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<strong>Internet</strong>-<strong>based</strong> <strong>intensive</strong> <strong>product</strong> <strong>design</strong> <strong>plat<strong>for</strong>m</strong> <strong>for</strong> <strong>product</strong> <strong>design</strong><br />
Shouqin Zhou* ,1 , Kwai-Sang Chin b , Prasad K.D.V. Yarlagadda a<br />
a School of Mech., Mfg., and Medical Eng., Queensland University of Technology, Brisbane, QLD 4001, Australia<br />
b Department of Manufacturing Engineering & Engineering Management, City University of Hong Kong, Kowloon, Hong Kong, People’s Republic of China<br />
Received 20 August 2001; accepted 4 February 2002<br />
Abstract<br />
For overcoming the limitations of traditional computer aided <strong>design</strong> <strong>plat<strong>for</strong>m</strong>, a framework of the <strong>Internet</strong>-<strong>based</strong> <strong>intensive</strong> <strong>product</strong> <strong>design</strong><br />
<strong>plat<strong>for</strong>m</strong> (IPDP) is proposed. The structure of IPDP and the key issues regarding its implementation are introduced. Further, the mean of<br />
knowledge storage, acquisition, and representation are portrayed in detail. Based on the concept of function driven, connected artificial neural<br />
networks and active server pages techniques, a novel method of knowledge search over the <strong>Internet</strong> is achieved. Finally, a prototype to<br />
demonstrate the feasibility of the structure and the constructional method of IPDP is developed. q 2003 Elsevier Science B.V. All rights<br />
reserved.<br />
Keywords: Product <strong>design</strong>; Knowledge engineering; <strong>Internet</strong>-<strong>based</strong>; Artificial neural network; Standard <strong>for</strong> the exchange of <strong>product</strong> model data<br />
1. Introduction<br />
The quality of the <strong>product</strong> heavily lies in its <strong>design</strong> [1].<br />
As increasing concerns over global environmental issues<br />
and rapidly changing economic situations worldwide,<br />
<strong>design</strong> must exhibit per<strong>for</strong>mance, not only in quality and<br />
<strong>product</strong>ivity, but also in life cycle issues including extended<br />
producers’ liabilities [2,3]. This requires that <strong>design</strong>ers and<br />
engineers use various kinds of <strong>design</strong> knowledge <strong>intensive</strong>ly<br />
during <strong>product</strong> <strong>design</strong>. As <strong>product</strong>s become more complex<br />
and competition intensifies, it is essential to make the<br />
maximum use of the available knowledge and to deliver that<br />
knowledge in an appropriate <strong>for</strong>m at the right time during<br />
the <strong>product</strong> development process.<br />
In addition, currently, CAD technology plays a key role<br />
in today’s advanced manufacturing environment [2]. The<br />
<strong>design</strong>er increasingly depends on various commercial CAD<br />
<strong>plat<strong>for</strong>m</strong>s, such as Pro/E, AutoCAD, and UGII. However,<br />
the knowledge repositories of these commercial CAD<br />
systems are self-contained and closed. When a <strong>design</strong>er<br />
using a commercial CAD system <strong>design</strong>s a <strong>product</strong>, he must<br />
* Corresponding author. Address: Faculty of Built Environment and<br />
Engineering Research Concentration in Manufacturing Systems<br />
Engineering, 2, George Street GPO Box 2434, 4001 Brisbane, Qld,<br />
Australia. Tel.: þ61-7-38642423; fax: þ61-7-38641469.<br />
E-mail addresses: zhoushouqin@263.net (S. Zhou),<br />
s.zhou@qut.edu.au (S. Zhou).<br />
1<br />
Tel.: þ61-7-38642423; fax: þ61-7-38641469.<br />
Knowledge-Based Systems 16 (2003) 7–15<br />
0950-7051/03/$ - see front matter q 2003 Elsevier Science B.V. All rights reserved.<br />
PII: S0950-7051(02)00035-7<br />
www.elsevier.com/locate/knosys<br />
base it on the inside repositories of the commercial CAD. If<br />
a <strong>design</strong>er wants to add new knowledge, he must expand the<br />
repositories of the commercial CAD system and <strong>based</strong> on<br />
the special data structure of the CAD system. There<strong>for</strong>e,<br />
embodying a user’s knowledge into the repositories of a<br />
commercial CAD system is very difficult. Besides, only<br />
vendors themselves have the option of updating the<br />
repositories of CAD. However, it is impossible <strong>for</strong> a vendor<br />
of a CAD <strong>plat<strong>for</strong>m</strong> to involve all the various kinds of<br />
knowledge in his CAD system repositories to bring them up<br />
to date.<br />
Since <strong>product</strong> <strong>design</strong>er need to utilize an amount of<br />
knowledge coming from various locations, domains and<br />
disciplines, and any single <strong>plat<strong>for</strong>m</strong> could not entirely<br />
posses all kinds of knowledge. There<strong>for</strong>e, to meet the need<br />
of <strong>design</strong>er on knowledge resource during <strong>product</strong> development,<br />
it is necessary to construct an <strong>intensive</strong> <strong>product</strong><br />
<strong>design</strong> <strong>plat<strong>for</strong>m</strong> through combining commercial CAD and<br />
outside knowledge repositories. Form this standpoint, the<br />
<strong>Internet</strong>-<strong>based</strong> <strong>intensive</strong> <strong>product</strong> <strong>design</strong> <strong>plat<strong>for</strong>m</strong> (IPEP) is<br />
proposed. Based on <strong>Internet</strong> networks, this <strong>plat<strong>for</strong>m</strong> aims to<br />
<strong>for</strong>m a robust knowledge integrated <strong>plat<strong>for</strong>m</strong> to aid the<br />
<strong>product</strong> <strong>design</strong>.<br />
Recently, several studies of <strong>Internet</strong>-<strong>based</strong> collaborative<br />
CAD are being conducted, because of the potential of<br />
<strong>Internet</strong> technology [4], among them the Adaptive,<br />
Collaborative, Open Research Network project (ACORN)<br />
[5]. The aim of the project is to construct a <strong>design</strong> and
8<br />
manufacturing architecture <strong>based</strong> on the <strong>Internet</strong>, with the<br />
World Wide Web (WWW) as the user interface. A <strong>design</strong><br />
expert system controlled through the <strong>Internet</strong> and integrated<br />
with a CAD system visualizes the <strong>product</strong> shape [6]; a<br />
Concept-Modeler and an expert systems shell with CAD<br />
ability, has also been used. The interface between the expert<br />
system shell and the web was developed by Common Gateway<br />
Interface (CGI) script using Pearl [7]. A distributed <strong>design</strong><br />
expert system should use an expert system shell and provide<br />
in<strong>for</strong>mation related to <strong>design</strong> and manufacturing through the<br />
<strong>Internet</strong> and multi-agents. However, the current distributed<br />
<strong>design</strong> expert system is not <strong>based</strong> on distributed <strong>design</strong><br />
knowledge, but is limited to an expert system shell remotely<br />
operated through the <strong>Internet</strong>. Until now, there is still a little<br />
research on how to achieve the integration of multidisciplines,<br />
distributive knowledge resources, and <strong>product</strong><br />
<strong>design</strong> <strong>plat<strong>for</strong>m</strong> over the <strong>Internet</strong> to support <strong>product</strong> <strong>design</strong>.<br />
From the author’s viewpoint, and <strong>for</strong> the sake of quickly<br />
acquiring <strong>design</strong> knowledge and improving the speed of<br />
<strong>product</strong> development, a kernel problem is the mechanism of<br />
knowledge acquisition. Another problem is the <strong>for</strong>m<br />
of knowledge representation (i.e. how to achieve the<br />
<strong>design</strong> knowledge interacting among various <strong>design</strong><br />
<strong>plat<strong>for</strong>m</strong>s and directly utilized by them). With the goal of<br />
solving these problems, combining the <strong>Internet</strong> enabling<br />
technologies with CAD <strong>plat<strong>for</strong>m</strong>s, a scheme, the IPDP, is<br />
proposed. The problems of representation, storage, transference,<br />
search and implementation of knowledge in IPDP are<br />
discussed in detail later. The ultimate objective of this paper is<br />
to present a rational scheme used to integrate the knowledge<br />
resources and <strong>design</strong> <strong>plat<strong>for</strong>m</strong>s over <strong>Internet</strong> so as to support<br />
the <strong>design</strong>er in developing a high quality <strong>product</strong> quickly and<br />
efficiently.<br />
2. The structure of IPDP<br />
The framework of IPDP is shown as Fig. 1. It is<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15<br />
Fig. 1. Framework of <strong>Internet</strong>-<strong>based</strong> <strong>intensive</strong> <strong>product</strong> <strong>design</strong> <strong>plat<strong>for</strong>m</strong>.<br />
composed of three layers: traditional <strong>design</strong> <strong>plat<strong>for</strong>m</strong>,<br />
middle-ware, and knowledge repositories. The IPDP apart<br />
<strong>design</strong> <strong>plat<strong>for</strong>m</strong>s (e.g. SolidWorks) from knowledge<br />
repositories, and links them via middle-ware. The <strong>design</strong><br />
<strong>plat<strong>for</strong>m</strong>s are independent of knowledge repositories. And<br />
the outside knowledge repositories are distributed in the<br />
servers of knowledge (<strong>product</strong>) vendors, it is also independent<br />
of the <strong>design</strong> <strong>plat<strong>for</strong>m</strong>. The <strong>design</strong> <strong>plat<strong>for</strong>m</strong>s communicate<br />
with knowledge repositories via <strong>Internet</strong> control, and<br />
the knowledge is translated between them via pre/post<br />
processor.<br />
As Fig. 1 states, obviously, the IPDP is a system with a<br />
Client/Server mechanism. Common repositories are useropened,<br />
and can be expanded by any user according to the<br />
specifications of the knowledge definition. The knowledge<br />
in IPDP repositories is represented with certain standard<br />
(e.g. the standard <strong>for</strong> the exchange of <strong>product</strong> model data,<br />
STEP). All <strong>product</strong> <strong>design</strong>ers may use these repositories.<br />
Furthermore, the <strong>design</strong>ers can also add their knowledge to<br />
the repositories or construct their own repositories according<br />
to the standard. Hence, the structure of repositories in<br />
IPDP is distributed, flat and net-like. The knowledge store<br />
style of the IPDP with the distributed, user-opened and userexpanded<br />
feature breaks through the limitations of the<br />
traditional style of commercial CAD (i.e. the single stiffness<br />
closeness feature).<br />
Considering the <strong>Internet</strong> networks can integrate distributive<br />
repositories with an opened network style, in IPDP,<br />
the knowledge (outside <strong>design</strong> <strong>plat<strong>for</strong>m</strong>) acquisition,<br />
organization, construction and utilization all are<br />
implemented through the <strong>Internet</strong>. All common repositories<br />
of IPDP are constructed and integrated over the <strong>Internet</strong>. By<br />
this mechanism, <strong>product</strong> <strong>design</strong>er can retrieve and download<br />
the knowledge from common repositories of IPDP via<br />
<strong>Internet</strong> control if the knowledge inside the repository of his<br />
<strong>design</strong> <strong>plat<strong>for</strong>m</strong>s does not meet what he needs. In IPDP, the<br />
<strong>product</strong> <strong>design</strong>er still depends on traditional <strong>design</strong> <strong>plat<strong>for</strong>m</strong><br />
(commercial CAD system) to develop <strong>product</strong>. Intensively,
Table 1<br />
EXPRESS in<strong>for</strong>mation model of rolling bearing<br />
STEP in<strong>for</strong>mation model<br />
SCHEMA rolling_bearing_support_schema:<br />
ENTITY bearing:<br />
style: STRING;<br />
static_load: REAL;<br />
dynamic_load: REAL;<br />
weight: REAL;<br />
limited_speed_with_oil: REAL;<br />
limited_speed_with_grease: REAL;<br />
external_diameter: REAL;<br />
inner_diameter: REAL;<br />
width: REAL;<br />
install_damin: REAL;<br />
install_damax: REAL;<br />
install_rasmax: REAL;<br />
other_d2_inner: REAL;<br />
other_d2_external: REAL;<br />
other_rsmin: REAL;<br />
END_ENTITY:<br />
END_SCHEMA:<br />
he can use not only the repositories inside the commercial<br />
CAD system, but also the common outside repositories via<br />
<strong>Internet</strong> control. Due to the common repositories are<br />
maintained by knowledge (<strong>product</strong>s) providers, they can<br />
quickly be updated and kept up to date. Since knowledge<br />
providers are distributed in all kinds of disciplines and to<br />
various sites, the knowledge in the repositories of the IPDP<br />
can abundantly contain distributive, various discipline<br />
knowledge resources. Consequently, a robust <strong>intensive</strong><br />
<strong>product</strong> <strong>design</strong> <strong>plat<strong>for</strong>m</strong> is <strong>for</strong>med.<br />
To achieve this IPDP framework successfully, there are<br />
server all-important issues need to be solved. Firstly, the<br />
common repositories of IPDP are distributed at various<br />
locations, domains and disciplines. And the knowledge<br />
stored in them should be utilized with various <strong>design</strong><br />
<strong>plat<strong>for</strong>m</strong>s. So the knowledge must be represented with a<br />
neutral <strong>for</strong>m independent of <strong>design</strong> <strong>plat<strong>for</strong>m</strong>s, meanwhile, it<br />
should be understood by them via knowledge processor.<br />
Secondly, because the IPDP is constructed over the <strong>Internet</strong><br />
and its knowledge repositories is a dynamic league of<br />
knowledge sites, an efficient method of knowledge search<br />
within <strong>Internet</strong> environment must be provided to assure the<br />
running per<strong>for</strong>mance of IPDP. The following content then<br />
will discuss these issues in detail.<br />
3. Knowledge representation<br />
As stated in Section 2, a key issue of the IPDP is that the<br />
knowledge retrieved from the repositories of IPDP should<br />
be directly utilized <strong>for</strong> various <strong>design</strong> <strong>plat<strong>for</strong>m</strong>s. So, if the<br />
knowledge is still represented in a traditional handbook with<br />
such things as data, tables and, diagrams, the user must<br />
translate the knowledge into a <strong>for</strong>mat that his <strong>design</strong><br />
<strong>plat<strong>for</strong>m</strong> can understand. For example, a <strong>product</strong> <strong>design</strong>er<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15 9<br />
needs a rolling bearing when he <strong>design</strong>s the structure of a<br />
<strong>product</strong> with a Solidworks <strong>plat<strong>for</strong>m</strong>. If the <strong>product</strong> <strong>design</strong>er<br />
gains the detailed structure of the rolling bearing from a<br />
traditional <strong>for</strong>mat such as a handbook, table or diagram, it<br />
cannot be directly understood in a Solidworks <strong>plat<strong>for</strong>m</strong>. As<br />
a result, the <strong>design</strong>er must draw a rolling bearing with<br />
Solidworks using the rolling bearing in<strong>for</strong>mation as<br />
represented in traditional handbook <strong>for</strong>m. This indicates<br />
that the traditional handbook representation limits the level<br />
of knowledge utilization and the speed of <strong>product</strong><br />
development.<br />
Since the repositories of the IPDP are independent of the<br />
application <strong>plat<strong>for</strong>m</strong>, and the knowledge acquired by the<br />
<strong>design</strong>er requires that it directly utilize the application<br />
<strong>plat<strong>for</strong>m</strong>, the knowledge representation must be standardized.<br />
The standard <strong>for</strong> the exchange of <strong>product</strong> model data<br />
(STEP) [8,9], released by ISO, can implement the<br />
in<strong>for</strong>mation expression depending on various application<br />
<strong>plat<strong>for</strong>m</strong>s. It is a standard <strong>based</strong> on the EXPRESS language<br />
[10], which can grow and can be extended to any industry<br />
and will not be outdated as soon as it is published. The<br />
EXPRESS language describes constraints as well as data<br />
structure. The <strong>for</strong>mal rules of the STEP standard will<br />
prevent conflicting interpretations. The knowledge represented<br />
in the STEP standard can felicitously meet the<br />
requirements of the IPDP system on the knowledge<br />
representation <strong>for</strong>m. Since STEP provides a mechanism<br />
<strong>for</strong> describing <strong>product</strong> data models and EXPRESS featureneutral<br />
and independent of any application <strong>plat<strong>for</strong>m</strong>.<br />
Besides the traditional <strong>for</strong>m, in this paper, the knowledge<br />
in common repositories of the IPDP is also represented with<br />
EXPRESS language <strong>based</strong> on the STEP standard. Hence,<br />
the <strong>design</strong>er can acquire not only the traditional handbook<br />
<strong>for</strong>m but also the STEP in<strong>for</strong>mation model of knowledge<br />
from repositories of the IPDP. The STEP contains all<br />
in<strong>for</strong>mation of this knowledge as expressed in traditional<br />
handbook <strong>for</strong>m in data, table and diagram style. When a<br />
<strong>design</strong>er retrieves knowledge from repositories of the IPDP,<br />
he first downloads the STEP in<strong>for</strong>mation model of knowledge<br />
and, then employs the STEP pre/post processor,<br />
translating the STEP in<strong>for</strong>mation into a <strong>for</strong>m understood by<br />
the application <strong>plat<strong>for</strong>m</strong>. By this mean, the knowledge can<br />
be quickly and directly utilized in various <strong>product</strong> <strong>design</strong><br />
<strong>plat<strong>for</strong>m</strong>s.<br />
Taking the rolling bearing as an example, we note in<br />
Table 1 that the representation <strong>for</strong>m of knowledge (rolling<br />
bearing) in the repositories of IPDP is described with<br />
EXPRESS language. This knowledge model then is<br />
translated into a data dictionary model using the EXPRESS<br />
compiler (e.g. ST-Deeloper8.0 [11]). The data dictionary is<br />
a knowledge model that is not populated (e.g. a class of<br />
rolling bearing), meaning that the model attributions are<br />
not endued with exact values. The bearing’s code is in a<br />
binary <strong>for</strong>mat, which can be directly read by machine<br />
(<strong>for</strong> example, after being compiled, the data dictionary<br />
of the in<strong>for</strong>mation model rolling_bearing_support_schema
10<br />
Table 2<br />
Instanced in<strong>for</strong>mation model of rolling bearing 6215<br />
Instanced STEP in<strong>for</strong>mation model<br />
Format ¼ ‘rose_r3.0’<br />
ROSE_OIDS (<br />
(0 ¼ 0 £ 0000000000000000000000000000000000000000)<br />
(1 ¼ 0 £ 01000004D20000387AD825000000B30000000000))<br />
ROSE_DESIGN (RoseDesign<br />
name: bearing6215<br />
root: $<br />
keyword_table: $<br />
name_table: $<br />
schemas: (,1-1 . ListOfRoseDesign<br />
, “rolling_bearing_support_schema” . ))<br />
STEP_OBJECTS (<br />
(,1-0 . bearing6215<br />
style: “general ball bearing with deep groove”<br />
static_load: 66<br />
dynamic_load: 49.5<br />
weight: 1.171<br />
limited_speed_with_oil: 5600<br />
limited_speed_with_grease: 4500<br />
external_diameter: 130<br />
inner_diameter: 75<br />
width: 25<br />
install_damin: 0<br />
install_damax: 0<br />
install_rasmax: 0<br />
other_d2_inner: 0<br />
other_d2_external: 0<br />
other_rsmin: 0))<br />
is rolling_bearing_support_schema.rose). Populating the<br />
data dictionary means to endue an exact value into every<br />
parameter of the in<strong>for</strong>mation model. Table 2 shows the<br />
instanced in<strong>for</strong>mation model of the rolling bearing that<br />
populated the 6215 rolling bearing. Once the in<strong>for</strong>mation<br />
model is instanced, all parameters of the in<strong>for</strong>mation model<br />
are confirmed. The detailed structural data of the 6215<br />
rolling bearing is shown in Fig. 2. The 6215 STEP<br />
in<strong>for</strong>mation model, containing all of the in<strong>for</strong>mation stated<br />
in Fig. 2, is shown in Table 2. It shows that, by contrast with<br />
Fig. 2. Traditional handbook <strong>for</strong>m of rolling bearing 6215.<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15<br />
Fig. 3. Mechanism of C/S database.<br />
the traditional representation <strong>for</strong>m of knowledge, the STEP<br />
in<strong>for</strong>mation model is a digital <strong>for</strong>m of knowledge<br />
representation that can be understood with the <strong>product</strong><br />
<strong>design</strong> <strong>plat<strong>for</strong>m</strong> and directly imported into it. This <strong>for</strong>m of<br />
<strong>product</strong> <strong>design</strong> has the advantage of increasing the speed of<br />
knowledge acquisition and utilization.<br />
4. The knowledge storage and transference<br />
Because the IDPP is built over the <strong>Internet</strong>, its<br />
repositories should be constructed with a database that is<br />
of the C/S mechanism so that it is easy to achieve the<br />
connection with <strong>design</strong> <strong>plat<strong>for</strong>m</strong> within <strong>Internet</strong> environment.<br />
In this paper, a prototype of knowledge repository is<br />
built with an SQL server database (shown as Fig. 3). The<br />
connection between the SQL database and the IPDP server<br />
is achieved through the Open Database Connection<br />
(ODBC). Once a user logs into the repositories of the<br />
IPDP via <strong>Internet</strong> control, fills out the <strong>for</strong>ms and sends in the<br />
requests, then the IPDP server will start up the Active Server<br />
Pages (ASP) scripts and the CGI program corresponding to<br />
the request. ASP scripts can retrieve data from the SQL<br />
database through the database control ActiveX Data Object<br />
(ADO) inside the ASP, and return the results to the user. By<br />
this means, once the <strong>product</strong> <strong>design</strong>er has a need <strong>for</strong><br />
knowledge that does not exist in his <strong>design</strong> <strong>plat<strong>for</strong>m</strong>, he can<br />
log into the IPDP server, search and retrieve knowledge<br />
according to his demands and the constraints that that<br />
knowledge should meet.<br />
5. The method of knowledge search<br />
The common repositories of IPDP contain a great deal of<br />
knowledge that belongs to various disciplines and is<br />
distributed in various sites. When a <strong>design</strong>er needs to<br />
retrieve the knowledge from repositories of the IPDP so as<br />
to service <strong>for</strong> his <strong>product</strong> <strong>design</strong>, the efficiency of the<br />
method of knowledge search greatly affects the running<br />
per<strong>for</strong>mance of the IPDP. There<strong>for</strong>e, the IPDP should<br />
provide a high per<strong>for</strong>mance method <strong>for</strong> knowledge search<br />
so as to retrieve knowledge quickly, exactly and efficiently
Fig. 4. The flowchart of searching support part on function driven.<br />
from its repositories. To this purpose, a method of<br />
knowledge search <strong>based</strong> on a function driven concept and<br />
an Artificial Neural Networks (ANN) technique is proposed<br />
in this paper.<br />
5.1. Function driven<br />
Designing and developing a <strong>product</strong> is system engineering;<br />
it refers to multi-discipline knowledge. Even <strong>product</strong>s<br />
with a single function or certain phases within the<br />
development of a <strong>product</strong> require the support of various<br />
kinds of knowledge. A <strong>design</strong>er could not master all of the<br />
necessary knowledge, or at least could not reach an expert’s<br />
level in all those disciplines. Certainly, he could not employ<br />
a knowledge that he does not completely know. This means<br />
that much knowledge may be familiar to, but not mastered<br />
by the <strong>design</strong>er though he may know the function and<br />
constraints of this knowledge. Based on this viewpoint,<br />
the IPDP proposes a method of knowledge search. That is,<br />
the knowledge is searched according to the functions of the<br />
knowledge, here called Function Driven Knowledge Search<br />
(FDKS). With this method, when a <strong>design</strong>er needs a piece of<br />
knowledge he determines the function of the knowledge and<br />
the constraints that the knowledge requires. Then the IPDP<br />
searches <strong>for</strong> the knowledge in the repositories and retrieves<br />
it, matching the required functions and constraints. For<br />
example, suppose that a <strong>design</strong>er needs a rotative support<br />
part when he develops a <strong>product</strong>, and the part does not exist<br />
inthedatabaseofhis<strong>design</strong><strong>plat<strong>for</strong>m</strong>.Hewantstogain<br />
it from the outside repositories. Obviously, he does not<br />
know the details of the part. But he knows the functions<br />
of the part and the constraints that the part should meet.<br />
Since the IPDP provides the (FDKS) method, the<br />
<strong>design</strong>er only needs to provide the function and<br />
constraints that should be met. The IPDP then returns<br />
to the <strong>design</strong>er the resulting part that coincides with the<br />
user’s requirements. By this means, the <strong>design</strong>er can<br />
gain the knowledge that meets his <strong>design</strong> requirements<br />
even if he is not very familiar with it. The flowchart of<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15 11<br />
searching the support part <strong>based</strong> on function driven<br />
knowledge is shown in Fig. 4.<br />
5.2. Back propagation neural networks<br />
Knowledge search driven by function requires the user to<br />
determine the function and constraints that the knowledge<br />
should meet. In many situations, a <strong>product</strong> (knowledge) has<br />
several functions, and the same function can be achieved<br />
with various <strong>product</strong>s (knowledge). Moreover, the repositories<br />
have a great deal of knowledge and the mapping<br />
relationships between function and knowledge are implicit<br />
and nonlinear. In these situations, it is very difficult to<br />
construct all mapping relationships through general mapping<br />
(e.g. rule reasoning). Then how does the IPDP<br />
efficiently implement the mapping between knowledge<br />
and the function of knowledge? To solve this problem, an<br />
ANN method is applied to construct the mapping relationship<br />
between functions and knowledge in the IPDP system.<br />
In 1986, D.E. Rumelhart, J.L. Meclelland of MIT<br />
University put <strong>for</strong>ward a Back Propagation (BP) algorithm<br />
of multi-layers feed <strong>for</strong>ward ANN. The BP algorithm solved<br />
the modeling problem <strong>for</strong> layer-networks, and realized the<br />
ANN used in engineering applications. Until the present the<br />
synapses of ANN have almost reached all fields of<br />
engineering application, such as machine vision, class of<br />
decision [12], intelligent control and fault diagnosis [13].<br />
Since the feed <strong>for</strong>ward neural networks with two layers<br />
(containing a hidden layer) were applied in class and curve<br />
approximate fitting, a two-layer BP neural network with a<br />
momentum coefficient is adopted here to construct the<br />
mapping relationships between functions of knowledge and<br />
knowledge itself. The mathematical model of BP neural<br />
networks is shown as follows.<br />
Training samples are {ðXp; DpÞlp ¼ 1; 2; …; N}: Here, Xp<br />
is the Pth input value of training samples. Xp ¼<br />
ðx p p<br />
1 ; x2 ; …x p a Þ: Dp is the Pth ideal output value of training<br />
samples, Dp ¼ðd p p p<br />
1 ; d2 ; …dL Þ: Yp is the Pth actual output<br />
value, Yp ¼ðy p p p<br />
1 ; y2 ; …yL Þ:<br />
To the Pth group of training samples with N groups, the<br />
input and output models of the hidden layer are stated as<br />
Eq. (1). The input and output model of the output layer are<br />
stated as Eq. (2).<br />
net p<br />
XM<br />
j ¼ Wijx i¼0<br />
p<br />
i<br />
o p<br />
8<br />
><<br />
ð1Þ<br />
>:<br />
p<br />
j ¼ f netj 8<br />
><<br />
>:<br />
net p<br />
k<br />
y p<br />
k<br />
¼ XS<br />
j¼0<br />
¼ f net p<br />
k<br />
W jko p<br />
j<br />
Select Sigmoid function f ðuÞ ¼1=½1 þ expð2uÞŠ as the<br />
active function of the BP neural networks. The valve values<br />
ð2Þ
12<br />
Table 3<br />
Constraints of support-pairs with rotative movement<br />
Constraints Values<br />
are hidden in weights via Eqs. (3) and (4).<br />
x p<br />
0 ¼ 21:0; W0j ¼ u ð3Þ<br />
o p<br />
0 ¼ 21:0; W0k ¼ u ð4Þ<br />
The global error function as:<br />
E ¼ 1<br />
2N<br />
X N<br />
X L<br />
p¼1 k¼1<br />
d p<br />
k<br />
2 y p<br />
k<br />
2<br />
Weight-adjusted <strong>for</strong>mula as: DW ¼ 2hð›E=›WÞ<br />
Eq. (5) shows the calculating model of the adjusting<br />
weight in the output layer (h represents the learning ratio<br />
and a represents the momentum coefficient).<br />
s p<br />
k<br />
DW p<br />
jk<br />
¼ y p<br />
k<br />
1 2 y p<br />
k<br />
p p<br />
¼ hsk oj DW jk ¼ h XN<br />
p¼1<br />
s p p<br />
k oj d p<br />
k<br />
2 y p<br />
k<br />
W jkðt þ 1Þ ¼W jkðtÞþDW jkðtÞþaDW jkðt 2 1Þ<br />
The <strong>for</strong>mula of adjusting weights of the hidden layer is<br />
shown as Eq. (6)<br />
s p<br />
i<br />
DW p<br />
ij<br />
¼ o p<br />
j<br />
1 2 o p<br />
j<br />
p<br />
¼ hsj x;p i<br />
DW ij ¼ h XN<br />
p¼1<br />
s p p<br />
j xi X L<br />
k¼1<br />
1 0.5 0<br />
Lubrication (LU) Need Any None<br />
Speed (SP) Low Middle High<br />
Load (LD) Low Middle High<br />
Temperature (TP) Low General High<br />
Precision (PR) Low General High<br />
Structure (ST) None General Compact<br />
s p<br />
k W jk<br />
Fig. 5. The BP networks <strong>for</strong> searching support-parts knowledge.<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15<br />
ð5Þ<br />
ð6Þ<br />
Fig. 6. Input interface of constraints on Support-Parts with Rotative<br />
Movement in IPDP.<br />
W ijðt þ 1Þ ¼W ijðtÞþDW ijðtÞþaDW ijðt 2 1Þ<br />
In BP neural networks, the coefficients h and a should be<br />
greater than zero and less than one. The groups of training<br />
samples of BP neural networks should be three to ten times<br />
the number of weights [14].<br />
5.3. An example of knowledge search<br />
As seen earlier, the mathematical model of the ANN is<br />
stated. Here, how to apply the ANN model <strong>for</strong> searching and<br />
retrieving knowledge from the repositories of the IPDP is<br />
discussed. The illustration is <strong>based</strong> on rotative support parts<br />
stated in Section 5.1.<br />
Corresponding to the knowledge function support-parts<br />
with rotative movement shown in Fig. 4, the constraints are<br />
shown in Table 3. The knowledge matched with the function<br />
requirement of the rotative support is the rolling bearing, the<br />
journal bearing and the magnetic bearing. Here, setting the<br />
number of hidden nodes of BP networks at 4, the structure of<br />
Fig. 7. Output interface of result on Support-Parts with Rotative Movement<br />
in IPDP.
the BP network is shown as Fig. 5. The input parameters of<br />
the BP networks are the constraints shown in Table 3: their<br />
values are endued with 1, 0.5 or 0. If the output value of BP<br />
networks is greater than 0.8, it should be set at 1; if it is less<br />
than 0.2, it should be set at 0. Output values (1,0,0), (0,1,0)<br />
and (0,0,1) represent the rolling bearing, journal bearing and<br />
magnetic bearing, respectively.<br />
Combining the ANN and ASP technique, and migrating<br />
the trained ANN program to the <strong>Internet</strong> environment, the<br />
IPDP achieves the knowledge search via <strong>Internet</strong> control<br />
<strong>based</strong> on a function driven concept. Once a user wants to<br />
retrieve the knowledge needed from the repositories of the<br />
IPDP, he only needs to log into the servers of the IPDP and<br />
confine the function of knowledge and the constraints that<br />
the knowledge should meet (e.g. lubrication conditions<br />
needs, any or none; working load heavy, general or slight;<br />
working speed high, middle or low; etc.). Then the IPDP<br />
system will return the results, which coincide with the<br />
requirements to the user. The input interface of ‘support<br />
parts with rotative movement’ shows as Fig. 6, the output<br />
interface is shown as Fig. 7.<br />
6. Prototype of the IPDP<br />
The prototype of the IPDP is introduced in this section;<br />
its structure is stated as Section 2. The client side of the<br />
prototype system adopts Solidworks and VCþþ programs<br />
(<strong>design</strong> <strong>plat<strong>for</strong>m</strong>) used <strong>for</strong> the structure <strong>design</strong> and<br />
per<strong>for</strong>mance analysis of <strong>product</strong>s. The browser <strong>for</strong> the<br />
client side employs a general WWW browser (e.g. MS<br />
<strong>Internet</strong> Explorer, Netscape, etc). The pre/post processor of<br />
the prototype, which translates data between STEP<br />
in<strong>for</strong>mation models and <strong>design</strong> <strong>plat<strong>for</strong>m</strong>s, employs STEP<br />
Developer 7.0, developed by STEP Tools Inc. The<br />
repositories of the server side are built with the SQL server<br />
database. The servers of the IPDP achieve communication<br />
with the database through ADO and ODBC. The servers<br />
were constructed upon a Peer Web Server in a Windows<br />
NT4.0 workstation environment. The structure diagram of<br />
the prototype system is shown as Fig. 8. Fig. 9 shows a piece<br />
of knowledge searched from certain common repository of<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15 13<br />
Fig. 8. The prototype of <strong>Internet</strong>-<strong>based</strong> <strong>intensive</strong> <strong>product</strong> <strong>design</strong> <strong>plat<strong>for</strong>m</strong>.<br />
Fig. 9. A piece of searched knowledge (rolling bearing) from repository of<br />
IPDP.<br />
IPDP. Fig. 10 indicates that importing the searched<br />
knowledge into <strong>design</strong> <strong>plat<strong>for</strong>m</strong> (SolidWorks) to aid the<br />
structure <strong>design</strong> of rotor-bearing system.<br />
The knowledge is represented in standard and neutral<br />
<strong>for</strong>m, and its store and transfer are achieved successfully<br />
over the <strong>Internet</strong>, but these are only the precondition to the<br />
implementation of the IPDP servicing <strong>for</strong> <strong>product</strong> <strong>design</strong>.<br />
Ultimately, the knowledge retrieved from the repositories of<br />
Fig. 10. The structure <strong>design</strong> of rotor system using searched knowledge.
14<br />
Fig. 11. The flowchart of organization, transfer, and implementation of in<strong>for</strong>mation models in the IPDP prototype.<br />
the IPDP must be imported into a <strong>design</strong> <strong>plat<strong>for</strong>m</strong> to support<br />
the <strong>product</strong> <strong>design</strong>, so it should be utilized and understood in<br />
an exact <strong>design</strong> <strong>plat<strong>for</strong>m</strong>. There<strong>for</strong>e, one must consider how<br />
the <strong>design</strong> <strong>plat<strong>for</strong>m</strong> is to understand knowledge with neutral<br />
<strong>for</strong>ms (i.e. how to achieve the knowledge downloaded from<br />
the IPDP but utilized in a user application <strong>plat<strong>for</strong>m</strong>). Here,<br />
an implementation flowchart on how to utilize the knowledge<br />
downloaded from the IPDP into a VCþþ 6.0 program<br />
(<strong>design</strong> <strong>plat<strong>for</strong>m</strong>) is stated. Fig. 11 shows the diagram of the<br />
organization, transference and implementation of knowledge.<br />
The implementation manner of in<strong>for</strong>mation models<br />
(knowledge) is concretely expounded as follows.<br />
The in<strong>for</strong>mation models (knowledge) as expressed <strong>based</strong><br />
on STEP, were compiled into a data dictionary and Cþþ<br />
classes using the STEP Developer 8.0. The data dictionary is<br />
the compiled binary <strong>for</strong>mat of in<strong>for</strong>mation models. Under a<br />
VCþþ situation, the in<strong>for</strong>mation models are instanced; and<br />
the instanced in<strong>for</strong>mation model and data dictionary is stored<br />
in the SQL server database. The instanced in<strong>for</strong>mation models<br />
contain all in<strong>for</strong>mation of the traditional <strong>for</strong>m of knowledge<br />
such as structure size, materials and characteristic parameters.<br />
The servers are connected with the SQL database via the ASP<br />
and ODBC. Users can log into the server of the IPDP, search<br />
the knowledge and download the STEP in<strong>for</strong>mation model of<br />
the knowledge. Once the downloaded STEP in<strong>for</strong>mation<br />
models are processed with STEP Developer 8.0, they can be<br />
directly used in the VCþþ programs (a <strong>design</strong> <strong>plat<strong>for</strong>m</strong>).<br />
7. Conclusions and future work<br />
Upon analyzing the limitations of the commercial<br />
S. Zhou et al. / Knowledge-Based Systems 16 (2003) 7–15<br />
CAD and requirements of <strong>product</strong> <strong>design</strong> on knowledge<br />
resource, a framework of the IPEP with client/server<br />
structure, which used to integrate traditional <strong>product</strong><br />
<strong>design</strong> <strong>plat<strong>for</strong>m</strong> and distributive knowledge repositories,<br />
is developed. The knowledge acquisition and transference<br />
is achieved over the <strong>Internet</strong>. The knowledge is<br />
represented <strong>based</strong> on the STEP standard. And the<br />
prototype of IPDP is developed successfully. The<br />
research provides a scheme to intensify the <strong>design</strong><br />
ability of traditional <strong>product</strong> <strong>design</strong> <strong>plat<strong>for</strong>m</strong>, increase<br />
the speed of knowledge acquisition, and shorten the<br />
cycle of <strong>product</strong> development.<br />
Based on the ANN and the function driven concept,<br />
a new method (FDKS) <strong>for</strong> knowledge search is put<br />
<strong>for</strong>ward. Superior to rule reasoning, the ANN can solve<br />
complex mapping between input and output and the<br />
FDKS method excellently implements the non-linear<br />
mapping between function of knowledge and knowledge<br />
itself.<br />
The success of the developed prototype illustrates<br />
that the mechanism of the IPDP is right and feasible.<br />
Certainly, there are many works that need further<br />
refinement be<strong>for</strong>e the engineering <strong>design</strong> system runs<br />
perfectly. For instance, the knowledge in repositories of<br />
the IPDP must be further enriched. In addition, the<br />
prototype stated in this paper is only used <strong>for</strong> acquiring<br />
and utilizing knowledge remotely. The methods of<br />
representation, storage and transference of knowledge<br />
have a commonality. But the application of knowledge<br />
depends on various <strong>design</strong> <strong>plat<strong>for</strong>m</strong>s. There<strong>for</strong>e, the<br />
STEP pre/post processor of the commercial CAD<br />
<strong>plat<strong>for</strong>m</strong> needs to be considered in next-step works.
Acknowledgments<br />
This research was partially supported by an RGC project<br />
of Hong Kong under grant No. 9350007 and National<br />
Natural Science Foundation of China under the grant No.<br />
59990472.<br />
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layer of influence diagrams in class of decision analysis, System<br />
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[14] J.K. Kim, Neural network-<strong>based</strong> decision class analysis <strong>for</strong> building<br />
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Shouqin Zhou was born in 1973. Currently, he works in the<br />
Department of Manufacturing Engineering and Engineering Management,<br />
City University of Hong Kong. He obtained the PhD degree in<br />
April 2001, and received M.Sc. in 1997, B.A. in 1994. His current<br />
research interests include distributed knowledge in<strong>for</strong>mation system <strong>for</strong><br />
<strong>product</strong> <strong>design</strong>; the standard <strong>for</strong> the exchange of <strong>product</strong> model data;<br />
<strong>Internet</strong> networks techniques, supply chain management, expert<br />
system, etc.<br />
Kwai-Sang Chin is an Associate Professor in the Department of<br />
Manufacturing Engineering and Engineering Management, City<br />
University of Hong Kong. Be<strong>for</strong>e joining the university, Dr Chin has<br />
more than ten years of experience in the manufacturing industry. He is a<br />
Chartered Engineer in the UK and Registered Professional Engineer in<br />
Hong Kong. Dr Chin is a fellow of Hong Kong Society <strong>for</strong> Quality,<br />
senior members of American Society <strong>for</strong> Quality (ASQ), Institute of<br />
Industrial Engineers (IIE) and Society of Manufacturing Engineers<br />
(SME), USA. His current research interests are new <strong>product</strong><br />
development strategies in the <strong>Internet</strong> Age, quality management<br />
strategies beyond ISO 9000 <strong>for</strong> Hong Kong and China, and the use<br />
of Artificial Intelligence technologies in <strong>product</strong> <strong>design</strong>.<br />
Prasad K.D.V. Yarlagadda is the Director of the Mfg. Systems Engg.<br />
Research Conc., School of Mech., Mfg., & Medical Eng., Queensland<br />
University of Technology, Australia.