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Computers in Industry 56 (2005) 125–140
Knowledge web-based system architecture for collaborative
product development
Karina Rodriguez, Ahmed Al-Ashaab*
School of Engineering and Built Environment, University of Wolverhampton, Wulfruna Street, Wolverhampton WV11SB, UK
Received 22 April 2003; accepted 5 July 2004
Available online 1 October 2004
Abstract
The manufacturing competitive environment has intensified in recent years. In this environment, companies do not possess
all the knowledge they need but instead rely on other organizations. This results in the need of distance product development,
which in turn requires information and knowledge in the place, time and format required. In response to this need the research
community has come with a solution called collaborative product development (CPD) systems. This paper introduces the partial
results of the ongoing research to propose a knowledge driven CPD system architecture, which will facilitate the provision of
knowledge involved in product development. This paper presents the research issues and industrial requirements for such
system. Furthermore, the proposed system architecture is described in detail and its implementation is presented using a case
study of an injection moulded product.
# 2004 Elsevier B.V. All rights reserved.
Keywords: Collaborative product development; Manufacturing model; Injection moulding process information; Knowledge web-based
engineering
1. Introduction
The manufacturing competitive environment has
intensified dramatically and expanded globally in
recent years. This trend has been principally driven by
world open market and growing customer expecta-
tions for products delivered quickly and at competitive
prices. In this global environment, organizations do
* Corresponding author. Tel.: +44 1902 32 22 76;
fax: +44 1902 32 27 43.
E-mail address: [email protected] (A. Al-Ashaab).
0166-3615/$ – see front matter # 2004 Elsevier B.V. All rights reserved
doi:10.1016/j.compind.2004.07.004
not possess all the knowledge they need but instead
rely on buying technologies or services through
contractual and cooperative partnerships with other
organizations [1]. The use of this approach results in
the need of distance product development, which in
turn requires the provision of product life cycle
information and knowledge in the place, time and
format required. In response to this need the research
community has come with a solution called colla-
borative product development (CPD) system, which is
defined as: ‘‘an Internet based computational archi-
tecture that supports the sharing and transferring of
.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140126
knowledge and information of the product life cycle
amongst geographically distributed companies to aid
taking right engineering decisions in a collaborative
environment’’ [2].
Among the existent technologies to support
collaborative product development, the focus has
been in sharing product data and providing colla-
borative tools to bring the multidisciplinary team
together. However, there is still the need to capture and
share the know-how of the geographically distributed
partners. The knowledge involved in this research is
related to the technological constraints that affect the
decisions taken when developing a product. For
example, manufacturing process and resources con-
straints that must be considered for the development of
injection moulded plastic products.
This paper presents a knowledge driven collabora-
tive product development (KdCPD) system architec-
ture that addresses the requirements, as defined by
both the research and industrial communities. Section
2 describes the methodological approach used in the
research. Sections 3 and 4 show the research issues
and industrial requirements of the collaborative
product development. The mentioned industrial
requirements have emerged from an industrial survey
conducted in three injection moulding companies.
Section 5 describes in detail the proposed system
architecture and its elements. Section 6 presents its
implementation using a plastic injection moulded part
as a case study. Conclusions are presented, finally, in
the last section.
2. The research methodology
The research approach that has been adopted in this
work is illustrated in Fig. 1. The different activities of
the research were conducted as follows:
a. A
n extensive literature survey was performed inorder to identify the characteristics of the systems
that support collaborative product development
(see Fig. 1a). The analysis helped to pinpoint
several technological requirements.
b. P
arallel to this, the industrial requirements wereidentified by performing a survey in three injection
moulding companies within the UK (see Fig. 1b).
The results were mapped with the previously
identified research issues and a list of requirements
for a CPD system was produced.
c. A
s Fig. 1c shows, CIMOSA [3] was chosen asreference architecture because it is considered to be
clear and flexible to model the activities, informa-
tion, knowledge, locations and organisation point
of views in order to support collaborative product
development. The formal modelling techniques,
such as IDEF0 for activity modelling and UML for
information modelling, were used to represent and
describe the above point of views.
d. T
he activities and knowledge were modelled usingthe information acquired from the injection
moulding companies approached during the
industrial survey and from the literature review
(see Fig. 1d).
e. A
KdCPD system architecture that addresses theresearch issues was developed. The architecture is
presented in detail in this paper.
f. F
inally, a prototype of the proposed KdCPD systemis being implemented and some of the results are
presented.
The next section will describe in more detail the
literature survey undertaken to identify the character-
istics of CPD systems.
3. Technological requirements of CPD systems
A number of research initiatives related to Internet
based collaborative product development systems
have been undertaken by several authors. The
literature review has highlighted several technological
requirements that must be addressed in order to
develop enabling technologies for this type of systems.
These are:
1. I
nformation system architecture: information mod-els and engineering applications are integrated
within a framework in a structured and transparent
manner using communication protocols between
the elements of the system [4].
2. C
ommunication tools: tools to enable the visual/audio communication amongst geographically
distributed team members.
3. V
irtual team management tools: to coordinate thedistributed team members.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 127
Fig. 1. Methodology to develop an Internet based architecture to support collaborative product development.
4. P
roduct model: a software representation of formand data that describe a product throughout its life
cycle [5].
5. E
ngineering applications: software to support thecorrect engineering decision making throughout
product development.
6. P
roduct geometric representation: software appli-cation that facilitates the visualization of product
design among the geographically distributed team
members.
7. I
ntegration with CAD/CAM/CAE commercialsoftware: interface applications to import/export
files from commercial CAD/CAM/CAE systems.
8. K
nowledge representation: the documentation oflearning lessons and other generic rules, which are
stored in a repository of information.
9. P
roject management tools: to coordinate productdevelopment activities.
Table 1 exhibits the reviewed CPD systems
illustrating the technological requirements they sup-
port. The following present in more detail the four key
technological requirements that the authors believe are
needed in any CPD system. These are communication
tools, engineering applications, product model and
knowledge representation.
3.1. Communication tools
In order to support communication between distri-
buted team members the reviewed systems provide
synchronous and asynchronous collaborative tools.
Synchronous tools are used for real time communica-
tions, such as video/audio conferencing, whiteboard,
chat sessions and sharing geometric models to provide
a virtual meeting environment. Asynchronous tools are
used in non-real time communications, i.e., email or
file downloading from a database.
3.2. Engineering applications
Effective collaborative product development could
be achieved by using engineering applications that
support the correct engineering decision making.
These are the applications that need to be performed
collaboratively.
K.
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28Table 1
Features of a collaborative product development system included in the reviewed systems
CPD systems Technological requirements
Information
system
architecture
Communication
tools
Virtual
team
management
Product
model
Engineering
applications
Product
geometric
representation
Integration
with CAD/
CAM/CAE
software
Knowledge
representation
Project
management
DOME by Abrahamson et al. [6] * *
DISCS by Anderson and
Abdalla [7]
* * Conceptual design * *
Biennier and Favrel [8] * Conceptual design
WebCADET by Rodgers
et al. [26]
* Conceptual design *
Chang et al. [18] * Whiteboard,
visualize geom.
* Conceptual design,
design for X, manuf.
process planning
* *
Chung and Kunwoo [9] * Conceptual design *
SOMF by Domazet et al. [10] * * * Conceptual design * *
CODES by Gupta et al. [11] * * * Conceptual design,
engineering analysis,
manuf. process planning
* *
Design for X by Shi et al. [27] * * Conceptual design,
design for X, manuf.
process planning
*
NetFEATURE by Jae et al. [25] * * Conceptual design *
CyberView by Kim et al. [19] Visualize geom. * Conceptual design * *
EDSE by Li et al. [12] Conceptual design *
STARS by Lu and Cai [13] * * Conceptual design *
WPDSS by Qiang et al. [22] * Conceptual design * *
Qin et al. [14] Conceptual design * *
Enterprise-Web by Rezayat [15] * Whiteboard * Conceptual design *
Roy et al. [20] Videoconference * Conceptual design,
design for X, eng. analysis,
prototyping, manuf.
process planning
* * *
Collab. Studio by Sevy et al. [21] * Audioconference,
whiteboard
Conceptual design * *
Su D. et al. [23] * Audioconference,
whiteboard,
visualize geom.
* Conceptual design,
manuf. process planning
* *
DCEE by Torlind [16] Videoconference,
visualize geom.
Conceptual design * *
CyberEye by Zhuang et al. [17] * Visualize geom. * Conceptual design *
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 129
Fig. 2. Different approaches to support collaboration during design.
Table 1 illustrates different engineering applica-
tions provided by the reviewed systems. As shown in
the table, most of the effort has been directed to
support the design activity. This activity involves
collaboration and, therefore, extensive communica-
tion is required among the team members in order to
create, analyse and evaluate design alternatives. The
following three approaches have been supported by
the researchers:
a. C
ommon access of design data: the collaboration isachieved by sharing product data [6–17]. There is
no real time visualization of the geometry. The
data, mainly design data, is downloaded from an
information system (see Fig. 2a).
b. C
ollaborative visualization of the component: asshown in Fig. 2b, this approach allows the
engineers to convert the solid model previously
designed into a 3D virtual geometric model. Such a
model can be visualized in real time, but not
modified, over the Internet [16–21].
c. C
ollaborative design of the component: thisapproach allows the geographically distributed
designers to visualize and modify the product
geometric model in real time (Fig. 2c). Qiang et al.
[22] and Su et al. [23] propose a system where the
designers work together with the same solid model
in a commercial CAD system. Other commercially
available initiatives, known as collaborative pro-
duct commerce systems, use a similar approach,
e.g. [24].
3.3. Product model
The product data is used and produced by different
engineering applications throughout the product deve-
lopment process. The data is usually stored in what is
called a product model. The structure of any product
model is related to the engineering application that it
supports. As presented in the previous section, most of
the reviewed CPD systems are concerned with the
design activity. Therefore, most of the product models
have been structured to capture product design data,
mainly geometric data and BOM, using the following
form:
� B
ased on ISO standard STEP 10303 AP-203[7,10,16,19].
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140130
� B
ased on non-standard structure and implementedwith commercial databases, Chang et al. [18], Jae et
al. [25], Gupta et al. [11], Qin et al. [14] and Roy et
al. [20] developed their own models to represent the
product design data and manufacturing data. The
information captured includes component features
[18,25,20], geometric data [18,11,20] and machine
tools [20].
3.4. Knowledge representation
In order to have an accurate and faster decision
making support with some level of automation,
knowledge related to product development should
be captured. There are different opinions regarding the
definition of this knowledge. The authors have
classified the knowledge in the following types:
1. P
roduct data: such as product specifications, CADfile, design analysis and market studies. This type
of knowledge has the disadvantage that the data
still needs to be analysed and applied to the specific
problem.
2. P
revious cases history: the data about past projectsand the rationale about how decisions were taken is
also considered useful to take decisions during
current projects [12,21]. This approach is time
consuming because the relevant information needs
to be found, understood and applied.
3. P
roduct life cycle constraints: the decisions takenduring the development of a product may be
limited by technological, processes, resources,
material or other considerations. For example, to
design an injection moulded component there are
certain characteristics of the process that need to be
considered, such as the capability of only produ-
cing thin walled products. This knowledge is
available most of the time from the experience of
the engineers, in books or other documents.
Research effort [18,20,26,27] has been made to
capture design and manufacturing rules in the form of
ontologies or artificial intelligent rules to support is-
olated applications. However, the proposed systems do
not provide the capability to share these rules in real
time or through direct interaction with the engineering
applications. One of the approaches adopted is to store
the constraints in a database and provide a search
engine.
4. Industrial study of collaborative product
development
After analysing the technological requirements for
a CPD system, an industrial survey was conducted
amongst engineers of three manufacturing companies.
In this particular research, the companies selected are
involved in some aspects of plastic injection mould-
ing, such as product design, mould design and
fabrication, as well as the processing of the plastic
parts. This is because the engineering application of
the presented CPD system is injection moulding.
The survey was conducted by means of a
questionnaire, which was designed based on the
information collected during the literature review. The
objective was to understand the industrial need of
collaborative product development, in addition to the
following specific objectives:
� I
nvestigate whether there is an industrial need tocollaborate with the customer, supply chain and
other partners.
� U
nderstand the current mechanism of communica-tion between the companies and their supply chain
when such collaboration exists.
� I
nvestigate the best mechanisms to achieve effectivecollaboration according to the industrial needs.
4.1. Results of the industrial survey
One of the main findings is that the distance
collaboration amongst the companies of the supply
chain is crucial due to the globalisation of the market
and their involvement in international manufacturing
alliances. Such results are illustrated in Fig. 3a, where
100% of the interviewed engineers considered the
collaboration either important or crucial in the current
product development practice.
To achieve an effective collaboration it is required
to use real time distance communication tools, as
previously explained. Fig. 3c shows the results of the
currently used tools and those that are desired to
support distance collaboration with other partners. It is
evident that the Internet communication tools are
favoured, especially email, sharing of product
information and geometric data. The required product
information in a typical collaborative activity is
illustrated in Fig. 3b. Specification data, parts and
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 131
Fig
.3.
Fin
di n
gs
of
the
indust
rial
surv
ey.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140132
component information, geometry data, bill of
materials, test data and design information are
examples of such product information.
4.1.1. Mapping of technological requirements and
industrial findings.
The industrial survey identified several requirements
that were mapped with those of the literature survey.
From this mapping a set of requirements for a CPD
system was deduced:
� T
he engineers considered that it is crucial to haveeffective collaboration with their geographically
distributed partners. Hence, an Internet based
computer system is imperative. Such a system
requires an architecture, which is distributed,
interoperable, secure and modular.
� A
major requirement that has not been addressed byany research group is the capturing of knowledge
and its delivery in real time to support engineering
decision making. This knowledge should be
captured in manufacturing constraints, such as
process, material and resources capabilities.
� T
he industry needs a CPD system that supports thecomplete product life cycle. Hence, the need to
capture and share product information could be
addressed by having a product model. Such a model
must capture and provide all product life cycle data
(i.e. product engineering data, manufacturing and
tooling and testing data) in real time.
� T
he current CPD systems are mainly focused insupporting the design application while the indus-
trial survey highlights the need for other key
applications that should be performed in distance.
As such, future CPD systems must support a range
of engineering applications. For example, design
for manufacturing and selection of production
equipment.
� T
he provision of communication tools has beenwell addressed in the current research. However,
two main points should be emphasised in future
generations of CPD systems. First, the distributed
team should share geometry in such a way that it
could be modified in real time; and second,
geometric data should be integrated with the
decision support engineering applications.
� P
roject management applications are required tocoordinate the virtual team and their tasks. This
issue has not been emphasised in the current CPD
systems.
To develop a CPD system with all the above
characteristics, it is necessary to have enabling
technologies. In this research, these technologies
were selected according to CIMOSA (Open System
Architecture for Computer Integrated Manufacturing),
which was selected as the reference system archi-
tecture. The proposed architecture is described in the
following section.
5. Proposed knowledge driven CPD systemarchitecture
An Internet based system architecture is proposed
in this paper to support collaborative product
development, while its application is presented in
Section 6. As shown in Fig. 4, the architecture is
structured in a three-layered framework: information,
application and end user layer. In such a system, the
end user layer is situated in the user’s desktop and is
connected to the application Web server (application
layer), which in turn is connected to the information
databases (information layer). The following sections
will describe each of the layers in more detail.
5.1. Information layer of KdCPD system
architecture
5.1.1. Product model
In order to support the whole product life cycle, as
required by industry, the product data should be
structured in a product model, which in this research is
based in a feature-based approach [28]. This approach
facilitates the integration with the manufacturing
knowledge and supports a range of engineering
applications. The product data is provided in real
time, and it captures the development progress.
Product data is also visualized through 3D virtual
product geometry as shown in Fig. 6.
5.1.2. Manufacturing knowledge model
Decision making during product development is
difficult as decisions need to be taken in collabora-
tion with other companies that do not have access to
the knowledge of their distributed partners. To
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 133
Fig. 4. Knowledge collaborative product development system architecture.
overcome this issue, it is necessary to have a
distributed source of knowledge to support the
different activities. The manufacturing knowledge
model [29] addresses such industrial requirement
because it is an information model that captures
process and resources capabilities. Its manufacturing
data integrity is captured as a result of the way the
model represents the manufacturing constraints
imposed on the product data definition.
The manufacturing knowledge model is the source
of information required to support the decision making
during the engineering applications presented in the
application layer section. In addition, the impact of
one engineering decision on other applications is
highlighted due to the interaction between the data
captured in the model.
5.2. Application layer of the KdCPD system
architecture
The application layer consists of two elements:
decision support engineering applications and infor-
mation management tools. Details of each element are
presented next.
5.2.1. Decision support engineering
applications
The application layer provides a range of key
product life cycle applications that need to be pre-
formed in a collaborative manner. As a result, the
system supports a range of engineering and manu-
facturing activities as emphasised during the industrial
survey.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140134
This research is concerned with the injection
moulded product development; hence the proposed
decision support engineering applications are project
management, specification definition, plastic product
engineering, process engineering, injection mould
design and fabrication. Each of these applications
contains sub-applications in order to provide the
specific support during product development.
It is important to mention that due to the provision
of both product data and manufacturing process
information, the engineering applications provide:
� a
level of automation when taking a decision;� t
he capability to be performed in parallel;� t
he flexibility to move from one application toanother without the need to follow a rigid sequence
assuming there is sufficient product data available.
The need of capturing and delivering knowledge in
real time is fulfilled by providing advice based on
relevant knowledge during the product engineering,
process engineering and tool making applications. In
addition, the end users are provided with collaborative
tools in order to maintain communication amongst
the distributed team. NetMeeting is used as the
communication mechanism in the implementation
of the system, as explained in Section 6.2.3. The
following sections will describe the elements of the
architecture, which are being implemented as pre-
sented in Section 6.
5.2.1.1. Project management applications. This
application provides the involved team members with
a project timing plan, which includes tasks status,
times and required resources [30].
5.2.1.2. Specification definition applications. This
application is concerned with capturing customer
requirements in order to ensure that the voice of the
customer is represented throughout product develop-
ment. This will facilitate performing quality function
deployment.
5.2.1.3. Product engineering applications. The pro-
duct engineering applications consist of several sub-
activities. These are design session, design for
manufacturing, FMEA and cost calculation. These
applications are implemented in the system to be
performed in a collaborative manner, as it was
highlighted in the industrial survey. A description of
each of them follows.
During the design session application the user
defines the product in terms of features, such as wall,
ribs and webs. The geometric representation of the
product is available in a 3D viewer. The product
feature information is stored in the product model and
used by different engineering applications to support
decision making after invoking the required informa-
tion from the manufacturing knowledge model. This is
to validate that any decision taken falls within the
manufacturing constraints.
The design for manufacturing (DFM) application
ensures that product functional features can be
moulded without problems and also provides feedback
to the designer whenever problems arise.
The cost calculation application estimates the
product development cost according to the three key
elements of information: product design, material and
required production resources.
The failure mode effective analysis application
(FMEA) identifies the potential product failure and
their causes in order to eliminate them from the
design. It requires the input from the product life cycle
experts through a virtual meeting environment.
5.2.1.4. Process engineering applications. The selec-
tion of production equipment application selects the
suitable injection-moulding machine for the produc-
tion of a specific plastic part. In order to calculate the
required machine size it is necessary to consider the
product design information available from the product
model.
The process parameters application gives advice to
the process engineer about the optimum operation
parameters (i.e. the injection pressure, the plastic
material melting temperature, the mould temperature
and the cycle time) of the selected injection machine.
These calculations are based on process and material
capabilities captured in the manufacturing knowledge
model as well as on product data and mould design
information available from the product model.
5.2.1.5. Tool making applications. The mould design
application uses product design data stored in the
product model to give advice about the best options to
define the injection mould elements, such as standard
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 135
plate, core, cavity, feed system (sprue, gate and
runner), venting system, cooling system and ejection
system. The process and resources capabilities stored
in the manufacturing knowledge model support this
application.
The mould fabrication application advises the
mould manufacturer about the best mould fabrication
methods, such as machining or EDM. The design data
of the plastic part and the injection mould stored in the
product model is used along with the manufacturer
knowledge model to produce this advice.
5.2.2. Information management applications
The proposed KdCPD system is based on timely
and accurate provision of information, which in turn
supports the engineering applications. Hence, the need
to have information management applications is to
control information access, maintain the knowledge
and manage the geographically distributed collabora-
tive team. The information management application
includes three main sub-applications. These are:
� T
eam management application: to capture teammembers data, responsibilities, expectations and
their right to access the different elements of the
system.
� P
roduct files access application, to upload/down-load documents from within the product model.
� K
nowledge management application, for theKdCPD administrator to maintain and upgrade
the manufacturing knowledge model.
5.3. End user layer
The end user layer forms the front end of the
system. It consists mainly of a web browser, such as
Internet Explorer or Netscape, to view and use the
different decision support engineering applications
and collaborative tools.
6. Knowledge web-based KdCPD system
6.1. The implementation of the KdCPD system
The proposed system architecture is being devel-
oped as a modular-based prototype. The manufactur-
ing knowledge model and the product model are
implemented as object oriented databases using the
Object StoreTM [31] database management system.
They reside in the back-end of the system and are
accessed by the engineering applications using
standard based CORBA [32] connectivity.
Fig. 6 shows the web interface of the implemented
KdCPD system. This interface includes a menu of
engineering and information management applica-
tions located on the left side of the screen. As
described in Section 5.2, the engineering applications
are classified in the following activities: specifications
definition, product engineering, process engineering,
tool making and project management. Each of these
activities contains a set of sub-applications. The
information management menu contains team man-
agement, product file access and knowledge manage-
ment applications. At this stage, two engineering
applications have been implemented in the KdCPD
system: ‘‘design session’’ and ‘‘design for manufac-
turing’’. In addition, other applications such as
‘‘selection of production equipment’’ and ‘‘mould
design’’, are in their preliminary stage of develop-
ment.
The implementation of the engineering applica-
tions use object oriented technologies, such as JavaTM
[33] and Java3DTM languages. Such applications
contain the graphical user interface and the CORBA
connection to the databases. They receive input data
from the end user and send it to the databases, where
the information is processed and a response is sent as
feedback advice. The next section describes some of
the functionalities of the system through a case
study.
6.2. A case study of collaborative DFM of an
injection moulded part
Fig. 5 illustrates a view of the interaction between
the different elements of the system architecture
presented in Section 5, while Fig. 6 shows the software
implementation of such system. A designer collabo-
rates with a mould maker to consider the design for
manufacturing issues of a plastic part shown in Fig. 5a.
This is an electrical housing prismatic part that has
three bosses for assembly purposes. The following
section presents in some detail the interaction between
the product model, the manufacturing knowledge
model and the product engineering applications.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140136
Fig. 5. Interactions between the end users, engineering decision support applications and knowledge and product models.
6.2.1. Design session
Product development in this collaborative environ-
ment starts by selecting the ‘‘design session’’
application. Fig. 6 illustrates the typical graphical
user interface, which is tailored as follows: menu to
define a product in terms of features, data input fields,
geometric representation area and feedback advice
area.
The end user needs to input general information
of the product, such as product name, general
dimensions, weight material and production quan-
tity. By pressing the ‘‘OK’’ button the data is
captured in the product model and the end user can
start defining the product in term of features, as
illustrated in Fig. 5b and c. The wall feature is
considered to be the main feature of a plastic
product, on which other features (e.g. ribs, bosses,
holes, etc.) are placed. Each feature must have a
name and attribute, which are used throughout the
analysis sessions of the KdCPD system. The end user
has the option to specify whether the feature is
critical or not for the part functionality. This is used
to prioritise them during the DFM analysis.
The feature definition is confirmed by pressing the
‘‘OK’’ button. A message is displayed in the feedback
area to confirm the successful capturing of the data or
any other problem. Then, the 3D virtual geometric
model of the feature is displayed in the geometric
representation area.
The part definition is stored in the product model
(see Fig. 5c) and used by other engineering applica-
tions to support decision making after invoking the
required constraints from the manufacturing knowl-
edge model as explained in Section 5.1.1. One of these
applications is ‘‘design for manufacturing’’, which is
presented in the following section.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 137
Fig. 6. The graphical user interface of the knowledge driven collaborative product development system.
6.2.2. Design for manufacturing application
The ‘‘Design for manufacturing’’ application is
accessed by clicking the corresponding icon. The first
step is to load product data from the product model.
Then, by pressing the ‘‘Start DFM’’ button one of the
following manufacturability analyses will start:
� P
art DFM: the system analyses the features of thepart prioritising the critical ones.
� F
eature by feature DFM: the user has the choice toselect any specific feature for its analysis.
As illustrated in Fig. 5e, the result of this analysis is
displayed in the feedback section and it is also stored
in a file to be shared amongst the geographical
distributed team.
The DFM analysis is illustrated using the ‘‘Base
Wall’’ defined with the following attributes: thickness,
6 mm; width, 80 mm; length, 80 mm, and without
draft angle. The DFM application invokes the
appropriate data from the manufacturing knowledge
model to validate the manufacturability of the ‘‘base
wall’’ (see Fig. 5b and d). This wall is outside
manufacturability constraints, so the application sends
a feedback advising to reduce the wall thickness to
1.8 mm, as shown in Fig. 5d and e. This value is based
on the recommendation of the plastic material
provider. The designer needs to change those values
in the appropriate fields. The new data is stored in the
product model by pressing ‘‘OK’’, as shown in Fig. 5c.
At the same time, the system displays these changes in
the virtual geometric model. In this way, the user is
aware of how the manufacturing constraints directly
affect the geometry of the part.
The mouldability of other features, such as the
boss, depends on the wall on which these are attached.
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140138
Bosses are commonly used for assembly purposes.
The rules for the maximum permitted height and
thickness are:
Boss height ¼ ð2:5 � wall thicknessÞ;
boss thickness ¼ 1
3ð2 � wall thicknessÞ
As shown in Fig. 5b, a boss is defined with the
following attributes: diameter, 20 mm; thickness,
5 mm; height, 15 mm, and without draft angle and
base radius. The system gives feedback advice to the
designers to reduce the height of the boss to 4.44 mm,
the thickness to 1.18 mm, add a draft angle of 18 and a
base radius of 0.58 as illustrated in Fig. 5e.
6.2.3. Other functionality of the KdCPD system
After running the product engineering applications,
the updated product design data is captured in the
product model. This data is available to other
engineering applications and distributed team mem-
bers. The other applications of the KdCPD system use
the same approach to support the geographically
distributed team.
The collaboration amongst a distributed product
development team is achieved by different mechan-
isms:
� B
y providing real time access of both product dataand manufacturing knowledge, facilitating the
following:
� One engineer interacting with the system,
while the other team members are able to
observe and trace the product development by
accessing the results. This case is illustrated in
Fig. 5.
� Two or more engineers, such as designer and tool
engineer, are able to use different engineering
applications simultaneously to develop a product.
� Two designers are able to access the same
engineering application to continue developing
the same product at different times.TM
� B y providing a tool, such as NetMeeting [34], toperform the applications in a collaborative envir-
onment. For this purpose, a NetMeeting session can
be started during the engineering activities that
require collaboration of the geographically dis-
tributed team members, such as ‘‘design session’’
and ‘‘design for manufacturing’’. NetMeeting
provides the following communications tools: chat
sessions, videoconference and whiteboard.
7. Conclusions
The paper has presented a novel approach of a
system architecture that guides the development and
implementation of a knowledge driven collaborative
product development system. A demonstration of its
application in injection moulded product development
has also been presented.
The research has been conducted by adapting a
practical methodology based on both findings from
extensive analysis of existing CPD systems and an
industrial survey. The latter has clearly shown the
interest of the manufacturing companies in the area of
CPD. Mapping their requirements with the findings of
the reviewed systems has led to the identification of
the key technological requirements. These require-
ments should be addressed in order to have an
effective CPD system that aids solving real engineer-
ing problems. One of the main requirements, which
the authors have emphasised as a major contribution
for the next generation of CPD systems, is the real
time provision of manufacturing knowledge. The
sources of this knowledge are the manufacturing
process and resource capabilities, company experi-
ence, industrial heuristic knowledge and other
technical documents available from the material and
machinery providers. This knowledge is stored in a
manufacturing knowledge model.
The web-based environment and the object
oriented technologies have demonstrated to be a good
development platform for the KdCPD system. In order
to integrate and share the information and knowledge
available in geographically distributed companies,
applications based on CORBA reference model [32]
have proven to be essential. In addition, the inter-
operability among the different heterogeneous ele-
ments of the system is also achieved by using the
CORBA standard.
The availability of both product data and manu-
facturing process information has facilitated a level of
automation when taking engineering decision in a
geographically distributed environment.
The use of a feature-based approach in this
collaborative environment has provided the integra-
K. Rodriguez, A. Al-Ashaab / Computers in Industry 56 (2005) 125–140 139
tion between the engineering applications and the
manufacturing process knowledge. However, it has
limited the geometric representation of complex
products. In addition, the geographically distributed
team members could visualize the product data in a
geometric virtual model, but its translation to a proper
solid model yet needs to be achieved.
The proposed approach does not aim to replace
existing systems in companies but rather to be a
support tool for communicating and sharing knowl-
edge among the geographically distributed partners.
The implementation of this system could be con-
sidered feasible among the partners of one industrial
group or extended enterprise, who are bonded by
common financial interests. Such system will lead to
the production of better and more cost effective
products, developed in a shorter period of time.
Acknowledgements
The authors gratefully acknowledge Latmier
Technologies, Arvin Meritor and Denso for their
support in providing information during the initial
stages of this research. In addition, the authors would
like to thank Excelon for providing the object oriented
database management system Object StoreTM and Dr.
Reyna Al-Ashaab for her valuable help with reviewing
the text of this paper. Miss Rodriguez Ph.D. research
study is supported by a bursary from the University of
Wolverhampton.
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Ahmed Al-Ashaab is a Senior Lecturer
in the School of Engineering and Built
Environment in the University of Wol-
verhampton. Ahmed obtained his Ph.D.
from Loughborough University in 1994.
Since then he has worked in the ITESM
Campus Monterrey in Mexico where 50%
of his time was spent working with Mex-
ican industry. He has been active in
introducing and implementing NPI/D
methodologies based on concurrent engineering within the Mexican
manufacturing companies. He is the Founder and was the President
of the Mexican Society of Concurrent Engineering. His research
interests are CE, knowledge based engineering, extended and virtual
enterprises and collaborative product development. Dr. Al-Ashaab
has written many international publications and participated in
several of conference committees and session chair. Dr. Al-
Ashaab is the Publicity Chair of the ISPE/CE2xxx series confer-
ences.
Karina Rodriguez is Ph.D. student in the
School of Engineering and Built Envir-
onment in the Wolverhampton Univer-
sity. She has a Computer Science
Honour degree from the ITESM Campus
Monterrey in Mexico in 1999. She
worked as Research Assistant in the
CSIM of ITESM Campus Monterrey in
the SPEED project. Her research interests
are knowledge based engineering, infor-
mation modelling and internet based collaborative product devel-
opment.
