Internet enabled fixture design system using case based reasoning technology

INTERNET-ENABLED FIXTURE DESIGN SYSTEM USING
CASE-BASED REASONING TECHNOLOGY

FAN LIQING
(B. Eng.)

A THESIS SUBMITTED
FOR THE DEGREE OF MASTERS OF ENGINEERING
DEPARTMENT OF MEACHANICAL ENGINEERING
NATIONAL UNIVERSITY OF SINGAPORE
2003


Acknowledgements

First and foremost I would like to express his sincere thanks and appreciation to my
supervisor, Associate Professor A. Senthil Kumar, for guidance, for his involvement in
this research, for the technical discussions and particularly for his support throughout
the course of my Master studies. I wouldn’t have finished this thesis without his
support and drive.

Thanks to my colleague, Fathianathan Mervyn, for his error check for this thesis and
for the suggestion and discussion with him at the research project. I am also very
grateful to fellow graduate students for encourage and discussion in study: Wang
Zhigang, Wu Yifeng, Zhang Wei, Wang Binfang, Chen Xiaolong, and Lu Cong.

I would also like to acknowledge financial support provided by National University of
Singapore and to thank Laboratory for Concurrent Engineering and Logistics (LCEL)
for providing facility to complete my research.

Last but not least, I would like to express my deep sense of gratitude to my wife, Chen

Hui, for her understanding, moral support and love. My son Fan Ziqian gave me great
spiritual support and encouraged me throughout this difficult but exciting journey. I
thank my mother, my brother and my sister for all of their support and love.

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Table of Contents

Acknowledgements ........................................................................................................ i
Table of Contents .......................................................................................................... ii
Summary....................................................................................................................... vi
List of Figures.............................................................................................................viii
List of Tables ................................................................................................................. x
Chapter 1 Introduction................................................................................................. 1
1.1 Fixture ................................................................................................................... 2
1.2 Case-based Reasoning .......................................................................................... 4
1.3 Internet-enabled Manufacturing Environment...................................................... 5
1.4 Organization of the Thesis .................................................................................... 6
Chapter 2 Research Background and Literature Review......................................... 8
2.1 Fixture Design Fundamentals ............................................................................... 8
2.1.1 Fixture Design Principle ................................................................................ 8
2.1.2 The 3-2-1 Locating Principle ....................................................................... 10
2.1.3 Modular Fixture Systems ............................................................................. 11
2.2. Introduction to Case Based Reasoning .............................................................. 13
2.2.1 Overview...................................................................................................... 13
2.2.2 Case-Based Reasoning Cycle ...................................................................... 14
2.2.3 Areas of CBR Applications ......................................................................... 15
2.3 Case-Based Reasoning for Design...................................................................... 16
2.3.1 Issues in Developing CBD systems ............................................................. 16

ii


2.3.2 Case Representation and Memory Organization ......................................... 17
2.3.3 Indexing and Case Retrieval ........................................................................ 19
2.3.4 Case Adaptation ........................................................................................... 20
2.4 Distributed CBR.................................................................................................. 21
2.5 Related Research Works ..................................................................................... 23
2.5.1 Case-Based Reasoning in Mechanical Engineering .................................... 23
2.5.2 Case-Based Reasoning in Fixture Design.................................................... 25
2.6 Discussion ........................................................................................................... 26
2.7 Research Objective and Scopes .......................................................................... 27
Chapter 3 System Architecture ................................................................................. 29
3.1 Distributed CBR Architecture............................................................................. 29
3.1.1 Three-tier Architecture Model ..................................................................... 29
3.1.2 Architecture for Distributed CBR................................................................ 31
3.2 Architecture of the System.................................................................................. 32
3.2.1. Server .......................................................................................................... 32
3.2.2 Client............................................................................................................ 33
3.2.3 Repository .................................................................................................... 35
3.3 Summary ............................................................................................................. 36
Chapter 4 Knowledge Representation for Fixture Design...................................... 37
4.1 Introduction......................................................................................................... 37
4.2 Case Representation using XML ........................................................................ 39
4.2.1 Case Structure .............................................................................................. 39
4.2.2 Part Representation ...................................................................................... 40
4.2.3 Fixture Design Representation..................................................................... 42
4.2.4 Setup Representations.................................................................................. 44

iii


4.2.5 XML Schema for Modeling......................................................................... 45
4.3 Case Base Organization ...................................................................................... 46
4.4 Summary ............................................................................................................. 47
Chapter 5 Case-Based Fixture Design Process ........................................................ 48
5.1 Design Process using Case-based Reasoning ..................................................... 48
5.2 Distributed CBR in Fixture Design..................................................................... 50
5.3 Case Indexing...................................................................................................... 51
5.4. Case Retrieval .................................................................................................... 53
5.4.1 Geometrical Similarity Metric ..................................................................... 55
5.4.2 Non-geometrical Similarity ......................................................................... 61
5.4.3 Mass Case Filter........................................................................................... 62
5.4.4 Ranking of Cases ......................................................................................... 63
5.5 Adapting Cases ................................................................................................... 63
5.5.1 Workpiece Adaptation ................................................................................. 64
5.5.2 Baseplate Adaptation ................................................................................... 66
5.5.3 Locating Elements Adaptation..................................................................... 68
5.5.4 Supporting Elements Adaptation ................................................................. 69
5.5.5 Clamping Element Adaptation..................................................................... 72
5.6 Case Storage........................................................................................................ 74
5.7 Summary ............................................................................................................. 74
Chapter 6 Case Study ................................................................................................. 75
6.1 Information Input ................................................................................................ 75
6.1.1 Feature Information Input ............................................................................ 75
6.1.2 Setup Information Input............................................................................... 77
6.2 Retrieval.............................................................................................................. 78

iv

6.3 Adaptation........................................................................................................... 83
6.4 Case Storage........................................................................................................ 87
6.5 Summary ............................................................................................................. 88
Chapter 7 Conclusions and Future Works............................................................... 89
7.1 Research Contributions....................................................................................... 89
7.2 Recommendation for Future Work ..................................................................... 91
References.................................................................................................................... 92

v


Summary

The primary objective of the research in this thesis is to develop an Internet-enabled
computer-aided fixture design system. This system is implemented in a new
environment that utilizes Case-Based Reasoning (CBR) paradigm, an approach derived
from instance based previous solutions of similar problems.

The main issues for the system are case representation and process control issue that
includes case indexing and retrieval, case adaptation, and case storing. Case
representation for fixture design is composed of three parts: part representation, fixture
representation and setup representation. They are described in XML (eXtensible
Markup Language) using Unified Modeling Language (UML) notation. A featurebased similarity measure is adopted for case indexing and case retrieval in this system.
There are two major perspectives in a part considered in the similarity: geometric
shape and material. In addition, a filter method is introduced to reduce the retrieval
time based on the size and shape of parts when the size of Case Base is large. A
derivational replay method is mainly adopted to adapt a retrieved case. This adaptation
process is fully integrated with the CAD system; it can interact with solid models on

the Java3D canvas. This process involves with five modules: workpiece adaptation,
base-plate adaptation, locator adaptation, support adaptation and clamp adaptation. It
creates a new solution using the same procedure.

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This is one of the first Internet-enabled design systems that are implemented using
distributed case-based reasoning methodology. A distributed CBR engine is developed
as client-server model and it is implemented to integrate with existing internet-enabled
fixture design system using Java3D technology and Java programming language so
that the system can run on any platform that supports Java. The system has been tested
and demonstrated with case study for fixture design in a distributed design
environment.

vii


List of Figures

Figure 2.1 Twelve degrees of freedom ........................................................................... 9
Figure 2.2 The 3-2-1 method of location ...................................................................... 11
Figure 2.3 Modular Fixture Systems ............................................................................ 12
Figure 2.4 The typical CBR cycle [Aamodt & Plaza, 1994] ........................................ 15
Figure 2.5 Memory organization .................................................................................. 18
Figure 3.1 A typical three-tier client-server architecture.............................................. 30
Figure 3.2 Architecture for distributed CBR engine..................................................... 31
Figure 3.3 System Architecture .................................................................................... 33
Figure 4.1 Unified modeling language notation ........................................................... 39
Figure 4.2 Case structure .............................................................................................. 40

Figure 4.3 Part representation in UML notation........................................................... 41
Figure 4.4 Inheritance in the Hole class........................................................................ 42
Figure 4.5 Example of XML file for part representation.............................................. 43
Figure 4.6 Fixture Design Representation Model in UML Notation............................ 43
Figure 4.7 Fixture design and its XML schema............................................................ 44
Figure 4.8 Setups in UML notation .............................................................................. 45
Figure 4.9 Structure of a facet data XML file............................................................... 46
Figure 4.10 Case Base organizations ............................................................................ 47
Figure 5.1 Design process using case-based reasoning ................................................ 49
Figure 5.2 Work flow of CBR on fixture design .......................................................... 51
Figure 5.3 Flow chart of case retrieval ......................................................................... 56

viii


Figure 5.4 An example of workpiece............................................................................ 57
Figure 5.5 Adapting cases process................................................................................ 65
Figure 5.6 Base-plate classification .............................................................................. 66
Figure 5.7 Flow chart of baseplate adaptation .............................................................. 67
Figure 5.8 Flowchart of locating elements adaptation.................................................. 70
Figure 5.9 Flowchart of support adaptation.................................................................. 71
Figure 5.10 Flowchart of clamping element adaptation ............................................... 73
Figure 6.1 Load a workpiece into system ..................................................................... 76
Figure 6.2 Input the property information of the workpiece ........................................ 76
Figure 6.3 Input parameters for selected feature .......................................................... 77
Figure 6.4 Group features into existing features and to-be-machined features ............ 77
Figure 6.5 Examples of parts in database ..................................................................... 78
Figure 6.6 The retrieved part names and their similarity value .................................... 81
Figure 6.7 One of retrieved parts and its fixture........................................................... 81
Figure 6.8 Tree views of features and fixture design of one of retrieved parts ............ 82

Figure 6.9 The new workpiece and fixture designs of its similar parts ........................ 82
Figure 6.10 Face selection for supporting faces ........................................................... 84
Figure 6.11 The input part and existing fixture ............................................................ 84
Figure 6.12 A locating face is selected for re-positioning the highlighted locator....... 85
Figure 6.13 A locator is selected from Database to replace the highlighted locator .... 85
Figure 6.14 A new point is selected to re-locate the highlighted support..................... 86
Figure 6.15 A top-clamp element is selected to clamp the workpiece ......................... 86
Figure 6.16 A side-clamp is selected to clamp the workpiece...................................... 87
Figure 6.17 The final fixture design of the new workpiece.......................................... 87
Figure 6.18 The storing option...................................................................................... 88

ix


List of Tables

Table 5.1 Examples of feature count, feature direction and feature direction .............. 59
Table 5.2 Examples of directional distribution............................................................. 60
Table 5.3 Examples of size distribution........................................................................ 60
Table 5.4 Relative orientation of feature class Hole and Slot....................................... 61
Table 5.5 Examples of relative orientation ................................................................... 61
Table 5.6 Material matrix ............................................................................................. 62
Table 5.7 Heat-treatment matrix ................................................................................... 62
Table 5.8 Part profile size group................................................................................... 63
Table 5.9 Assembly relationships between locator and locating face .......................... 68
Table 6.1 The input information ................................................................................... 79
Table 6.2 The geometrical similarity ............................................................................ 80

x

Chapter 1 Introduction

In modern manufacturing, concurrent engineering and computer integrated
manufacturing (CIM) are becoming accepted as essential management techniques for
minimizing lead time [Nee, et. al. 1995]. Computer-aided process planning (CAPP)
used within the framework of concurrent engineering is the interface between design
and manufacture. Fixture design is an essential part of process planning. CIM is not
possible without CAPP and no CAPP system is complete without a computer aided
fixture design module.

This thesis reports the development of a computer aided fixture design system in a
mechanical engineering domain. In this chapter, section 1.1 introduces what the fixture
is, fixture design approaches and problems current fixture design is facing. Section 1.2
presents Case-based Reasoning (CBR) approach and why it is utilized in fixture design
domain. Section 1.3 discusses the reasons why manufacturing systems are applied via
Internet. The first three sections provide background and motivation of this thesis.
Section 1.4 establishes the objectives and scopes of this research, and Section 1.5 gives
an overview of the rest of the thesis.

1


Chapter 1 Introduction

1.1 Fixture
Fixtures are devices which are designed to repeatedly and consistently maintain the
orientation of a workpiece during machining, assembling, welding, inspection, etc.
[Nee et al. 1995]. They are an essential part of manufacturing production. As part of
manufacturing tooling, fixture design makes significant contributions to the production

time and cost in daily production.

Flexible fixtures play important roles in modern flexible manufacturing systems (FMS)
as well as computer-integrated manufacturing system (CIMS). In order to achieve an
integrated manufacturing system, standardization and flexibility in fixture design are
important. Modular fixtures just meet these requirements. Modular fixtures are
designed as a series of prefabricated standard components and units with relatively
tight geometric tolerances that can be assembled rapidly into a variety of design
configurations to hold parts with different geometry and fixturing requirement.

Fixture design is a highly complex process because it must consider the workpiece, the
cutting tools, the machining environment and the components that are interacted with
each other. Besides these aspects mentioned above, Senthil Kumar et. al. [1995]
illustrated all factors considered in fixture design that are categorized into three basic
constraints, including technical, economical and resource availability.

Fixture design is also experience-based. Designers prefer to use previous designs
because they save time and effort and because the concepts have proven effective in
previous situations. In the design of fixture, based on all the information pertinent to
the product as given by the engineering specification and the process sheet, a tool
2


Chapter 1 Introduction

designer configures a fixture setup appropriate to the workpiece depending on his/her
experience of fixturing a similar product [Nnaji et al. 1990a]. Meanwhile, the selection
of surfaces on the workpiece and fixture elements for locating and clamping during
machining is flexible and largely relies on the prior experience of the designer.

According to statistics, in the manufacturing industry more than 70% of fixture designs
are generated by modifying existing designs that are similar [Rong and Zhu, 1999].
This also makes necessary a computerized tool for fixture design that stores previous
design experiences and retrieve them when needed.

With the application of Artificial Intelligence (AI) technology in fixture design, some
research work has been attempted to capture design knowledge from design experience
in a rule-based expert system [Senthil Kumar, et. al. 1992] [Nnaji, et. al. 1990b]
[Caillaud, et. al. 1995] [Pham, et. al. 1990]. However, most of the systems are only
able to handle prismatic workpieces with relatively simple prismatic features because
the knowledge and experience in fixture design is too complex to be expressed using
simple rules.

In addition, in today's product development context, the design of products is subcontracted out to other firms. This creates a scenario where the designers and
manufacturing engineers may be globally dispersed. Therefore, to realize a
collaborative functional fixture design system, care must be taken such that the design
activity can be performed on the internet.

3


Chapter 1 Introduction

For these reasons, a case-based reasoning (CBR) approach which organizes previous
experiences as cases to reason is attempted in this work. Except CBR approach, a new
paradigm in Computer Integrated Manufacturing (CIM), namely Internet-based
Manufacturing, is also adopted in this work. The objective of this research is to
propose a system where a strategy extending case-based reasoning to the Internet,
distributed case-based reasoning, is applied in the fixture design domain.

1.2 Case-based Reasoning
CBR is a general problem solving method which uses past experiences to solve novel
problems [Kolodner, 1993]. The past experiences are stored in memory as cases, which
are packets of information about the experiences. A case may contain information
about a problem encountered in the past and a complete and successful solution to the
problem. Given the new problem to be solved, the case-based method retrieves the
solution to a similar problem encountered in the past, adapts the previous solutions to
the current problem, and stores the new problem-solution packet as another case in the
memory.

CBR is a more useful method than the use of an expert system to simulate human
thought because proposing a similar case and applying a few modifications seems to be
self-explanatory and more intuitive to many humans. In addition, a case-based
reasoning system is generally more flexible than the traditional rule-based expert
system for problem solving, because:
•

Knowledge acquisition is simplified by recording a number of problems and
their solutions instead of building generalized rules;
4


Chapter 1 Introduction

•

by acquiring new cases, it can learn from experience and thus increase its
efficiency and its problem-solving capabilities over time;

•

It can suggest solutions in domains where knowledge is incomplete and openended so that it is difficult to generate rules to cover the domain.

As mentioned in last section, fixture design is a complex process and based on past
experiences, and its domain knowledge is incomplete and difficult to generalize. These
features make case-based reasoning approach naturally suitable to the domain of
fixture design. Fixture design can also benefit from the advantages of case-based
reasoning.

1.3 Internet-enabled Manufacturing Environment
In today's manufacturing environment, more and more businesses are exploring the use
of the internet/intranet and web technologies to support distributed manufacturing
facilities around the world. Implementing distributed manufacturing systems would
offer rapid manufacturing capacity. An Internet-enable manufacturing system not only
saves costs and time, but also creates a seamless collaborative manufacturing
environment to resolve problems with heterogeneous manufacturing software products.

Another goal of developing an Internet-based manufacturing and design environment
is that it has the capacity to share information, knowledge base, design tools and
existing design solutions to authorized users. A user could share his/her designs to
other users by storing the designs into database. Users around the world could share
their designs to other users by storing the designs into database from which they can be
retrieved when needed.
5


Chapter 1 Introduction

Therefore, in this research an attempt will be made to develop a fixture design system
based on Internet. This makes the fixture design system possible to interoperate with

other Internet-based manufacturing systems, such as computer-aided process planning
(CAPP) and computer-aided numerical control systems. This also makes available the
database storing fixture design experiences that users around the world could access.

1.4 Organization of the Thesis
This chapter has discussed the underlying motivation of this research and presented
approaches adopted by this thesis. The rest of this thesis is organized as follows.

Chapter 2 provides the principle of fixture design, gives an overview of case-based
reasoning, including CBR cycle and main tasks of CBR, presents research issues in
developing case-based design applications, and introduces distributed CBR and the
classification of its applications. Chapter 2 also discusses related research work on
mechanical engineering domain including fixture design and proposes the objective
and scopes of this research.

In Chapter 3, a traditional three-tire client-server model is introduced, a distributed
CBR engine is presented and system architecture for integrating distributed CBR and
an Internet-enabled fixture design system is proposed.

In Chapter 4, the knowledge in the domain of fixture design is represented using XML
and the XML schema is expressed in UML notations. The structure of Case Base in
this system is also presented in this chapter.
6


Chapter 1 Introduction

Chapter 5 presents an overview of design process using CBR. It discusses the fixture
design process of this system in detail, which includes case indexing, case retrieval,
case adaptation and case storage aspects.

Chapter 6 chapter shows the developed fixture design system with relevant Graphical
User Interface (GUI) design.

Chapter 7 concludes this thesis by research contributions. It also discusses the potential
of future work, both in terms of how the current fixture design system could be
enhanced, and the directions in which this thesis could lead to future research.

7


Chapter 2 Research Background and Literature Review

This chapter not only introduces the fundamentals of fixture design, but also provides
an overview of the field of case-based reasoning in order to justify its use in this
application. Section 2.1 briefly presents the domain knowledge for fixture design.
Section 2.2 introduces definition of CBR, how it works and its tasks classification.
Section 2.3 presents CBR application in design, and discusses research issues in casebased design (CBD) applications, which primarily include case representation, case
indexing and case retrieval, and case adaptation. Section 2.4 presents distributed CBR
and the classification of its applications. Section 2.5 discusses related research works
using CBR in mechanical domain including fixture design. Section 2.6 discusses why a
distributed case-based reasoning approach is adopted in this research. Section 2.7
establishes the objectives and scopes of this research.

2.1 Fixture Design Fundamentals
2.1.1 Fixture Design Principle
Fixture design is a complex process in which the workpiece, the cutting tool, the
machining environment and the fixture components interact with each other. The basic
requirement of a fixture is to locate and secure the workpiece in right position and
orientation, to assure repeatability, and to remain the workpiece in equilibrium. The

8


Chapter 2. Research Background and Literature Review

workpiece has an unconstrained spatial motion of twelve degrees of freedom (DOF) in
3D space. These movements are along the positive and negative directions of the x, y,
and z-axes, as well as clockwise and counterclockwise rotations about the three axes
(Figure 2.1). The DOFs are constrained by fixture elements.

3

7

6

8

2

1
11

12

9

5

10
4

Figure 2.1 Twelve degrees of freedom

The primary components for a typical fixture are locators, supports and clamps.
Locators restrict movement of the workpiece in static equilibrium. Clamps provide a
holding force on the workpiece against the locators by preventing motion. Supports
prevent workpiece deflection under the action of imposed cutting forces or clamping
forces.

There are four general requirements of a fixture: [Hargrove and Kusiak, 1994]
ƒ

Accurate position: A workpiece must be located accurately in a fixture with
respect to the machine coordinate system and the workpiece coordinate system.

ƒ

Total restraint: The fixture must hold and restrain the workpiece from the
external force, e.g. cutting force.

9


Chapter 2. Research Background and Literature Review

ƒ

Limited deformation: When a workpiece is under the action of cutting forces

and clamping forces, additional adjustable-locators or adjustable-supports are
needed to reduce deformation of the workpiece.

ƒ

No interference: None of the fixture elements should interfere with any of the
machining operations. At the same time, interference among fixture elements
should be avoided.

Moreover, the design outcomes must satisfy several design criteria so as to arrive at a
“good design” [Nee et al. 1995].
ƒ

Design specification: Because fixture design can have an effect on
dimensional tolerance, geometric tolerance and workpiece surface finish, a
fixture must have an ability to produce workpiece to specification.

ƒ

Factory standard: Fixture design is constrained by factory standards to ensure
compatibility with other systems.

ƒ

Ease of use: The fixture should be designed to satisfy ergonomic and ease of
use.

ƒ

Cost: Since cost of fixtures is a major part of an FMS, saving in fixture costs

could decrease overall production costs.

2.1.2 The 3-2-1 Locating Principle
The most common locating rule in practice for prismatic workpiece is the 3-2-1
method. The rule provides the maximum rigidity with the minimum number of fixture
components. In general, an unrestricted workpiece in space can have twelve degrees of
freedom. A workpiece may be positively located by means of six point positions so
that they restrict nine degrees of freedom (DOF) (Figure 2.2). However, together with

10


Chapter 2. Research Background and Literature Review

the clamps (the wide arrows shown in Figure 2.2) which hold the part in place, the
locators (the gray cylinders in Figure 2.2) provide equilibrium of all forces. Flat-2-1
and 4-2-1 principle are alternative methods of 3-2-1 principle. In flat-2-1, the primary
locating surface is a flat surface. It is not suitable when a through-hole is machined in a
setup. In the 4-2-1 method of location, four points are positioned on the primary
locating surface.

Tertiary
Locating
Surface

Secondary
Locating
Surface

Primary

Locating
Surface
Figure 2.2 The 3-2-1 method of location

2.1.3 Modular Fixture Systems
Dedicated fixtures that are specially designed and built for a particular workpiece has
greatly contributed to the development of automated manufacturing systems,
especially in the automobile industry. They ensure repeatability and facilitate loading
and unloading, and meeting stringent design specifications. As in the development of
technologies, flexible fixturing is desired for the need of flexibility and the increasing
design complexity. Currently, modular fixtures are the most widely used flexible
fixture in industry.

A modular fixture system is flexible because it can be designed to hold parts with
different geometry and fixturing requirements by constructing a large number of

11


Chapter 2. Research Background and Literature Review

configurations using standard fixture elements. Modular fixtures can reduce time and
labor cost in fixture design. They also need less storage space compared with dedicated
fixtures. Hence, manufacturing lead time is shorter, engineering changes are easier to
handle, and storage cost is decreased.

Modular fixture systems are broadly classified into two categories: T-slot-based and
dowel-pin-based systems. Figure 2.3 are designs of T-slot-based and dowel-pin-based
modular fixture design systems. Compared with the T-slot-based modular fixture, the
dowel-pin-based modular fixtures have the following advantages [Rong and Zhu,

1999]: (1) high fixturing stiffness; (2) Low manufacturing cost; (3) short setup time; (4)
reliable locating. The only disadvantage is that it has less assembly flexibility.

Although fixturing is fundamental to many manufacturing operations such as
machining, fabrication, assembly and inspection, the research conducted in this thesis
is limited to machining fixtures. In addition, the system in this thesis utilizes the
dowel-pin-based modular fixture system provided by IMAO Corporation, Japan.

(a)

(b)

Figure 2.3 Modular Fixture Systems
(a) T-slot-based (b) dowel-pin-based

12


Chapter 2. Research Background and Literature Review

2.2. Introduction to Case Based Reasoning
2.2.1 Overview
Case-based reasoning (CBR) is an Artificial Intelligence (AI) technology like rulebased reasoning, neural networks or genetic algorithms, which is described as a
methodology for problem solving. In case-based reasoning, a new problem is solved
by searching its similarity with one or several previously solved problems and by
adapting their known solutions rather than working out from the scratch. In many
aspects, case-based reasoning is a problem solving method different from other AI
approaches. In particular, instead of only using general dependent heuristic knowledge
like in the case of expert system, it is able to use the specific knowledge of concrete,
experienced, problem situations. Another import characteristic is that CBR implies

incremental learning since a new experience is memorized and available for future
problem solving each time a problem is solved. CBR is thus a simple problem solving
paradigm that involves matching your current problem against problems that you have
solved successfully in the past.

Case-based reasoning can provide an alternative to rule-based expert systems, and is
especially appropriate when the number of rules needed to capture an expert’s
knowledge is unmanageable or when the domain theory is too weak or incomplete.
CBR can work in problem domains where the underlying models used for solutions are
not well understood. Historically, CBR has shown its greatest success in areas where
individual cases or precedents govern the decision-making processes, as in case law.

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Chapter 2. Research Background and Literature Review

2.2.2 Case-Based Reasoning Cycle
The process involved in CBR can be represented by a schematic cycle (Figure 2.4).
Aamodt and Plaza [1994] have described CBR typically as a cyclical process
comprising the four REs:
(1) RETRIEVE the most similar case or cases comparing the case to the library of
past cases;
(2) REUSE the retrieved case(s) to attempt to solve current problem;
(3) REVISE the proposed solution if necessary, and
(4) RETAIN the new solution as a part of a new case

Initially, a problem in a domain is defined as a new case that can be used to retrieve a
case or a list of cases from the collection of previous cases called case library (or case
base). The candidate solution is also retrieved from case library. The retrieved case(s)

is combined with the new case into a solved case through REUSE, i.e., a proposed
solution to the initial problem. In the REVISE process, this solution is verified for
success, and repaired if necessary. During RETAIN, useful experience is retained for
future reuse, and the case base is updated by a new learned case, or by modification of
some existing cases.

14