Intelligent knowledge management environment for design and manufacturing
Abstract
This thesis reports on a development of the knowledge management environment for design and manufacturing. The original objective of this research is to build up an intelligent environment which can assist engineers in managing a large amount of knowledge for configuration design. While this research has been implemented in a generic manner, to look for practical applications constitutes the other important objective of this study. The proposed environment consists of a scheme for knowledge organization and several associated control mechanisms. The three major modules can be briefly described as follows: (1) Knowledge Organization. A hierarchical organization scheme in an object-oriented environment is proposed to arrange the information of configuration design into structured knowledge. (2) Constraint-Based Knowledge Synthesis. A constraint satisfaction with machine learning approach is developed to satisfy the requirements of completeness and consistency for a given design purpose. (3) Goal-Directed Analysis. The goal-directed clustering and the Analytic Hierarchy Process (AHP) are used to manage the classification and the multi-attribute qualitative evaluation process. Even though these three modules deal with different tasks, they actually are designed to work in a cooperative manner. Thus, this research are not only intended to automate the individual knowledge management modules but also to integrate them. The proposed methodology can be used to assist the designer in exploring multiple solutions for configuration design as well as in making conceptual analysis among different feasible candidates. In addition, this environment can also be addressed to several manufacturing applications especially in the area of group technology.
Degree
Ph.D.
Advisors
Liu, Purdue University.
Subject Area
Industrial engineering|Artificial intelligence
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