A CASE STUDY INVESTIGATING RULE BASED DESIGN IN AN INDUSTRIAL SETTING

This thesis presents a case study on the implementation of a rule based design (RBD) process for an engineer-to-order (ETO) company. The time taken for programming and challenges associated with this process are documented in order to understand the benefits and limitations of RBD. These times are obtained while developing RBD programs for grid assemblies of bottle packaging machines that are designed and manufactured by Hartness International (HI). In this project, commercially available computer-aided design (CAD) and RBD software are integrated to capture the design and manufacturing knowledge used to automate the grid design process of HI. The stages involved in RBD automation are identified as CAD modeling, knowledge acquisition, capturing parameters, RBD programming, debugging, and testing, and production deployment. The stages and associated times in RBD program development process are recorded for eighteen different grid products. Empirical models are developed to predict development times of RBD program, specifically enabling HI to estimate their return on investment. The models are demonstrated for an additional grid product where the predicted time is compared to actual RBD program time, falling within 20% of each other. This builds confidence in the accuracy of the models. Modeling guidelines for preparing CAD models are also presented to help in RBD program development. An important observation from this case study is that a majority of the time is spent capturing information about product during the knowledge acquisition stage, where the programmer\u27s development of a RBD program is dependent upon the designer\u27s product knowledge. Finally, refining these models to include other factors such as time for building CAD models, programmers experience with the RBD software (learning curve), and finally extending these models to other product domains are identified possible areas of future work

A study of the methodologies currently available for the maintenance of the knowledge-base in an expert system

This research studies currently available maintenance methodologies for expert system knowledge bases and taxonomically classifies them according to the functions they perform. The classification falls into two broad categories. These are: (1) Methodologies for building a more maintainable expert system knowledge base. This section covers techniques applicable to the development phases. Software engineering approaches as well as other approaches are discussed. (2) Methodologies for maintaining an existing knowledge base. This section is concerned with the continued maintenance of an existing knowledge base. It is divided into three subsections. The first subsection discusses tools and techniques which aid the understanding of a knowledge base. The second looks at tools which facilitate the actual modification of the knowledge base, while the last secttion examines tools used for the verification or validation of the knowledge base. Every main methodology or tool selected for this study is analysed according to the function it was designed to perform (or its objective); the concept or principles behind the tool or methodology: and its implementation details. This is followed by a general comment at the end of the analysis. Although expert systems as a rule contain significant amount of information related to the user interface, database interface, integration with conventional software for numerical calculations, integration with other knowledge bases through black boarding systems or network interactions, this research is confined to the maintenance of the knowledge base only and does not address the maintenance of these interfaces. Also not included in this thesis are Truth Maintenance Systems. While a Truth Maintenance System (TMS) automatically updates a knowledge base during execution time, these update operations are not considered \u27maintenance\u27 in the sense as used in this thesis. Maintenance in the context of this thesis refers to perfective, adaptive, and corrective maintenance (see introduction to chapter 4). TMS on the other hand refers to a collection of techniques for doing belief revision (Martin, 1990) . That is, a TMS maintains a set of beliefs or facts in the knowledge base to ensure that they remain consistent during execution time. From this perspective, TMS is not regarded as a knowledge base maintenance tool for the purpose of this study

Expert system verification and validation study: ES V/V Workshop

The primary purpose of this document is to build a foundation for applying principles of verification and validation (V&V) of expert systems. To achieve this, some V&V as applied to conventionally implemented software is required. Part one will discuss the background of V&V from the perspective of (1) what is V&V of software and (2) V&V's role in developing software. Part one will also overview some common analysis techniques that are applied when performing V&V of software. All of these materials will be presented based on the assumption that the reader has little or no background in V&V or in developing procedural software. The primary purpose of part two is to explain the major techniques that have been developed for V&V of expert systems

Knowledge Representation Using Petri Nets and Knowledge Tables

Computer Scienc

Expert system verification and validation study: Workshop and presentation material

Workshop and presentation material are included. Following an introduction, the basic concepts, techniques, and guidelines are discussed. Handouts and worksheets are included

First CLIPS Conference Proceedings, volume 1

The first Conference of C Language Production Systems (CLIPS) hosted by the NASA-Lyndon B. Johnson Space Center in August 1990 is presented. Articles included engineering applications, intelligent tutors and training, intelligent software engineering, automated knowledge acquisition, network applications, verification and validation, enhancements to CLIPS, space shuttle quality control/diagnosis applications, space shuttle and real-time applications, and medical, biological, and agricultural applications

Tool Support for Finding and Preventing Faults in Rule Bases

This thesis analyzes challenges for the correct creation of rule bases. Based on experiences and data from three rule base development projects, dedicated experiments and a survey of developers, ten main problem areas are identified. Four approaches in the area of Testing, Debugging, Anomaly Detection and Visualization are proposed and evaluated as remedies for these problem areas