Research Into The Self-Reconfiguration Of Knowledgeable Manufacturing System

To solve the general and urgent problems faced by the manufacturing enterprises, a new manufacturing concept--knowledgeable manufacturing is brought forward for this requirement. The self-reconfiguration is one of the important characteristics of knowledgeable manufacturing system (KMS), and it improves the adaptability of the manufacturing system and alters the situation of bad flexibility and repeated development in the existing manufacturing system. Meanwhile, it is the imperative function needed by the modern manufacturing system. Thus, the self-reconfiguration of KMS is studied in this dissertation. The knowledge representation of manufacturing systems is studied and a complicated knowledge representation based on the agent mesh (AM) and knowledge mesh (KM) is presented. The self-reconfiguration operations, their properties and self-reconfiguration algorithms are studied. Meanwhile, the self-reconfiguration enabling tool is developed. Then, as to the approximation in the practical system, a self-reconfiguration method based on the approximate match is proposed. The algorithms of the self-reconfiguration based on the approximate match are studied and the self-reconfiguration enabling tool based on the approximate match is developed. The self-reconfiguration must have reconfiguration expression, thus, the automatic construction of knowledge mesh is studied and two methods are proposed, that is: configuration construction and briefest construction. Finally, as to the decision-making in the self-reconfiguration, the approach to KM reconfiguring decision and the gray decision-making tree approach to mode selection are presented.The main content of this dissertation is introduced in detail as follows:1. The knowledge representation of complicated systems such as KMS is studied. A new approach to knowledge representation based on KM and AM is proposed. The algorithms of the self-reconfiguration and the preprocessing rules in the self-reconfiguration are explored. Thus the theoretical basis of the self-reconfiguration of KMS is established. For the convenience of practical application, the self-reconfiguration enabling tool is realized. In the development of the self-reconfiguration enabling tool, the knowledge representation in KMS and the design of knowledge mesh database are discussed. The realization of the self-reconfiguration algorithms is discussed in detail and the automatic construction of thereal software system is realized. Finally the self-reconfiguration is exemplified by the self-reconfiguration of the management information system (MIS) in a vehicle body plant using the developed enabling tool, which verifies the validation of the self-reconfiguration theory and its enabling tool.2. As to the case of the approximate module in the practical manufacturing system, the approach and application of the self-reconfiguration based on the approximate match of KMS are studied. Firstly, the matching degrees of the self-reconfiguration originals (knowledge point original and relationship original) in the self-reconfiguration of KMS are discussed, and the matching degree definition and the properties are proposed as well as their algorithms. The self-reconfiguration algorithms based on the approximate match of the knowledge mesh are proposed and the theoretical basis of the self-reconfiguration based on the approximate match is established. Then the self-reconfiguration enabling tool based on the approximate match is developed. Finally, the application of the KMS's self-reconfiguration based on the approximate match is exemplified.3. As to the shortcoming: there must be self-reconfiguration expressions given by the users in the self-reconfiguration of KMS, thus, the automatic construction methods based on the user's functional requirement is studied. Two methods are proposed to automatically construct knowledge meshes, that is configuration construction and briefest construction. In KM configuration construction, satisfaction degree relationships between the KM and the users'requirement are defined as well as their operations, and the optimal model of KM multiple set operation expression is proposed. Then the KM multiple set operation expression is optimized based on the improved hybrid genetic algorithm, and the steps of the KM's automatic construction are presented. In KM briefest construction, the matching rules of the briefest KM construction are proposed; meanwhile, the matching problems in the briefest construction of the knowledge points in the bottom layer are analyzed. Then the briefest coincident degrees of the knowledge point functions are defined and the matching algorithms of the knowledge points in the bottom layer are given, and the steps of the KM's briefest automatic construction are also presented. Thus, the construction of briefest KM under the condition of user's satisfaction is solved.4. As to the decision-making in the self-reconfiguration, the approaches to KM reconfiguration decision in the self-reconfiguration and to selecting mode after the self-reconfiguration of KMS are studied. In the KM reconfiguration decision, based on the requirement relationships of KMs, the operations on KMs'fuzzy requirement degrees are defined and the requirement evaluation method for the KM is proposed, which is used for the KM reconfiguration. Next, a grey decision-making tree method is proposed to select the mode in the self-reconfiguration of KMS. The factors influencing the decision-making on the selection of reconfigured KMs are analyzed and classified. The conceptual model of decision-making factors is given and the factors are evaluated by various methods such as investigation, evaluation and functional analysis. On the basis of rational analysis, the gray decision-making tree model is proposed, and the detailed decision-making steps are provided. Finally, the application of the methods in thedecision-making in KMS shows the validation of the decision-making methods.Finally, a self-reconfiguration system is developed based on the above researches. It is a sub-system of the knowledgeable manufacturing system and integrates self-reconfiguration enabling tool based on the accurate match, self-reconfiguration enabling tool based on the approximate match, user data management, user views, KM evaluation, KM automatic construction and system software construction.The research and development of the self-reconfiguration in KMS perfect and develop the KM and its multiple set theory as well as the KMS self-reconfiguration theory. In the meantime, the theoretical basis of the self-reconfiguration based on the approximate match and the optimization in the self-reconfiguration are established. In methodology, the formal representation of complicated system (such as KMS, software system), the automatic construction of KM and the decision-making of self-reconfiguration are provided with feasible methods. In application, the development of self-reconfiguration sub-system provides the platform for the self-reconfiguration of KMS and lays the foundation for the application of KMS.