Product Data Quality and Collaborative Engineering
Manuel Contero
*
, Pedro Company
†
,
Carlos Vila
†
, Nuria Aleixos
†
*
Polytechnic University of Valencia and
†
Jaume I University
Abstract
In this paper, the impact of product data quality in the
implementation of collaborative engineering in an extended
enterprise framework is analyzed. Previously, some
definitions about collaborative and concurrent engineering
and present concepts like extended and/or virtual enterprise,
digital mock-up, virtual prototype and virtual factory are
reviewed.
The product data model as a key element for the product
development process is analyzed. The different views of this
model are placed according to the fields where they apply.
The importance of product model quality in the current status
of data exchange standards is highlighted, with particular
attention to ISO 10303 (STEP) new developments. Current
state-of-art on data quality models, and product data quality
recommendations such as VDA 4955/2 and SASIG PDQ, are
also revised. Finally, our own product data quality model is
presented. This comprises three points of view or levels:
morphological, syntactic and semantic. Hence, it provides a
tool for a better understanding of product data quality that
helps find solutions that avoid the interoperability problem.
Throughout the paper, references to the automotive industry
will be used to illustrate concepts.
Front-page photo: The left image
represents an automotive radiator
model simplified for FEM analysis.
The central image shows the mesh
model, and the right image
represents modal analysis results
Introduction
Product Development is a key activity for enterprise
survival and competitiveness. This process must be agile and
efficient so as to provide enough flexibility to adapt to a
changing market. Most new Product Development methods
are based on empowering the role of design and shortening
the development cycle of new products. Digital tools like
CAX and Product Data Management (PDM) systems are key
elements in this strategy. They allow product developers to
experiment with many alternative solutions, providing better
products with better quality, in less time and at a lower cost.
Shortening the development cycle and lowering cost are some
of the advantages of employing digital mock-ups and
simulating the manufacturing process in a virtual
environment.
A complete digital representation of the product and its
manufacturing process allows complex simulations to be
carried out, avoiding the construction of physical prototypes
and providing early detection of bottlenecks in the
manufacturing process. In this way, an important time
reduction in the whole development process as well as better
quality are obtained, because more design alternatives can be
explored. However, this approach is not exempt of problems,
because it is necessary to transfer product data between
different software applications. This introduces the data
exchange problem, because data can be lost or degenerated
during exchanges. In this context, product data quality is
becoming a key issue to guarantee a true integration among
participants defining the product development process.
Concurrent Engineering
Product Development has suffered an enormous evolution
during the last two decades. The appearance of Concurrent
Engineering (CE) was a milestone in simultaneously lowering
product cost, increasing product quality and reducing time to
market. Concurrent Engineering began as an initiative of the
US Department of Defense. In 1982, the Defense Advanced
Research Projects Agency (DARPA) began a program with
the objective of improving Product Development. As a result
of this program, Winner et al. [1] first defined the term
Concurrent Engineering as “… a systematic approach to the
integrated, concurrent design of products and their related
processes, including manufacturing and support. This
approach is intended to cause the developers, from the outset,
to consider all elements of the product life-cycle from
conception to disposal, including quality cost, schedule, and
user requirements.”
After this project, the DARPA started a five-year
program: the DARPA Initiative in Concurrent Engineering
(DICE), aimed to incorporate this methodology in the US
military industry. As part of this initiative, the “Concurrent
Engineering Research Center” (CERC) was founded at West
Virginia University in the US. As a result of this work,
Cleetus [2] proposed another definition for CE: “Concurrent
Engineering is a systematic approach to the integrated and
concurrent development of a product and its related processes,
that emphasizes response to customer expectations and
embodies team values of cooperation, trust, and sharing in
such a manner that decision making proceeds with large
intervals of parallel working by all life-cycle perspectives,
synchronized by comparatively brief exchanges to produce
consensus.”
Extended and Virtual Enterprise
At the end of 90’s the quest for reducing costs lead to the
progressive outsourcing of design tasks to suppliers. This
movement brought suppliers into greater involvement in
design and product technology responsibility [3]. The most
advanced industries, like the automotive, aeronautical and
aerospace ones, soon adopted this trend. Automotive maker
Chrysler pioneered the development and use of the Extended
Enterprise concept. It means working closely with the supply
base in a teamwork atmosphere of cooperation based in trust,
communication and partnership, where the workgroup is
usually geographically dispersed and advanced tools support
communications.
In recent years, new enterprise models appear to exploit
modern high-performance computer networks. In this context,
the concept of Virtual Enterprise [4] with its sharing of data,
costs, skills, and technology allows this new kind of enterprise
to put products in the market that they could not previously
deliver individually. The European Society of Concurrent
Engineering [5] defines a Virtual Enterprise as a “distributed,
temporary alliance of independent, co-operating companies in
the design and manufacturing of products and services. Such a
complex organization makes use of systematic approaches,
methods and advanced technologies for increasing efficiency,
and is enacted by the means offered by recent Information and
Communication Technologies”.
Concurrent Enterprise
Integrating the Virtual Enterprise paradigm and the
methods of Concurrent Engineering, a new concept named
Concurrent Enterprise arises. Thoben and Weber [6] proposed
the following definition: “The Concurrent Enterprise is a
distributed, temporary alliance of independent, co-operating
manufacturers, customers and suppliers using systematic
approaches, methods and advanced technologies for
increasing efficiency in the design and manufacturing of
products (and services) by means of parallelism, integration,
team work, etc. for achieving common goals on global
markets.”
Collaborative Engineering
The scope of Concurrent Engineering must be broaden to
include the new models of “Extended Enterprise”, “Virtual
enterprise” and “Concurrent enterprise” that have become
commonplace during the last decade. The concept of
Collaborative Engineering encompasses both supplier
integration and advanced communications tools to cope with
the product development process and extends the scope of
Concurrent Engineering. With the intention of widening the
scope of Concurrent Engineering, de Graaf [7] proposes the
following definition for Collaborative Engineering:
“Collaborative Engineering is a systematic approach to
control life-cycle cost, product quality and time to market
during Product Development, by concurrently developing
products and their related processes with response to customer
expectations, where decision making ensures input and
evaluation by all life-cycle disciplines, including suppliers,
and information technology is applied to support information
exchange where necessary.”
Figure 1. Collaborative Engineering model.
In Figure 1, a schematic vision of our Collaborative
Engineering model is presented, based on de Graaf’s
definition. The central element is the workgroup, usually
geographically dispersed, working in the context of the
Extended and/or Virtual Enterprise. Concurrent Engineering
methodologies and Information Technologies tools support
the Product and Processes Development. As in de Graaf’s
definition, product life cycle, customer input and supplier
involvement are underlying elements included in the model.
Concurrent Engineering Methodologies
As noted in the Collaborative Engineering definition, the
virtual workgroup employs Concurrent Engineering
methodologies [8,9]. Some of the more frequently used ones
are:
x QFD (Quality Function Deployment) a structured
method in which customer requirements are translated
into appropriate technical requirements for each stage of
product development and production.
x DfX (Design for X) techniques capture, in a standard
procedure, all the factors known to be important in a
particular design activity. For example:
o Design for Manufacturability (DfM): rules that can
ease manufacturing during early conceptual
development.
o Design for Assembly (DfA): rules that can ease
assembly during early conceptual development.
o Design for Environment (DfE): rules to achieve a
design that uses minimum material and energy at all
stages of its life cycle providing maximum reuse and
recycling of products.
x FMEA (Failure Model and Effects Analysis): a
procedure by which each potential failure mode in a
system is analyzed to determine the potential effects
caused on the system and to classify each potential failure
mode according to its severity.
x DOE (Design of Experiments): a branch of applied
statistics dealing with planning, conducting, analyzing,
and interpreting controlled tests to evaluate the factors
that control the value of a parameter or group of
parameters.
x Taguchi methods: a quality engineering methodology,
based on the design of experiments to provide near
optimal quality characteristics for a specific objective to
improve quality and reduce costs.
Information Technology Tools
Information Technology (IT) development has completely
transformed the Product Development. New methodologies,
specifically oriented toward shortening the development
cycle, have been adopted. The present growth in simulation-
based design tools makes it possible analyzing the behavior of
complex products without constructing physical prototypes.
Virtual factory software permits production to be simulated,
and bottlenecks to be detected early in the factory design
phase. These new methods are represented in Figure 2. The
essential element in this development approach is the 3D solid
model provided by CAD applications. A plethora of
downstream applications like CAM, CAE and many other
CAX tools depends on the geometric model.
Digital Mock-Up (DMU) tools are able to manage large
assemblies of thousands of parts. In this way, it is possible to
detect tolerance and assembly problems early in the design
phase. Current DMU applications are capable of managing
complex products such as a complete airplane representation.
However, optimized tessellated representations extracted from
the 3D solid models are needed to cope with so many parts.
Some systems also provide several representations for each
part, each one according to a different Level of Detail (LOD).
These tools provide simultaneous capabilities for design
collaboration, mark up, fly through, and interference and
collision detection.
Virtual Prototyping tools go a step beyond. Their
objective is to assess product function and operating
performance. Virtual Prototyping solutions make use of finite
element analysis and advanced calculus to accurately predict
the operating performance of the product by means of virtual
tests. Thus, we can simulate a crash test with a virtual car,
analyze its dynamic behavior, optimize aerodynamics with
computational fluid dynamics (CFD) applications, and so on.
In the superior stage, Virtual Factory Simulation [10] is
used to assess manufacturability and assembly of the product.
There are two main types of simulations:
x Discrete event simulation (DES) applications simulate
the behavior of entities when an event occurs at a distinct
time. This kind of simulation is aimed at material flow
simulation, manufacturing system and information flow
analysis. Usually, time in a DES simulator does not
proceed linearly but in irregular intervals.
x Geometric simulation GS, also known as continuous
simulation, proceeds with time linearly in constant
intervals, and provides a geometric representation of the
whole manufacturing system. It is appropriate for 3-D
visualization, off-line programming of robots and
collision detection during manufacturing process.
Figure 2. Advanced product development.
Virtual Factory Simulation provides significant savings,
allowing early detection of manufacturing bottlenecks in the
design phase, not under operation.
PMD and cPDm
Product Data Management (PDM) [11] is the supporting
tool that enables these advanced simulations to be performed.
PDM has evolved from a mid-80’s CAD file manager
application to provide sophisticated functions:
x Engineering Data Management: providing data vaulting
and document management, product structure and
configuration management, classification and search.
x Engineering Workflow Management: providing project
management, engineering change and release
management and communication support.
At present, PDM systems are evolving to take into
account Internet, Web-based technologies, and the new
extended and/or virtual enterprise paradigm. This evolution
leads to the concept of “collaborative Product Definition
management” (cPDm) [12], which is a broadening of PDM
capabilities to support the management of product definition
and associated processes in the extended enterprise
framework by means of Internet/Web technologies. Systems
such as these are particularly interesting for global companies
with facilities located around the world and also for enabling
true integration among OEMs, clients and suppliers in the
product development process.
Figure 3. Evolution from PDM to cPDm
Web-based CAD and Communication Tools
The heterogeneous enterprise architectures presented
previously encouraged the development of new Web-based
design tools, which combine CAD, PDM and Web access in a
unified environment. These tools are aimed at reducing costs
between Original Equipment Manufactures (OEMs) and
suppliers sharing a common design platform. Usually these
kind of applications are built on a 3-tier architecture using
Internet as the communication infrastructure. Thus, we have a
first tier where a Thin Client, usually through an Internet
navigator, provides the front-end to the system. In a second
tier, an Application Server hosts the software application.
Finally, the Database Server holding the central data
repository that stores and manages design data provides the
third tier. This technology also introduces the concept of
subscription, where users pay a monthly subscription fee for
the service. This approach allows companies to reduce
information technology expenses by avoiding the need to buy
and maintain expensive software and hardware. The growing
Internet bandwidth is supposed to broaden this technology in
the near future.
Finally, Communication Tools as supporting technologies
for Collaborative Engineering will be discussed. These tools
are evolving parallel to Internet, and are fundamental to
providing collaboration for a geographically dispersed work
team. A distinction can be done between synchronous and
asynchronous collaboration [13], depending on whether the
collaborative partners are working simultaneously or not.
Examples of asynchronous collaboration are e-mail and
newsgroups. On the other hand, to arrange a virtual meeting
between the partners, synchronous communication tools are
needed; such as whiteboards, videoconferencing and
application sharing. In the context of the extended enterprise,
it is usual to find a multi-platform and multi-vendor
environment. For that reason, communication standards are an
enabling element to real team collaboration. The International
Telecommunication Union and the International Multimedia
Teleconferencing Consortium have developed several
families of standards for this purpose. Thus, the T.120 Series
of Recommendations collectively define a multipoint data
communication service for use in multimedia conferencing
environments. Inside this series, Recommendations related to
the communication layer are found (T.122, T.123 and T.125).
The collaboration layer provides support for both data and
audio/video conference. The recommendations related to data
conferencing are:
x T.126: Multipoint still image and annotation protocol.
x T.127: Multipoint binary file transfer protocol.
x T.128: Multipoint application sharing.
x T.134: Text chat application entity.
Figure 4. Architecture of communication tools.
The Audio/Video conferencing part proposes three
standards associated with communication bandwidth:
x H.320 for ISDN videoconferencing.
x H.323 for LAN videoconferencing.
x H.324 for low bit rate connections such as POTS.
Nowadays, the main limitation for the use of these tools is
communication bandwidth. From a practical point of view, in
restricted bandwidth situations parts of the data-video-audio
conference can be redirected to other communication
channels; for instance, moving audio conferencing to normal
telephone calls, and making a selective use of the video,
which is the most bandwidth consuming part.
One of the most interesting facts about communications
tools is that many of them are free, or have a very reduced
cost. Thus, an imaginative use of them can be very
productive. For example, setting up a newsgroup server can
be a very inexpensive way to provide a discussion forum
where work team members can ask for help or receive general
notifications about the product development process.
To finish this analysis of Collaborative Engineering, it
must be emphasized that the key for all the Product
Development Process is a digital product representation. The
next section will study this aspect in depth.
Product Data Model
CAD and PDM systems are the primary elements for the
Advanced Product Development Process, as noted in Figure
2. Product Data Management Systems [11,14] supply an
infrastructure oriented to provide everybody’s need of
information in a concurrent engineering environment. These
systems also cover external partners’ access, and company
security and release procedures. The following can be
distinguished:
x Product data (and tooling data): geometry, DMU,
analysis and simulation results, materials, reports, etc.
x Process data: advanced manufacturing engineering data
(relations between parts/tools/processes), build sequence
planning and machining data, work cell definition and
plant layout, and so on.
Both types of data are closely related to the geometric
model provided by CAD applications. As will be seen later,
the quality of these CAD models will be of vital importance
for a smooth integration among the participants of the Product
Development Process.
Primary and Secondary Views
From a practical point of view, as this analysis is restricted
to the available commercial technology, we propose the
Product Data Model represented in Figure 5. This model is
built on a PDM system, which serves as the repository of the
different product views that integrate the Digital Product
Master Model. CAD provides the connection line among
those different views.
Current technology is clearly biased towards Design, [16].
Hence, the 3D solid models are considered as the Primary
View, deriving Secondary Views for other purposes like
DMU, analysis or manufacturing. Any modification of the
geometry must be performed on the Primary View. The way
in which the different tasks in the Advanced Product
Development Process make use of the Primary View will now
be analyzed:
x Documentation: Most of the Engineering Drawings are
obtained from the 3D geometric model. Projections and
sections are easily created from the 3D model. Many
parametric systems propose a set of dimensions, and the
user has only to select the more convenient ones.
Nevertheless, in the near future, we expect the drawings
to be relegated to a secondary role. They will be even
eliminated, at least in the most technological advanced
industries; in step 3 of VDA 4953 Recommendation [15]
the creation of drawings is omitted. The legal
implications should be noted, since OEMs assign a
binding nature to CAD model data [17].
x Rendering: this application takes advantage of the 3D
model by means of a surface representation generated by
a tessellation process, as provided by the
stereolithography STL format.
x Digital mock-ups: This application usually uses
simplified representations of parts, obtained by
