Applying Ontology-based Knowledge Methodology in Product

Innovative Collaborative Conceptual Design Framework

Janus S. Liang

National Taiwan Normal University, 162 Heping East Road Section 1, 10610, Taipei, Taiwan, Taiwan

Keywords: Product Innovative Design Ontology, Function Representation, Collaborative Design, Semantic Web.

Abstract: In this research, an ontology-based knowledge methodology is utilized in distributed design environment. It

is composed of a regular restrictions-based method for expressing the aspired functions, a field-independent

method for constructing functional knowledge of given criterion solutions, and a heterogeneous-substance-

search method for combining given criterion solutions to reach the aspired functions. This research presents

that the capability of function design ontology (FDO) to be inferred can acquire the design intentions by an

exposition with a real toy product. Finally, this research proposes a novel framework of information sharing

in product innovative design and a design viewer for collaboration in product generation.

1 INTRODUCTION

To develop a sturdy function-oriented model needs a

comprehension of component geometry and its

substantial outcomes. The morphological

characteristics are also importance except the

geometric properties. They are results of the

principles substantial processes and of the design

intents. However, present solid modeling software

offer incomplete product descriptions and are not

able to perform in the light of the semantic content

of the models (Zhang, 2010). Furthermore, the

semantic web sustains combined and similar entry to

services and message sources as well as to

intelligent utilizations by the definite expression of

the semantics involved in an ontology. While

designer turns into increasingly knowledge-intensive

and collaborative, a concurrent crucial for

computational platforms to enable conceptual

product generation, by effectively supporting the

regular expression, recovery, and reuse of product

information will be achieved. (Kissel et al., 2012)

This research addresses a collaborative

knowledge-based product innovative conceptual

design mode that function design ontology (FDO)

performs in a regular, definite description of a

shared conceptualization of product design

modeling. The FDO, in which is derived from AsD

ontology (Kim et al., 2006), makes design

knowledge accurate and machine-interpretable. In

this research, implicit design constraints (including

criterion solutions) are definitely expressed using

Semantic Web Rule Language (SWRL) and Web

Ontology Language (OWL). A meta-pattern,

function interconnection pattern (FIP), which was

initially constructed to acquire the relations in

function engineering, is promoted utilizing the

ontology techniques to meet the requirements in

collaborative engineering. The implicit conditions of

function engineering relations are expressed by

utilizing SWRL norms and OWL triads. The FDO

also acquires a design rationale, including the

function intention, assembly, and spacial relations.

This work generates an information sharing

circumstance in innovative conceptual design that

can inquire FDO messages selectively.

2 RELATED WORKS

Existing computer-aided conceptual design systems

can be classified as reuse-oriented systems and

creation-oriented systems. The former often aim at

modeling the product knowledge of a total

engineering system for guiding subsequent design of

similar systems. For instances, the FBS modeler

employs the Function-Behavior-State approach to

model the function-related knowledge of existing

criterion solutions for reuse (Cabrera et al., 2009).

Based on an existing functional taxonomy, several

studies have developed component taxonomy for

archiving, searching and reusing component

324

Liang J..

Applying Ontology-based Knowledge Methodology in Product Innovative Collaborative Conceptual Design Framework.

DOI: 10.5220/0004616603240330

In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2013), pages 324-330

ISBN: 978-989-8565-81-5

 2013 SCITEPRESS (Science and Technology Publications, Lda.)

knowledge (Joshi and Pathak, 2011). The latter

generates a criterion solution for a desired function

through recalling basic components from its

component library and synthesizing them together

for a desired function. Based on the fact that systems

in different disciplines can be represented with

similar graphs on the mathematical meta-level, the

infused design approach employs multiple graph

representations to identify suitable problem-solving

methods from related disciplines for human

designers. However, it cannot integrate criterion

solutions in multiple disciplines into one system.

The above literature analysis discloses there are still

no suitable computer-aided conceptual design

systems for fulfilling innovative conceptual design

in a collaborative environment.

Observing the product from the constructional

point of view gives a product break down structure

(product, assembly, subassembly, component, and

feature) each of which requires be designing and

therefore calling as product design units (PDEs). A

PDE at component building level is a reusable

design information unit representing a potential

solution means for a function requirement. Rehman

and Yan (2003) proposed a generic function to PDE

mapping process model for supporting decision

making in the conceptual design stage. Baxter et al.

(2007) categorized existing work in which the

design process has a relationship to design

information management or design reuse mainly

into: (i) Design process with the information

management at its core; (ii) Integrating design

rationale process; (iii) Design methodology as

design process description or management method;

(iv) Design information capture and representation

through design processes. Panchal et al. (2006)

developed an approach for the integrated design of

materials, products, and design processes which was

based on the use of reusable interaction patterns to

model design processes, and the consideration of

design process decisions using the value of

information metrics. It was shown that the integrated

design of materials and products can be carried out

more efficiently by considering the design of design

processes. However, their style still has implicit

restraints and relations that cannot be analyzed by a

calculator in a semantic web circumstance. This

research will develop the FDO style using ontology

technology. The FDO will definitely express

conceptual design restraints and the calculator will

can reason the surplus implicit ones. Meanwhile, the

function interconnection pattern (FIP) will involve

the motion characteristics in product innovative

conceptual design except the static assemble

conditions.

3 SYSTEMATIC

REPRESENATION AND

SYNTHESIS APPROACH

A HeOS-based (Heterogeneous Object Search)

synthesis method is generated in order to accomplish

ICD in collaborative environment. The agent

concept (Russel and Norvig, 2009) is utilized to

illustrate the HeOS-based synthesis method. It is

supposed that there is a SCD (Smart Conceptual

Design) agent that involved all criterion solutions in

its knowledge base. For SCD agent, the given

criterion solutions can be considered as its behaviour

devices for converting import flows, the import

flow(s) derived from an aspired function can be its

original condition, and its export flow can be the

target situation. This agent can sense its condition

automatically, and can choose proper criterion

solutions from its knowledge base to perform it,

until the target conditions is achieved. The condition

of SCD agent consists of the flows that SCD agent

can detect. Besides, each flow is also expressed with

a name of flow, along with a group of attribute-

values. Following the attribute restraints on the

import flow(s), SCD agent can create original

conditional flow(s) by integrating whole probable

values of each attribute completely, and place them

into its condition. After a given criterion solution is

specified to perform a conditional flow, some export

flows can then be created that are also place into the

condition for farther design synthesis.

After a qualified criterion solution has been

recognized, SCD agent will then decide how it

performs the present conditional flow, where the

main attention is what flow(s) the criterion solution

will export. The functional knowledge of the

criterion solution is utilized to predict the export

flow(s). In a state space of heterogeneous substance,

what SCD agent should predict originally is the

name of the export flow. Based on the import-export

flow name pair(s) of a given criterion solution, SCD

agent knows the name of the export flow. Then SCD

agent has to decide the value scopes of the attributes

for the export flow. This procedure includes two

portions. One is to decide the value scopes of the

attributes in accordance with the attribute-mapping

norms of the criterion solution. For instance, when

the criterion solution Crank-slider mechanism is

utilized to perform an import “Angular_velocity”

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flow with its attribute Axial_orientation set as Z, the

attribute orientation of the export “Linear_velocity”

flow can then be predicted as either X or Y. Another

is to decide the value ranges of the attributes that are

not restricted by the attribute-mapping rules, using

the attribute constraints of the selected criterion

solution on its export flow. Eventually, SCD agent

creates all possible export flows, using the value

scope determined for each attribute. This can be

done by extracting each value decided for each

attribute and combining them together in an

thorough way. This action process can be shown

with an example shown in Figure 1, where the

allowable value scopes that SCD agent has

determined for the attribute of the export flow are

shown in the right side. Based on these allowable

values, SCD agent generates two probable export

flows by means of a thorough conjucntion process,

i.e. “Linear_velocity {Stability: variable;

Orientation: X; Direction: reciprocating;

Motionstate: continuous}” and “Linear_velocity

{Stability: variable; Orientation: Y; Direction:

reciprocating; Motionstate: continuous}”.

Figure 1: An example of SCD agent’s action process.

In order that SCD agent can investigate in

collaborative solution environment for discovering

the conjunctions of novel and potential criterion

solution, the thorough search approach is utilized to

generate the automated ICD synthesis algorithm.

The process of design synthesis can then be

implemented after a designer imports an aspired

function with the restraints on the import and export

flows. Besides, it is important that a designer takes

care of the most potential criterion solution selected

for refining farther design after various

combinatorial criterion solutions are exported. If

SCD agent cannot create a potential criterion

solution with the assigned the maximal depth for

searching, the designer may add the maximal depth

for searching and re-begin the process of design

synthesis.

Suppose a designer intends to develop a toy dog

that can shake its head and tail after turning on the

switch. A solar energy is chosen for driving the toy.

Utilizing the proposed method of functional

expression, the import flow, i.e. the solar light, can

be expressed as “Lighting_energy {Stability:

constant || variable; Motionstate: continuous; Type:

Hot_light}”, while the export flow, i.e. the head and

tail-shaking action of the toy, can be expressed as

“Angular_velocity {Stability: variable;

Axial_orienation: X || Y; Direction: reciprocating;

Motionstate: continuous}”. To illustrate this

example, several criterion solutions are chosen to

create the criterion solution knowledge base, which

are Crank_slider, Spur_gear_pair, Crank_rocker,

Rack_pinion, Transformer, Solar_array, AC_motor,

DC_motor, Electrical_inverter, and

Light_emitting_diode. Meanwhile, the process of

design synthesis is depicted below: (1) SCD agent

converts the restraints on the import flow into some

detailed circumstance. Consequently, two original

environmental flows are generated. (2) SCD agent

starts to perceive its circumstance. The first

conditional flow perceived is the flow

“Lighting_energy {Stability: constant; Motionstate:

continuous; Type: Hot_light}”. SCD agent then

explores the restraints of the given criterion

solutions on the import flows to discover qualified

criterion solutions. Hence, the criterion solution

Solar_array is recognized as a qualified one. (3)

SCD agent applies the functional knowledge of the

recognized criterion solution to perform the present

flow. Based on its name pair of import-export flow,

SCD agent finds that the criterion solution will

export an “Electrical_current” flow; in the light of

the relevant attribute-corresponding norms and the

attribute restraints on the export flow, then SCD

agent can decide the value scopes of the attributes

for this export flow, and then create an export flow,

“Electrical_current {Stability: constant; Motionstate:

continuous; Direction: positive; Type:

Direct_current}”, which is also place into its

condition. Subsequently, SCD agent keeps on

detecting its condition until whole conditional flows

have been searched. When a flow is detected as

unsearched, it will then discover suitable criterion

solutions to perform it, and the recently-generated

export flows will be increased to its environment. (4)

when the search process terminates, SCD agent then

searches for the environmental flows that can meet

the restraints on the export flow (goal), and get

whole relevant flows by a backtracking process,

with a effect of some conjunctions of given criterion

solutions. For instance, SCD agent will then get the

relevant flows and bind the corresponding criterion

solutions as a combinatorial criterion solution when

the flow “Angular_velocity {Stability: variable;

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Motionstate: continuous; Axial_orientation: X;

Direction: Reciproating}”. The combinatorial

criterion solution is listed “Solar_array →

DC_motor → Crank_rocker”.

The above design project shows that SCD agent

can create combinatorial criterion solutions for a

aspired function by integrating given criterion

solutions from diverse disciplines into a

collaborative environment. For instance, when the

maximal depth for searching is set as four, a

combinatorial criterion solution, “Solar_array →

Electrical_inverter → AC_motor → Crank_rocker”,

can be created, which is included criterion solutions

from diverse fields, e.g. mechanical engineering,

electrical engineering, electronic engineering, etc.

Furthermore, the SCD agent cannot only determine

whether various criterion solutions meet each other

in flow names, but also can verify if they are

congenial regarding the elaborated properties.

4 FRAMEWORK OF

INNOVATIVE CONCEPTUAL

DESIGN

4.1 Function Relation Model

To fulfill the desired functions, the mechanism

design portion also has to be involved in the

innovative conceptual design system except the

above mentioned approaches. Thus, a FIP is

generated in this research. It is a meta-pattern with

XML format, developed by utilization of the FDO

style. All geometric elements in the FIP are

connected to a relevant solid model, namely, the

output of the style is an XML file deriving from

geometric elements in a CAD model. By utilization

of FDO style, a designer can assign linking modes,

linking conditions, and spacial relations between

components in a CAD circumstance. Figure 2

illustrates a Unified Modeling Language for

showing a FIP static structure. Function has

“part_of” relations with the two features (assembly

and component), and component has “part_of”

relations with the feature form. The feature assembly

is crucial factor for realizing the function intent. It

involves the characteristics below: coupler,

matching, degree of freedom, and material. The

FDO style that acquires motion, assembly, and

linking relations of a product, is included several

aspects: extraction of feature matching, description

of spacial relation, extraction and generation of

feature coupler, generation of feature assembly as

well as relation extraction of function engineering.

Figure 2: The diagram of function interconnection

pattern – UML format.

4.2 Ontology-based Function Design

In this framework of ontology-based function,

product properties, assembly, function, and linking

procedures are generated in an ontology. Different

collaborative designers can entry the function

messages by utilizing a semantic inquiry while

applying collaborative design tools (called eCol-

tools). The FDO has been generated based on a FIP,

which was depicted in Section 4.1; the ontology-

based FIP acts as a meta-pattern that provides a

connection between CAD models and function

relations. Besides, the FDO ontology also offers

facts by utilization of a reasoning module.

In innovative conceptual design, OWL and

SWRL are utilized for establishing relationships.

This study indicates that SWRL principles can be

inferred to supply semantic inquiries and

information requirements in a collaborative ICD

circumstance. To develop the FDO and principles,

Protégé SWRL editor is applied for this research.

There are three types of relations, spacial relations,

and linking relations expressed in OWL and SWRL.

First of all, the relations between a feature form and

a feature component are expressed the “Inhere”. The

Inhere relations infer two constraints. The inferred

constraints can be transformed to two alleged

conditions.

Meanwhile, the relations among form features

are expressed the “Inter-Conjunction”. The

constraint (Rc

) means the relation between two

form features in the hierarchy of form feature. The

generated SWRL rules are used to add new facts and

utilized in a fact-adding mode only in this research.

Finally, the relations between form features that

inhere to different components are defined the

“linking”. The implied constraints are represented in

SWRL rules.

The designer’s initial intention forced on

function design can be investigated through a

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definite linking manner and the planned degree of

freedom. For instance, if designers intend to

perpetually bind two components to move

simultaneously, they specify spacial relations to

fasten them. A designer concerns a fastened coupler

and assigns a screwing utilization for a linking

manner, then the degree of freedom consistent with

the screwing utilization can be reasoned by applying

the ontology inferring ability, and utilized to check if

this screwing utilization will meet the designer’s

intention on the function. The SWRL principles to

express spacial relations, degree of freedom and

inference instances are depicted (Kim et al., 2006):

(i) aligned spacial relation: Two components that

aligned between collinear lines along the direction y,

have degree of freedom of {lin_y :: rot_y}. (ii)

against spacial relation: Two components that have

against spacial relation between planar surface along

the direction x, have degree of freedom of {plan_x ::

rot_x} - in other words, plane degree of freedom

along x-direction of the coordinate of the instance

component and rotational degree of freedom within

its own coordinate system (x-direction). (iii)

decrease in degree of freedom: When multiple

spacial relations are assigned, the result of

interaction of degree of freedom should be decided

to realize the resultant degree of freedom. (iv) bolt

with nut or rivet: If a component is joined by more

than on bolt with nut or rivet, the component has

restricted degree of freedom.

5 THE FRAMEWORK OF

DESIGN INFORMATION

SHARING

A novel framework of design information sharing

and design viewer generated by utilizing the

standard widget toolkit (SWT), Java, and the Jena

ontology application program interface. The design

viewer delivers just an essential group of design

information in a collaborative environment and

hence it conquers the obstructions of present

conceptual design systems that designers have to

find either with finite sustains of system or manually

to find appropriate design information. As an

instance, let us consider the scenario that tail

mechanism of toy dog is being concurrently

generated by multiple collaborators in distributed

environment.

In the distributed framework, the function

ontology is corresponded to the FIP, and the FIP is

definitely connected to a consistent solid model.

Figure 3 shows a structure for the information

sharing in conceptual design. First of all, product

relationships, i.e. function, are acquired from the

function design models that are created by different

CAD tools, and the consistent FIPs are created. This

FDO module executes the selection and FIP creation

as the FDO generator. The FIP is corresponded to

the consistent CAD model. The FDO is created by

utilizing an ontology tool, e.g. Protégé, and the OFM

generator creates an ontology-based function model

(OFM) that an ontological expression of FIP, and

executes the corresponding with the FIP messages.

The OFM generator converts the normalized

contents in FIP to OFM, when reasoning the pre-

constructed ontology. OFM strictly follows the

ontological rules in spite of the FIP created from

different CAD systems may be heterogeneous. The

inferring unit performs the rules in FDO, and puts

recently detected facts to the OFM base. The FDO

viewer treats embedded inquiries and customized

inquiries by utilizing a query unit based on the

OFM. The unit spread the outcomes through the

ontology and then transmits the outcomes to the

conceptual design browsers.

Figure 3: The framework of conceptual design information

sharing.

6 IMPLEMENTATION OF

SYSTEM

In this framework, the elements in the ontology are

persistently connected to a corresponding solid

model by FIP, which is format and application

independent. In this way, the designers do not need

to know a specific CAD format, and loss of

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information is relatively low since design

information is represented explicitly in the FRM.

Figure 4 shows the interface of conceptual design

browser, designers can search for product models

that contain relevant design information by using the

interface. There are several views of the product

information provided on the browser: a hierarchical

view of the ontology classes, a product geometry

view (assemble/exploding condition), and view of a

model data structure and XML structure. Through

browsing the ranking system, a designer can decide

that classes are definitely expressed in the model and

their sub-class relations. The XML view offers the

designer the chance to examine the structure in that

the model will be delivered from one system to

another. Meanwhile, the viewer of conceptual design

explores for relative elements by utilizing keyword

that investigates class structure and file name of the

relevant ontology model. The relevant model comes

back files that involve the particular design

messages if the search rules are met. Besides, other

search rules are also shown to make supplementary

searches on similar items for designer. For instance,

if a designer searches for linkage assembly that

involves screwing information displayed in Figure 4,

other search rules such as riveting, welding, or

adhesive bonding may be returned by utilizing the

ontology model because they are also joining

methods, which is a result of a semantic query.

Figure 4: Screen snapshot of SICD system – FDO viewing

browser.

7 CONCLUSIONS

In this research, the proposed approach for ICD

system paves a path for designers to integrate

criterion solutions from various disciplines into a

collaborative framework for fulfilling a desired

function. It is mainly composed of a formal

approach for representing a desired function, a

domain-independent approach for representing

functional knowledge of known criterion solutions,

and a HeOS-based synthesis approach for automated

ICD system in collaborative environment.

Furthermore, the author has also proposed a

collaborative ICD structure sustained by an

ontology-based knowledge methodology. The

generation of a FDO mentions the requirement that

product design has for high-level semantic

modeling. High-level semantics and a normailization

of function notions as well as relationships among

those concepts give the calculator the capability to

infer messages for the instances of particular

function model. In this research, function knowledge

has been categorized into a ranking system of

function concepts. They inserted in conceptual

design have been defined utilizing particular names

and hence have generated a normal vocabulary to

depict functions. This is essential for concerted

function design that in various disciplines

symbolically include. This research obtains most

benefits of OWL and SWRL techniques to express

complex relationships that are spread among form

properties and components. Because the restrictions

have been normalized, they can be explained and

kept in a normal way in the collaboration period.

The FDO and viewer can be applied in different

activities regarding the collaboration in product

design modeling.

ACKNOWLEDGEMENTS

This research is supported in part by the National

Science Council in Taiwan under contract number

NSC 101-2511-S-003-059-MY2 and NSC 100-

2511-S-003-068-MY2.

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