DEVELOPMENT OF FEATURE LIBRARY FOR
A PROCESS PLANNING SYSTEM
Koichi ANDO*1, Hendry MULJADI*2, Hideaki TAKEDA*2, Makoto OGAWA *1*1Shibaura Institute of Technology, Japan*2National Institute of Informatics, Japan

ABSTRACT
For the generation of process plans of a part type based on the manufacturing features
recognized from the product design information, a feature library where manufacturing features canrefer to their corresponding manufacturing information is needed. In this paper, we describe thecreation of ontology of manufacturing features for the development of a feature library. The creationof manufacturing features ontology is done by considering the designer’s intention described in thefunctional data of the face elements that construct the features. The goal of this ontology creation is
to make the feature library be useful for the automated extraction of proper manufacturing
information for the generation of process plans.
1. INTRODUCTION
In a manufacturing stage such as a Flexible Manufacturing System (FMS) line where multiple
part types are machined, dynamic changes such as increased production, part type changes, machine
breakdowns etc are ordinary occurrences. To deal with these dynamic changes, we presupposed theneed to integrate design, manufacturing and scheduling activities. Our research puts its goal in thegeneration of a CAPP system that can integrate process planning, scheduling and manufacturing
activities (Sakurai et al. 2000). The CAPP system is named the Feature-Based Flexible Process
Planning System (FBFPPS). Figure 1 shows the overview of the proposed FBFPPS. The system
consists of 3 steps.
Step 1: manufacturing features recognition from the product design data.
Step 2: generation of multiple process plans of a part type based on the recognized manufacturingfeatures.
Step 3: determination of optimal set of process plans for product mix.
FBFPPS

DesignActivities
CAD
data

Step 1:
Manufacturing
FeatureRecognition

Step 2:
Generationof Multiple
Process
Plans of aPart Type

Step 3:
Determinationof Optimal
Sets ofProcess
Plans for
Product Mix

S
C
H
E
D
U
L
I
N
G

Shop
Floor
Monitoring

Fig. 1 Overview of the proposed Feature-Based Flexible Process Planning System
Generation of multiple process plans of a part type in Step 2 of the FBFPPS is considered toprovide alternative plans in the determination of optimal sets of process plans for product mix in thescheduling stage. During the shop floor monitoring, re-scheduling may occur to handle the dynamicchanges in the manufacturing stage. For re-scheduling, a new optimal set of process plans for thepresent shop floor or production planning condition may be required from the Step 3 of the
FBFPPS.
In order to bring the proposed FBFPPS to realization, we have proposed a manufacturing

feature recognizer that can lead to the generation of multiple process plans (Muljadi et al. 2002).
For the development of the manufacturing feature recognizer, we implemented Super Relation
Graph (SRG) Method (Kao et al. 1995). We did some modification to the SRG Method andproposed the Modified SRG Method. So, the manufacturing feature recognizer uses the Modified
SRG Method to extract manufacturing features from the product design information. We havefurther modified the Modified SRG Method, and proposed the Extended SRG Method that is able toextract not only single depression features, but also protrusion and compound features (Muljadi et al.
2003). Protrusion and compound features can also be extracted by the Extended SRG Method sincethese features can be represented by the Extended SRG. The Extended SRG representations of
manufacturing features are stored in the feature library.
For the development of the feature library for the FBFPPS, we collect and store manufacturingfeatures, their corresponding Extended SRG representations and the manufacturing informationneeded to create the shape of the manufacturing features. However, we found that instances of same
type of manufacturing features may require different manufacturing methods. Thus, it is possible tocreate subclasses to the manufacturing feature types based on the required manufacturing methods
to create the manufacturing features, so that each instances of the subclass will have the same
possible manufacturing methods.
In this paper, for the development of the feature library, we propose the creation of ontology of
manufacturing features by considering the designer’s intention described in the functional data of
the face elements that construct the features. The goal of this ontology creation is to make thefeature library be useful for the extraction of proper manufacturing information to create the
manufacturing features that are extracted by the Extended SRG Method.
The structure of this paper is as follows. In order to make this paper self-contained, theExtended SRG Method is described briefly in Section 2. In Section 3, we discuss the creation of
ontology of manufacturing features for the feature library. In Section 4, a case study is used to show
the validity of the proposed manufacturing features ontology to enable feature library to extract
proper manufacturing information from the extracted manufacturing features.
2. EXTENDED SUPER RELATION GRAPH METHODIn Extended SRG Method, feature extraction is made possible by using three relations between
faces, super-concavity relation, face-to-face relation and convexity relation, and also by using theedge elements which construct the features. Super-concavity relation, face-to-face relation andconvexity relation can be defined by Eq.1, Eq.2 and Eq.3 respectively.
++
n f+i .n f+j ≠ -1; f i ∩S(f j ) ≠ ∅ and f j ∩S(f i ) ≠ ∅(1)
n f+i .n f+j = -1; f i ⊂ S(f j )+and

f j ⊂S(f i ) +n f+i ・n f+j ≠ 1; n f+i ・n f+j ≠ -1; f i ∩S(f j ) |+| =Ø; f j ∩S(f i ) |+| =Ø;E fi ∩E f j ≠ Ø

(2)
(3)

where n f+i is the positive face normal of face f i (figure 2(a)), and the strict positive half space ofTface f i , S(f i ) |+| = { x | n f+i x > k } is the positive half space which exclude the embedding plane ofTface f i , P(f i ) = { x | n f+i x = k } (figure 2(b),(c)), E fi is the set of edges of face f i . n f+j , S(f j ) + andE f j are defined similarly as above.
Figure 3 and figure 4 show the Extended SRG representation of a stepped-hole feature andrectangular boss feature respectively. A node with one circle in the Extended SRG corresponds to aplain face of the feature. A double circle node corresponds to a curve face. Dotted links are used torepresent face-to-face relations. Solid links are used to represent super-concavity relations andface-to-face relations. To distinguish these two relations, 0 is used as the attribute of the solid links
to represent super-concavity relations and 1 to represent convexity relations. Solid links with noattribute are used to represent the face-edge relations. Plain edges are represented by e n and curveedges are represented by e +n . The Extended SRG Method has the ability to extract not only single
depression features, but also protrusion and compound features, since protrusion and compoundfeatures can have their Extended SRG representations too.
In the development of feature library, a collection of manufacturing feature types, theircorresponding Extended SRG representations and the possible manufacturing information to create
the manufacturing features is stored. In the next section, we discuss the creation of manufacturingfeatures ontology to make the feature library be useful for the extraction of proper manufacturing
information of manufacturing features extracted by Extended SRG Method.
fi

S(f i )

P(f i )(a)Positive Face Normal(b)The Embedding Plane of f i (c)Strict Positive Half Space of f iof Face f i
Fig. 2 Explanation of terms used in Extended SRG Method
e3 e+1 e+7

e+5

e2

e4

+

2 0
1
2
e+6

4

5

e10

+

3 1

0

1

3

1 4
5

e+1 e2 e+3 e4 e+5 e6+ e+7 e8 e+9 e10 e11+ e+12

e11 e8e+12
e+9
Fig.3 Stepped-hole feature and its Extended SRG representation
e1

e5

2

e6

e4

e2
１
3
e9

1

2
5

4
e11

e16
e12 e8

e3

0
0
0

1

1

1
3

4 1
0

5

e1 e2 e3 e4 e5 e6 e7 e8 e9 e10 e11 e12 e13 e14 e15 e16e13e10
e14 e7 e15
Fig.4 Rectangular Boss feature and its Extended SRG representation

3. DEVELOPMENT OF THE FEATURE LIBRARY
3.1

The Role of Feature Library in Process Planning System
A manufacturing feature can be defined simply as a geometric shape that has its manufacturinginformation to create the shape. This definition means that when a manufacturing feature is
extracted from the product design information, the possible manufacturing information to create theshape is also extractable at the same time (Kanamaru et al. 2004). The linkage between
manufacturing features and their corresponding possible manufacturing information is stored in the
database, which we call as a feature library.
Thus, a feature library plays a big role in FBFPPS for the generation of process plans based on
manufacturing features. As manufacturing features are extracted, the manufacturing information canalso be extracted from the feature library.
3.2

Considering Designer’s Intention for the Creation of Manufacturing Features Ontology
Manufacturing features are extracted from the product design information. However, torecognize the functions of the manufacturing features, we have to know why the designer designs
the geometrical shapes, or in other words, we have to understand the designer’s intention.
Understanding the designer’s intention is very important to extract the proper manufacturing
information to create the manufacturing features. Since normally designer does not design a partusing manufacturing features, we suppose that it is better to understand the designer’s intention byconsidering the functions of the face elements that construct the manufacturing features.
The functional data of face elements can be described as basic function, mechanism utilized
for realization of the basic function and condition and direction of the motion. The detail
explanation of the functional data of face elements is given in other reports (Yoshikawa et al. 1987)(Ando et al. 1989). Table 1 shows the contents of functional properties of face elements that areused for the creation of manufacturing features ontology.

Basic Function
Transmission of
motionConstraint of
motionFixation of motion

3.3

Table 1 Contents of Functional Properties
Mechanism utilized for realization ofCondition and direction of thethe basic function
motion
1: friction-mech.,
1:liner, 2: smooth-liner,
2:gear-mech.,
3:very-smooth-liner, 4:round,
3:link-mech.,
5:smooth round,
4:cam-mech.
6:very smooth round
1: rigidity-mech.,
1: liner, 2:weak-radial,
2: ball-bearing-mech.,
3:strong-radial, 4:weak-thrust,
3: sliding-mech.
5: strong-thrust
1: bolt-and-nut, 2: bolt-only,
1: stationary-object,
3: friction-mech., 4: bearing-fit,
2:revolutionary-object
5: key-fit, 6: river-fit, 7: shrinkage-fit

Creation of Manufacturing Features Ontology
Figure 5 shows the manufacturing features ontology and the functional data ontology. New
classes for manufacturing features ontology are created to have their relation with the functional
data ontology. The relation between the class of the manufacturing features ontology and thefunctional data ontology is defined as how the manufacturing features should be manufactured tofulfill the required functions. Here, each new class of the manufacturing features ontology will referto a collection of possible manufacturing information that can be used to create the shape of theinstances of the feature class. In figure 5, a “threaded drilled thru hole” class is created to relate thethru hole feature type in the manufacturing features ontology with the “fixed with bolt and nuts andis a stationary-object” class of the functional data ontology. This is done since a threaded drilled
thru hole can fulfill the required mentioned functions. And for the “threaded drilled thru hole”
feature class, a collection of possible manufacturing information for the instances of the “threaded
drilled thru hole” feature class should be prepared so that when a manufacturing feature extracted

by the Extended SRG Method falls to this class to fulfill the required functional data as intended by
the designer, a proper manufacturing information can be extracted automatically. Thus the creationof manufacturing features ontology will make the feature library be useful for the extraction ofproper manufacturing information that can lead to the generation of process plans of a part.
Manufacturing
Features
Ontology

Manufacturing Features

Step

Thru Hole

Milled Thru HoleThreaded DrilledThru Hole

Functional
Data
Ontology

Feature Classes thatcan be represented by
the Extended SRG

Stepped-HoleDrilled Thru Hole
Precise Drilled Thru Hole

Fixed with Bold and Nuts andis a stationary object

Transmission
realized by Friction
Mechanism

Constraint realized by
Rigidity Mechanism

Transmissionof Motion

Constraintof Motion

Fixed with
Bolts and Nuts

Fixation of
MotionFunctional Data

Fig.5 Ontology of Manufacturing Features and Functional Data
4. CASE STUDY
Figure 6 shows a sample part for the case study and the functions of the face elements of thesample part.
First, Extended SRG Method is applied to extract manufacturing features from the sample part.
There are 5 thru hole features extracted. Then using the function data as the input, the extracted
features find the matched feature class from the feature library. Here, one thru hole feature falls to
the “grinded thru hole” feature class, and four thru hole features fall to the “threaded drill thru hole”
feature class. Then, as illustrated in figure 7, manufacturing information for each thru hole features
are extracted by referring the instances of the feature classes. The thru hole feature that falls to the“grinded thru hole” feature class extracts a manufacturing method where cylindrical grinder isrequired to manufacture the shape. The four thru hole features that fall to the “threaded drill thruhole” feature class extract a manufacturing method where threading is required to manufacture theshape. Thus, by considering the designer’s intention described in the functional data of the faceelements that construct the features for the development of the feature library, the automatedextraction of manufacturing information is made possible.

Basic Function: Fixation
Mechanism: bolt
Motion: Stationary-Object
Basic Function: Fixation
Mechanism: bolt
Motion: Stationary-Object
Basic Function: Constraint
Mechanism: rigidity
Motion: weak radial

Basic Function: Fixation
Mechanism: bolt
Motion: Stationary-Object

Basic Function: Fixation
Mechanism: bolt
Motion: Stationary-Object

Fig.6 A Sample Part and the Functions of the Face Elements
Thru Hole Feature
Feature Class: “Threaded Drill
Thru Hole”
Thru Hole Feature
Feature Class: “Threaded Drill
Thru Hole”
Thru Hole Feature
Feature Class: “Grinded
Thru Hole”

Thru Hole Feature
Feature Class: “Threaded Drill
Thru Hole”

Thru Hole Feature
Feature Class: “Threaded Drill
Thru Hole”

Fig.7 Extracted Manufacturing Features and Their Proper Feature Classes
5. CONCLUSION
In this paper, we presented the creation of ontology of manufacturing features for thedevelopment of a feature library by considering the designer’s intention described in the functional
data of the face elements that construct the features. New classes for manufacturing features
ontology are created to have their relation with the functional data ontology. Each new class of the
manufacturing features ontology will refer to a collection of possible manufacturing informationthat can be used to create the shape of the instances of the feature class. As shown in the case study,
the creation of manufacturing features ontology will make the feature library be useful for the
automated extraction of proper manufacturing information for the generation of process plans.
REFERENCES
Ando, K., Yoshikawa, H., 1989, “Generation of Manufacturing Information in Intelligent CAD”,
Annals of CIRP, Vol.38/1, 133-136
Kanamaru, M., Ando, K., Muljadi, H., Ogawa, M., 2004, “Manufacturing Feature Library for the
Machining Process Planning”, Proceedings of the JSPE Autumn Conference (in printing)Kao, C.Y., Kumara, S.R.T., Kasturi R., 1995,”Extraction of 3D Object Features from CAD
Boundary Representation Using the Super Relation Graph Method”, IEEE Transaction on PatternAnalysis and Machine Intelligence, 17(12), 1228-1233
Muljadi, H., Ando, K., Ogawa, M., 2002, “Feature Recognition and Organization for Making
Multiple Process Plans”, Proceedings of 7th International Pacific Conference on Manufacturing &Management, 934-939
Muljadi, H., Ando, K., Ogawa, M., 2003, “Practical Application of Manufacturing Feature
Recognition Method”, Proceedings of the International Conference on Leading Edge Manufacturing
on 21st Century, 813-818
Sakurai, T., Muljadi, H., Ando, K., Ogawa, M., 2000, “Research of Dynamic, Flexible andIntegrated Process Planning System”, Proceedings of the JSPE Spring Conference, 44 (in Japanese)
Yoshikawa, H., Ando, K., 1987, “Intelligent CAD in Manufacturing”, Annals of CIRP, Vol.36/1,
77-80