of the
functionalities envisaged by the FITMAN Smart Factory Configuration Management
Features architectural component;
Re. II Backend Dev. Manag. GE: is also part of the FI-WARE IoT Backend system
and is in charge of the management of the kind of remote assets envisaged by the FI-
WARE IoT Backend system25
. FITMAN plans to use the FI-WARE Release II
version of this GE. Coupled with the previous GE this one completes the
functionalities envisaged for the FITMAN Configuration Management Features
architectural component. Additionally, this FI-WARE GE contributes to implement
the Device Management Sublayer architectural component as depicted in Fig. 3-15;
Re. II DB Anonym. GE: this is the FI-WARE DB Anonymizer (release II) GE26
that
covers all the functionalities envisaged for the FITMAN Security Assessment
Features architectural component;
SEI_2 Secure Events Man. SE: this is a FITMAN specific enabler that provides the
features27
envisaged by the Event Collection & Dispatching Features architectural
component. This SE is based on outcomes of the FP7 IoT@Work project28
and is
specifically designed to manage secure and scalable events collection and dispatching
for shop floor environments, as well as to assure strict access control to events and
scalability which, as argued in section 3.2, are critical features in smart factory
context;
IoT Broker GE: this GE provides a lightweight and scalable middleware component29
that helps in decoupling applications from underlying IoT devices easing their
management and translating their data into a common format and using a common
access approach. This GE will be mainly used in cooperation with the Protocol
Adapter GE to manage the device types envisaged by that GE. This GE contributes to
the provision of the features envisaged by the FITMAN Data Collection &
Adaptation Sublayer architectural component;
Protocol Adapter GE: this GE, as described in its FI-WARE specification30
, is in
particular devoted to support ZigBee devices and, therefore, contributes to the
implementation of the Protocol Adapters FITMAN architectural component
providing specific plug-ins for the GE supported devices;
SEI_1 Data Collection SE: this too is a FITMAN specific enabler31
that contributes
both to the implementation of the FITMAN Data Collection & Adaptation Sublayer
architectural component, as well as to the Protocol Adapters component. Actually
24 http://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.IoT.Backend.ConfMan 25 http://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.IoT.Backend.DeviceManagement 26 http://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Security.Optional_Security_Enablers.DBAn
onymizer 27 http://catalogue.fitman.atosresearch.eu/enablers/secure-event-management 28 https://www.iot-at-work.eu/ 29 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.IoT.Backend.IoTBroker 30 http://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.IoT.Gateway.ProtocolAdapter 31 http://catalogue.fitman.atosresearch.eu/enablers/shopfloor-data-collection
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this SE is a collection of functional elements, as described on the FITMAN
catalogue. A first set of elements deal with the management of sensor networks and
enhances the related outcomes of the GSN project32
. A second set of elements is
focused on supporting RFID technologies in the shop floor and is based on the GS1 /
EPCglobal specifications and, specifically, on the Fosstrack33
implementation of
some of the EPCglobal specifications. This FITMAN SE, in particular, enhances and
integrates the Fosstrack implementation of the EPCglobal ALE Server [50], which
contributes to the realization of the FITMAN Data Collection & Adaptation Sublayer
architectural component, and the EPCglobal Low Level Reader Protocol (LLRP) [51]
to integrate standard-compliant RFID readers therefore contributing to complete the
FITMAN Protocol Adapters architectural component.
Fig. 3-15: The FITMAN Smart Factory Reference Architecture and GEs / SEs
32 http://sourceforge.net/apps/trac/gsn/ 33 See the Fosstrack project web page for further information: https://code.google.com/p/fosstrak/
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As evident from the above description, the FI-WARE Internet of Things Services
Enablement chapter plays the role as the main chapter in the FITMAN Smart Factory
Architecture, due to the need of (near) real-time monitoring of the shop floor, device (e.g.,
sensors) management, and events collection and dispatching.
Additionally, the relevant role assigned to CEP (Complex Event Processor) engine’s enablers
will definitely allow getting an improvement in the manufacturing processes helping in
quickly (re-)adapt them or (re-)configure manufacturing machines to take into account the
actual production context and needs.
3.5.4. The FITMAN Digital Factory GEs/SEs
As for the previous chapter, Fig. 3-16 depicts the mapping between the FITMAN Digital
Factory reference architecture and the identified GEs and SEs. The following paragraphs
shortly described the identified elements:
DF Open Call Topic II SE (Product Data Visual. & 3D Rendering): this SE is part of
the FITMAN Open Call for Digital Factory and, specifically, is specified as the 2nd
topic of the Digital Factory call asking for features to support “collaborative product
data 3D visualisation (Collaborative and Mobile PLM), based on a collaborative
multi‐task project management environment and including devices and software
components for a web enabled rendering and interaction with 2D‐3D complex
manufacturing objects, e.g. CAD solids, points of clouds, large unstructured data‐sets including real‐time data repositories”. As indicated in Fig. 3-16 this SE is
expected to cover all the functionalities envisaged for the Advanced Data
Visualization & Manipulation Features architectural component;
Re. III XML 3D Web GE: this GE is a FI-WARE Release III GE providing
functionalities to create HTML based 2D and 3D interactive environments34
that can
therefore be accessible using simple web browser. This GE, which will be actually
available in FI-WARE Release III, has been inserted due to its relevance for the
Digital Factory as highlighted in sections 2.1.4and 3.3;
Application Mashup GE: this GE provides functionalities that make possible to
integrate heterogeneous data sources, UI widgets and services according to the user
defined application logic and create new applications. This GE fulfils the
functionalities envisaged for the FITMAN Application Mashup Features architectural
component;
Re. III Unstruct. Data Anal. GE: this too is a FI-WARE Release III GE35
to be soon
available to support processing of high volumes of unstructured data coming from the
Internet, therefore fulfilling the features envisaged for the FITMAN Unstructured
Data Analysis Features architectural component. This GE contributes also to provide
features envisaged by the FITMAN Product Lifecycle & Metadata Management
Sublayer (and specifically its Interoperability Services sub-component) and
Unstructured & Social Data Analysis Sublayer (specifically its Processing /Querying
Engine sub-component) FITMAN architectural components;
SEI_3 Unstructured and Social Data Analytics SE: this FITMAN SE36
, which
provides the features envisaged by the FITMAN Unstructured & Social Data
Analysis Features and, partially, by the Unstructured & Social Data Analysis
Sublayer architectural components, aims at extracting unstructured knowledge from
selected social media systems and web resources and at providing insights to user-
34 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/Materializing_Advanced_User_Interfaces_in_FI-WARE 35 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FI-
WARE_Data/Context_Management#Unstructured_data_analysis 36 http://catalogue.fitman.atosresearch.eu/enablers/unstructured-and-social-data-analytics)
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generated content. As evident from Fig. 3-16 this SE is the main element of the
FITMAN Digital Factory reference architecture for the unstructured and social data
analysis and, as reported in the SE description on the FITMAN on-line catalogue, it is
based on the integration and customization of well-known and powerful open source
components to perform such kind of analysis;
Data Pub/Sub Broker GE: this is the FI-WARE publish/subscribe enabler37
that
supports collecting data (called context information in the FI-WARE specification)
and made them available to application consumers. The rationale behind the selection
of this GE within this FITMAN manufacturing domain is in its suitability for the
FITMAN Product Lifecycle & Metadata Management Sublayer architectural
components and its integrability with the other FI-WARE GEs selected for this
architectural component;
Mediator GE: this FI-WARE GE is a functional element38
able to provide
interoperability among different communication protocols and among different data
models, as such it will support conversion of data among different formats and
acquired from different sources;
DF Open Call Topic I SE (Prod. Lifecycle & Metadata Mgmt): this SE is the main
element of the Product Lifecycle & Metadata Management Features architectural
component and is in charge to provide a uniform access to PLM data sources, as well
as to enrich these data with meta-information to help upper layers in integrating and
properly processing the mediated data. This SE is part of the FITMAN Open Call for
Digital Factory and, specifically, is specified as the 1st topic of the Digital Factory
call asking for features to support “product data and knowledge in product life cycle
(standard‐based access to PLM and product‐item data), including definition and
adoption of standard metadata systems for Product Data and Knowledge
representation, semantic interoperability transformation services from heterogeneous
systems and/or available or de‐facto standards …”.
37 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Data.PubSub 38 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Apps.Mediator
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Fig. 3-16: The FITMAN Digital Factory Reference Architecture and GEs / SEs
As evident from the above description, the main issue in the Digital Factory domain is to
have ICT systems able to support in taking more intelligent and informed decisions at the
various levels (strategic, planning, and operational). The challenge is mainly related to the
fact that information is kept in information silos and it is difficult to streamline work based
on a natural and controlled flow of information. The selection of the above GEs and SEs aim
at demonstrating how Future Internet technologies, and the FI-WARE platform in particular,
can contribute to solve, or alleviate, such situation.
The above selection of GEs/SEs provides an effective means to consolidate a view on
Product Life Cycle Information, so that more flexible and contextual access, query and
analysis can be performed on the distributed product information. Moreover, industrial
competitiveness depends not simply on the information availability but actuality on the quick
presentation of such information in the required format for effective decision making, as
envisaged by the GEs/SEs supporting the implementation of business intelligence and rich
information presentation and visualisation applications.
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The main FI-WARE chapters contributing to the Digital Factory domain are the
Applications/Services Ecosystem and Delivery Framework and the Data/Context
Management chapters.
The first one plays a key role in overcoming the closures (i.e., data silos, vertical and
difficult-to-integrate applications) that currently characterize the manufacturing domain. The
possibility to opening the applications, integrate them, transparently access data, etc. that is
envisaged by this FI-WARE chapter improves the opportunities for software companies to
access reliable data and quickly deliver new products, which is further improved by the
possibility to use different APIs to mix the data and present it in a single solution without the
user knowing the application is made out of many other services.
A critical aspect for the factories of the future is to provide an ecosystem that relies in data
for better decision making process, as supported by this FI-WARE chapter.
The Data/Context Management chapter, instead, helps in managing the amount of
information that needs to be exchanged across the factories with the involvement of different
entities, and in orchestrating the actions and transfers in order to keep the information easily
available for any data consumer service, without requiring that information consumers be
aware of the specifics of the producer such as the locations or the transfer protocol.
3.5.5. The FITMAN Virtual Factory GEs/SEs
As for the previous sections, the Fig. 3-17 sketches the envisaged GEs and SEs for the
FITMAN Virtual Factory Reference Architecture. Starting from the top, the identified
enablers are:
VF Open Call Topic II SE (Seman. Data Interop.): this SE is part of the FITMAN
Open Call for Virtual Factory and, specifically, is specified as the 2nd
topic of the
Virtual Factory section in the call. The functionalities envisaged for this SE are to
support “… semantic interoperability (Product‐Service Manufacturing Ecosystem),
including platforms and software components for dynamic, semantic data formats
transformations (e.g. unified interoperability form by means of a common model
schema), in the view to achieve ERP (and other Enterprise Systems) compatibility in
the supply chain”. This SE is therefore a key element for the provision of the
functionalities envisaged for the FITMAN Virtual Factory Interoperability Services
architectural component to support interoperability among legacy systems, and across
enterprises, and the design and deployment of cross-enterprise collaborative
processes;
Mediator GE: this is the same FI-WARE GE39
included in the Digital Factory
reference architecture (see Fig. 3-16) but with a slightly different objective. In the
Virtual Factory reference architecture, indeed, it will not be finalised to simply
provide mediation services among different data structures (and data access
mechanisms) as envisaged within the Digital Factory case, but as a key element to
support integration and interoperability among enterprise applications (e.g., ERPs,
CRMs, etc.) for cross-enterprise processes. In the Virtual Factory scenario, therefore,
the GE’s ESB (Enterprise Service Bus) and the Enterprise Integration Patterns [52]
[53] features will be fully exploited;
SEI_8 Data Interop. Platform Services SE: this FITMAN specific enabler40
completes the functionalities envisaged for the Virtual Factory Interoperability
Services architectural component. It specifically provides features for the
39 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Apps.Mediator 40 http://catalogue.fitman.atosresearch.eu/enablers/data-interoperability-platform-services/documentation
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management of Data Interoperability services (including services to support end-
users in designing and configuring them). This SE is based on outcomes of the FP7
COIN IP project41
and, specifically, it extends the COIN Integrated Platform;
Semantic App. Support GE: this FI-WARE GE42
is one of the elements providing the
services required by the FITMAN Semantic Application Support Features
architectural component and, specifically, it will provide the RDF/OWL aware
repository, ontology management features and ontology management;
Light Semantic Composition GE: this FI-WARE GE43
will provide support for
creating and managing business processing where semantics supports identification,
selection and integration of services and control elements in the business processes.
Indeed, the actual definition of a business process is normally not an easy activity,
requiring the contribution of different skills and knowledge of the available
application services (both in terms of their specific functionalities, as well as in terms
of their interfaces, supported data, etc.) This GE, therefore, aims at simplifying these
activities, and the type and number of required skills, thanks to capability to use
knowledge about application services formalized according to ad hoc ontologies (for
example giving the possibility to identify and select application services on the basis
of their provided, ontologically specified, properties, and not on more complex
service descriptions like WSDL);
SEI_6 Metadata, Ontol. Semantic Matching SE: the FITMAN Metadata and
Ontologies Semantic Matching SE44
completes the set of features envisaged for the
Virtual Factory Semantic Application Support Features architectural component
providing features to semi-automatically matching different OWL ontologies, or
XML schema definitions, addressing similar contexts of knowledge (e.g., XML
schemas for business documents defined in different standards like OASIS UBL45
or
UN/CEFACT CCL46
). This FITMAN SE provides both functionalities for nosiness
process designers to manage maps among different, even similar, ontologies or
document schemas, as well as run-time features to convert knowledge or information
from one formalization to a different one;
SEI_7 Collaboration Platf., BP Management SE: the FITMAN Collaborative
Business Process Management SE47
provides the functionalities envisaged for the
Virtual Factory Collaborative BP Management Features architectural component
and, specifically, the ones required to design, execute and monitor semantically
enhanced BPMN 2.0 business processes. This SE is actually an extension of the FI-
WARE Light Semantic Composition GE;
Identity Mgmt GE: this FI-WARE GE48
has to provide the subjects (e.g., users and
services) authentication functionalities that are critical for cross-enterprise contexts
which are at the core of the Virtual Factory domain;
Re. II Store & Registry GEs: this couple of GEs, from the FI-WARE Release II
delivery, have to jointly support the provision of the FITMAN Virtual Factory
Marketplace Management Features architectural component’s features. The FI-
41 http://www.coin-ip.eu/ 42 http://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.Data.SemanticSupport 43 https://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Apps.LightSemanticComposition 44 http://catalogue.fitman.atosresearch.eu/enablers/metadata-and-ontologies-semantic-matching/documentation 45 OASIS Universal Business Language (UBL). See https://www.oasis-open.org/committees/tc_home.php?wg_abbrev=ubl 46 UN/CEFACT) Core Components Library (CCL) http://www.unece.org/cefact/codesfortrade/unccl/ccl_index.html 47 http://catalogue.fitman.atosresearch.eu/enablers/collaborative-business-process-management/documentation 48 https://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Security.IdentityManagement
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WARE Store GE49
provides services for managing offerings and sales of services
(e.g., publication of service offerings, payments, access to purchased services, etc.).
The Registry GE50
, on the other hand, provides directory features to store information
used for the maintenance, administration, deployment and retrieval of services.
Together these two GEs provide support to manage offered and requested services
and on their availability, location, software elements, etc.;
Marketplace GE: this GE51
completes the FITMAN Virtual Factory Marketplace
Management Features architectural component providing a uniform interface to
discover offered application and services that match consumer demands so to help in
navigating through the multitude of apps and services that is envisaged on the Future
Internet;
VF Open Call Topic I SE (TA/TI Semant. Cluster.): this SE is part of the FITMAN
Open Call for Virtual Factory and, specifically, is specified as the 1st topic of the
Virtual Factory section in the call. This SE aims at covering the lack of
functionalities to support semantically based assets discovery, to extend business‐oriented service description languages (e.g., USDL and LinkedUSDL), to cluster and
generate new assets from unstructured and semi‐structured enterprise resources (e.g.,
CVs, products catalogues, etc.) and their dynamic composition;
SEI_5 Supply Chain & Business Ecos. Apps SE: this FITMAN SE52
provides features
to exploit tangible (e.g., machinery capacity) and intangible (e.g., people skills)
services allowing to combine a set of communicating gadgets and support end-users
in improving cross-enterprise r value-networks collaboration in their Production
Capacity Planning or team building activities;
Repository GE: this FI-WARE GE53
is the main provider of the storage descriptions
for services and assets. The information managed by this GE is mainly structured
using USDL and LinkedUSDL specifications so to take into account all aspects of the
managed elements (e.g., API description, business conditions, etc.);
SEI_4 Collaborative Assets Management SE: this FITMAN SE54
provides support for
the collaborative management of assets (Asset-as-a-Service - AAS). It is targeted to
the business users having no, or very low, IT expertise. The elements (i.e., assets)
managed via this SE, represent any item of economic value for an enterprise like
resources (e.g., machinery, buildings, vehicles, etc.) and capabilities (e.g.,
knowledge, competencies, relationships, etc.) that is functional to achieve the goals
of the Enterprise.
49 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.Apps.Store 50 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.Apps.Registry 51 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.Apps.Marketplace 52 http://catalogue.fitman.atosresearch.eu/enablers/supply-chain-business-ecosystem-apps/documentation 53 http://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.Apps.Repository 54 http://catalogue.fitman.atosresearch.eu/enablers/collaborative-asset-management/documentation
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Fig. 3-17: The FITMAN Virtual Factory Reference Architecture and GEs / SEs
In summary, the above briefly described Virtual Factory GEs/SEs provide features that can
be categorised as follows:
Support to enterprise interoperability and collaboration through the provision of
advanced services for setting up and execute cross-enterprise business processes.
Services that, thanks to the data and knowledge transformation features can easily
use, and reuse, the required data across the enterprise boundaries;
Support to the transparent management of enterprise tangible and intangible assets as
required to support the cross-enterprise cooperation managed via the business process
highlighted in the previous bullet.
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Due to the wide need to integrate data sources, enterprise systems (e.g., SCM, CRM, ERP,
etc.) and people the Virtual Factory reference architecture instantiations (e.g., FITMAN
Virtual Factory trials) are envisaged as requiring many Trial Specific Components (TSC) as
compared to other factory domains.
3.5.6. The FI-WARE Cloud Hosting GEs in FITMAN
As already shortly reported in section 3.5.1, although the FI-WARE Cloud Chapter does not
directly contribute “application functionalities” to, and therefore have an explicit positioning
within, the FITMAN Reference Architecture, nevertheless it plays a significant role in
meeting requirements of flexibility, dynamic deployment and management of applications
and services as envisaged for the near manufacturing future environments [2][3][4][5][6].
In the following we report the rationale behind the selection of the FI-WARE Cloud Chapter
GEs, as well as the expected role they will play in the deployment of FITMAN compliant
manufacturing solutions.
As highlighted in section 2.1, there are contrasting requirements affecting the deployment of
cloud computing based solutions in manufacturing. Indeed, on the one hand, there is the need
to deploy solutions able to scale, be provided on-demand, support cross-enterprises contexts,
etc.; on the other hand, there is the need of assuring manufacturing solutions provide
information protection, liability, time constraints, etc.. The former set of needs of course
plays in favour of cloud based deployments, while the latter raises some concerns on the
usage of currently available cloud computing public services (e.g., Amazon AWS, Microsoft
Azure). In the near future we expect to have cloud and connectivity services that provides
SLAs and contractual terms that meet the manufacturing constraints and, therefore, an
increasing usage of public or community cloud services [54].
To overcome the above issues, most of the FITMAN trials that plan to deploy their FITMAN
compliant manufacturing systems on a cloud platform will actually use on premises cloud
infrastructures. This by no means affects the value of the FITMAN FI-WARE GEs cloud
evaluation; on the contrary this approach can help both in fulfilling the constraints mentioned
above, as well as in assessing in real contexts the cloud technologies, therefore fostering
manufacturers awareness about cloud services and their more conscious evaluation of third
parties contracts and SLAs for cloud services.
The selected FI-WARE Cloud Chapter GEs have the objective to provide specialised, added
value services as compared to the IaaS services cloud platforms like OpenStack55
, which is
the foundation of the FI-WARE cloud computing infrastructure, provide.
The selected GEs are the following:
Cloud.DCRM - IaaS Data Center Resource Management GE: The DCRM GE56
is
one of the most fundamental added value elements of the FI-WARE cloud computing
facilities being devoted to improve the management of the Virtual Machines (VMs),
and their resources, lifecycle. This DCRM GE extends the OpenStack baseline
functionalities;
Cloud.SM - IaaS Service Management: the IaaS SM GE57
is a key enabler for the
lifecycle management of virtual infrastructures required by applications, for example
scaling vertically or horizontally the virtual servers allocated to an application
according to a pre-defined set of rules. The flexibility provided by the IaaS SM GE
enhance the usability and flexibility of FI-WARE compliant platforms, improving the
usage of resources, reducing deployment/reconfiguration time, automating the
55 http://www.openstack.org 56 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Cloud.DCRM 57 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.ArchitectureDescription.Cloud.SM
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management of failure tasks and supporting the integration of public and private
cloud infrastructures;
Cloud.ObjectStorage - Object Storage: the CDMI GE58
exposes a CDMI59
RESTful
API to manage object storage (e.g., binary or textual objects, hierarchical containers,
etc.) therefore supporting both infrastructure GEs and applications to organize and
manage their persistent data;
Cloud.SelfServiceInterfaces - Cloud Portal: this GE60
enables end-users and platform
administrators to manage their services and resources. This GE offers both a
graphical dashboard, accessible via a web portal that is part of the GE, as well as a
command line interface through which users can manage and supervise their services
and reosurces deployed on the cloud infrastructure.
As evident from the above paragraphs the FITMAN selection of FI-WARE Cloud Chapter’s
GEs is focused on enablers that can easy the on premise deployment and management of
cloud based solutions, as well as on FI-PPP provided infrastructures.
One of the expected benefits of the usage of the Cloud Chapter GEs in the FITMNA trials is
to gain actual experience on the performances, usability and suitability of cloud solutions in
manufacturing so to foster the deployment of cloud based solutions.
58 https://forge.fi-ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Cloud.ObjectStorage 59 http://www.snia.org/cdmi 60 https://forge.fi-
ware.eu/plugins/mediawiki/wiki/fiware/index.php/FIWARE.OpenSpecification.Cloud.SelfServiceInterfaces
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4. CONCLUSIONS AND NEXT STEPS
The previous sections have tried to characterize the evolution of the manufacturing sector
from highlighting the main envisaged challenges (see section 2.1.1) and issues (see section
2.1.2). Afterwards we tried to better characterize different manufacturing domains (i.e., the
Smart, Digital and Virtual Factory ones) as envisaged by the EFFRA organization [5], and
we provided a quick summary of the FITMAN trials so to better characterize the specific
contexts the FITMAN architecture has to address.
Sections 3.1-3.4 provide the rationale behind the choice to define reference architectures for
the three manufacturing domains and a detailed description of each of reference architecture.
Finally, section 3.5 analyzes how the selected FI-WARE GEs and FITMAN SEs contribute
to, and position within, the three reference architectures.
The FITMAN plan does not envisage new versions of this deliverable, being the rationale
behind the design of the three reference architectures well founded and in line with the
manufactured trends as reported in section 2.1. Therefore, even if the selection of FI-WARE
GEs could be revised, or the FITMAN SEs could be refined, the overall design will
hopefully not be affected. Changes in GEs selection or SEs specifications will be addressed
and reported in other FITMAN deliverables.
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[46] See the “Overall FI-WARE Vision” document (http://forge.fi-
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[47] FITMAN Consortium, “D1.3 - FI-WARE Generic Enablers Final Selection for
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[49] See the “FI-WARE Architecture” document (http://forge.fi-
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[50] EPCglobal Inc., “The Application Level Events (ALE) Specification, Version 1.1
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