Annals of the CIRP Vol. 56/1/2007 -439- doi:10.1016/j.cirp.2007.05.105

High Resolution Production Management

G. Schuh(2)1, S. Gottschalk1, T. Höhne1

1Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Aachen, Germany

Abstract High Resolution Production Management describes the approach to set up a network of sensors for online order identification and localisation in production consisting of new and existing information technologies such as Radio Frequency Identification (RFID), Programmable Logic Controllers (PLC) and Personal Digital Assistants (PDA). It is intended to establish a new order optimisation principle between the interlaced planning levels, which allows an improved real-time decision making. Finally, a software architecture is proposed which allows for a consistent interaction of the heterogeneous planning and control systems. The paper introduces the approach and first concepts of High Resolution Production Management and presents first experiences of application to industrial cases.

Keywords:Planning, Scheduling, Open Architecture

1 INTRODUCTION Today's dilemma of production planning and control is to achieve high process efficiency, low throughput times and good planning confidence in spite of a turbulent environment with short product-lifecycles, an increasing variety and a growing individualisation of demands [1]. Most companies have reacted by increasing internal flexibility and accelerating business processes. One common approach is to reduce inventory and work in progress to minimise queuing times. Due to the continuous reduction of safety buffers, both in terms of material stocks and throughput time, processes have become strongly coupled. As a result, any deviation from plan strikes through to subsequent process steps and causes continuous noise and oscillatory instabilities. Consequently, the fulfilment of planned production schedules becomes more difficult in such environments and process transparency as basis for correct reactions to deviations is crucial. To overcome the arising lack of overview, more and more IT-tools are put into operation: Supply Chain Management (SCM) [2], Enterprise Resource Planning (ERP) and Manufacturing Execution Systems (MES) [3] are examples of the various means to keep the growing complexity under control. In particular, the growing penetration of Advanced Planning and Scheduling systems (APS) shows that many companies see a necessity to improve their capability of mastering high dynamics in processes and demand. The basic idea of these systems is to use real-time feedback from production to continuously adapt the production schedule to any kind of turbulence [4]. Within the following paragraphs, the deficits of established methods of production planning and control shall be discussed and a new perspective on real-time production planning and control, named "High Resolution Production Management" is presented.

2 CHALLENGES IN PLANNING AND CONTROL Quality and performance of production can be achieved either by highly stable and repeatable processes or by the capability of reacting to deviations in coherence to overall performance targets. Planning and control activities are in

their quintessence optimisation problems of matching multiple order fulfilment with limited resource capacities [5] [6]. Therefore, in the following Planning Consistency and IT Integrity are described besides Real-time Ability [7] as today's main challenges for production planning and control.

2.1 Real-time Ability A real-time system is one that responds to a signal, event or request fast enough to satisfy a specific requirement. The Nyquist-Shannon sampling theorem constitutes a master guideline. It states that exact reconstruction of a continuous-time baseband signal from its samples is possible if the sampling frequency is greater than twice the bandwidth [8]. Real-time ability in production includes the continuous acquisition of checkback signals from all stages in production and the purposeful and selective provision of planning information to the execution level. According to the Nyquist-Shannon sampling theorem, a maximisation of the level of resolution, both in detail as well as in promptness of information can not be the goal. In contrast, the appropriate level of resolution is to be adjusted depending on the specific use case.

2.2 Planning Consistency The fundamental problem of planning and control is the optimisation of order fulfilment in spite of limited resource capacities. A dynamic, real-time process management needs continuous rescheduling to handle deviations from plan. The established planning and control methods are based on the Manufacturing Resource Planning principle [9]. Often, simple rules and restrictions, such as singular bottlenecks, are applied, but a capacity planning and optimisation of multiple resource utilisations is not done during scheduling. Typically, resource conflicts are solved separately afterwards, either by mathematical optimisation in an APS system or manually on the shop floor (Figure 1). Optimisation tries to achieve a fulfilment of the scheduled material requirements while assuring good resource utilisation at the same time. Continuously acquired checkback signals on order progress can be used to frequently reschedule the same set of orders.

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Order scheduling based on standard times

Optimisation of resource assignment

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Figure 1: Established planning logic In an adequately stable environment, a good planning result can be achieved by this method within little iteration. But with growing dynamics and frequent rescheduling, a logic deficit becomes obvious: Planning is unable to anticipate all restrictions of the execution level. But due to the omnipresent need to maximise utilisation, planning claims the ability to prescribe the realisation of production in increasing detail. It uses idealised models to puzzle out activity scenarios and postulates their exact reproduction in execution. However, reality’s fuzziness guarantees the sensitiveness of the whole order microstructure and causes instabilities. With tight activity plans to be adhered to at every workstation, there is no space for compensation and deviations strike through to the whole process chain.

2.3 IT Integrity The structural deficit of established planning and control approaches lies in the way IT-systems and functions are coupled to one another. At the core this is a problem of the mathematical complexity of optimisation problems as well as of the evolution of IT-tools in practice. Problem complexity means that with inevitably restricted modelling and planning resources, there is always a balancing between model depth and model breadth [10]. Integrated planning models (e.g. Computer Integrated Manufacturing, introduced in the Eighties) and their efforts to utilise holistic optimisers, which search for total optimums by means of simultaneous planning, typically fail, since they disregard this balancing dilemma: with the planning breadth being extended to a maximum, the planning depth suffers. Therefore, the well proven approach is to delegate various planning functions to different planning entities, which are represented in modelling details specified to their planning functions’ needs. By decomposing the planning levels gradually, the balancing of depth and breadth can be solved very individually. The resulting interlaced and multilevel planning process suits the common hierarchy of corporate decision processes, typically structured as strategic, tactical and operational [11].The practical challenge is that IT-landscapes typically evolve over time and are usually highly heterogeneous and individual. While lossless decomposition (top-down) is feasible in theory, conventional planning aggregation (bottom-up) still results in information filtering and loss. The resulting requirement is to develop an IT-architecture

which enables flexible coupling, interconnection and substitution of production planning modules of arbitrary planning details. It must centre the production process and preserve logically complete order progress information. This way, an information detail achieved once remains available to all subsequent processes.

3 HIGH RESOLUTION PRODUCTION MANAGEMENT High Resolution Production Management describes the approach of managing production processes on a real-time basis. In Figure 2 the main elements of the proposed approach are contrasted with the solutions currently established in industrial practice.Sufficient information availability and the capability to communicate planning decisions rapidly are fundamental prerequisites for a real-time optimisation of production schedules. For this, the resolution of information and planning detail must be set to an appropriate level instead of mere maximisation. The required communication capability must be facilitated by a Sensor Actor Network. The second element of the approach is a planning logic supporting a real-time order management. Here, the main challenge is to give advice for action to different planning hierarchies. In particular, this includes giving prognoses to subsequent process steps so that they can adapt their planning accordingly. As third element of the approach, an architecture for IT-systems is necessary, which allows a hierarchic and decentralised composition of functionalities.

3.1 Sensor Actor Network To enable real-time process information, a low-level Sensor Actor Network must be established. To provide feedback-control information to super-ordinate or subsequent planning levels as a basis for real-time decisions, Personal Digital Assistants (PDA) can be propagated onto the shop-floor. The challenge is to develop on-demand information processes which ensure people being informed at all times without detaining them from value creation. Therefore, the specific use-cases must be analysed for each participating role individually, and a dynamic front-end concept must be developed to exchange information obstacle-free. While the low-level information layer provides versatile enriched real-time information, an information management concept must be developed for on-demand information supply, filtering out any status messages not relevant at present, and focusing alerts with relevant impact to the individual planning and execution situation. A third building block is to intensify the use of auto-identification technologies. They must be deployed for automated localisation and result in process progress notifications without human interaction. In addition to well-established barcode readers, Radio Frequency Identification (RFID) has matured in the last years. Furthermore, 2D-barcode or image recognition are more enablers for automated real-time data capture of the future.

Currently followedApproachChallenges

High ResolutionApproach

Maximised resolutionReal-time Ability Appropriate resolution Sensor Actor Network

Best possible fulfilment of given orders with fix resources

Planning Consistency Planning values degrees of free-dom and sets boundaries

High Resolution Order Management

Simultaneous planning and control

IT Integrity Hierarchic, decentralised planning and control

Service Oriented Architecture

Solution

Figure 2: High Resolution Production Management

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3.2 High Resolution Order Management The optimisation logic strived for in High Resolution Order Management does not focus the allocation of resources to processes, neither the allocation of orders to resources. In contrast, it is based on the acknowledgement that the main challenge is to allocate the available excessive time (slack) among the particular process steps, so that they obtain degrees of freedom to self-optimise according to their local goals. So, order assignments comprise specific boundaries for scheduling etc. plus unambiguous structures of objectives which functions as guidelines for decentralised self-optimisation (Figure 3).

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Figure 3: High Resolution Order Management The result are two decoupled levels of optimisation exercises. On the superordinate planning level, the optimisation focus is the allocation of the available degrees of freedom across the process chain. On the subordinate control level, the challenge is to exploit the degrees of freedom while optimising execution according to individually assigned objectives. In the course of process progress, predecessors commit to alternative procedures, and by this make predefinitions which have great influence on successor processes by limiting sucessors’ original degrees of freedom before they even get to execution. At the same time, those successors process other orders and by this fix arrangements with influence on other orders’ degrees of freedom.Hence, important for the design of the optimisation logic of High Resolution Order Management is the following: A fundamental requirement during execution is the

predecessors’ projection of progression and the prenotification of all successors.

With prompt feedback, those successors can anticipate their predecessors’ revocation of original degrees of freedom within their own control, and update their own plans to any changed situation in real-time, even before the orders physically arrive.

Optimisation is not designed as simultaneous planning approach but leaves freedom for detailed optimisation at lower planning hierarchies.

The fundamental challenge of optimisation lies in the allocation of the degrees of freedom across the process chain. Analogies like takt decline in flow-line balancing are promising starting points in this context.

A promising approach is the integration of the human being in the optimisation process, due to the ability of mastering complex decisions using implicit context knowledge. Complementary, the adjustment of the appropriate level of information resolution to the use-case specific real-time definition is fundamental.

3.3 Service Oriented Architecture Figure 4 shows the basic IT architecture developed for High Resolution Production Management. The Order Manager covers the functionality of material and resource requirements planning and the administration of master data is located here. The scheduling of orders is done by the Process Manager which is realised within a Service Oriented Architecture (SOA). The SOA concept allows the required modularisation of functionalities to deal with their planning complexity and the heterogeneity of IT-tools. The constitutive principle of SOA is the unification of data interchange among functional modules using standardised messages and common technologies (typically web-based) [12]. Subordinate resource optimisation functions and the information layer of the Sensor Actor Network are connected to the Process Manager as services. The Process Manager functions as a super ordinate control authority. While sub-functions can be delegated to subordinate services, the master algorithm (business logic) and scheduling decisions are located here and govern all attached services.

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Figure 4: High Resolution IT Architecture 4 FIRST APPLICATIONS IN INDUSTRY CASES In order to illustrate the practical relevance and potentials of High Resolution Production Management, industry cases at Deckel Maho Pfronten GmbH (machine tools) and Koenig & Bauer AG (printing technology) are examined and analysed in detail. The business processes focus assembly and reach from internal logistics over pre-assembly to final assembly. The goal is an advanced synchronisation of the assembly progress and the required material provision, while real-time planning and communication facilitates reactive adaptations of assembly operations to improve continuous assembling. RFID tagged carriers are located at various reading points along the in-house provision process (e.g. stock picking, truck loading, factory workshop entering, delivery), so that the addressees in assembly can keep track of their ordered materials (sensor network). Expected arrival dates and plan variances are presented on personalised assembly PDAs, which are also used to trigger supply (actor network). At the same time, the RFID sensor network is used as an automated completion confirmation system, as the return

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of unloaded carriers is interpreted as the completion of the corresponding assembly step. In order to enable easy integration of the planning procedures into the existing IT-structure, a SOA is introduces, using XML-messages which are based on standardised data sets (e.g. bills of materials, resources, work plans, processes, orders). Coordination among downstream assembly processes is structured by using a PDA solution which minimises information presentation to a circumstance-specific minimum and replaces insufficient verbal arrangements by dependable agreements. Successors (e.g. final assembly) narrow down the expected requirement definitions as they proceed in assembly, so that their predecessors (e.g. sub-assembly) are able to adapt their order priorities accordingly. In return, predecessors project their expected finish dates of sub-assemblies, always trying to stick to the centrally agreed time-frames. By receiving continuously approved time-frames or prenotifications of plan violations, the successor can adapt the own plans to changing preconditions by way of precaution.With full transparency of material availability and arrival at every assembly step, local optimisations of operations and adaptations of plans become feasible. By keeping detailed tasks like assembly sequence optimisation on low decision levels, the high-level Order Manager can focus the most far-reaching problems. By avoiding uninformed dependence on provision variation, the formerly common fluctuation of assembly personnel efficiency between 70% and 125% efficiency factory was harmonised to approximately 115%. Considering that in some cases, 70% break-in’s had occurred every other day, the benefits are substantial both in personnel utilisation and lead time reduction.

5 CONCLUSION High Resolution Production Management introduces a new perspective on real-time production planning and control. The approach consists of three components. A Sensor Actor Network provides real-time ability for the communication between planning and execution. Communication consists of checkback signals on order progress and provision of planning information to subsequent process steps. Real-time ability is understood as the appropriate level of information resolution necessary for control of deviations in a specific case of application. High Resolution Order Management provides the basis for real-time decision making. While currently applied methods focus on the optimisation of resource allocation, the proposed approach is to optimise the allocation of degrees of freedom along the process chain. In this logic, degrees of freedom provide space for subordinate optimisation according to individual structures of objectives while superordinate time-frames remain robust at the same time. As third component of the approach, a Service Oriented Architecture is proposed. Hereby, it is possible to distribute planning functionalities and to meet the necessity of heterogeneous IT-tools for planning and control. First applications in industrial case-studies have verified the relevance and potential of the addressed issues. While to a large extent, the individual components of the solutions are known from various disciplines, their combination discloses a number of unsolved questions which are being investigated in ongoing research.

6 ACKNOWLEDGEMENT The new approach of High Resolution Production Management is being investigated by the Laboratory of Machine Tools and Production Engineering (WZL) within several publicly funded research and development projects: “Smart Logistics” (Federal Ministry of Economics and Technology, BMWi) [13], “Adaptive Logistik” [14] and “my Open Factory” [15] (both Federal Ministry of Education and Research, BMBF) as well as the Cluster of Excellence “Integrative Production Technology for High Wage Countries” (German Research Foundation, DFG).

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