Study On Building An Intelligent Fixture Design System Based On Knowledge Engineering

Fixturing is an important manufacturing operation which contributes greatly to the production quality, cycle time, and cost. As computer technology, especially computer-aided design and manufacturing (CAD/CAM), developed, computer is utilized to inherit the knowledge and experiences and some systemic method is implemented to assist fixture design and analysis. The current research is focused on the approaches to automate the task of conceptual and detailed fixture design. Under this background, the thesis makes a point of building an intelligent fixture design system. The related research on fixture design ontology, fixture planning and fixture configuration design in a computer-aided fixture design (CAFD) system are also surveyed as follows:In order to enhance the practicability of fixture design system and improve the design process, knowledge engineering is utilized to develop the intelligent system for fixture design. CommonKADS methodology is imported to analyze the task of the fixture design and to retrieve the knowledge. Using the conceptual modeling language (CML), the knowledge model of fixture design is constructed, including domain knowledge, task knowledge and inference knowledge. The domain knowledge describes schematically the knowledge and information types concerning fixture configuration design. The task knowledge describes the functional decomposition and control strategy. The inference knowledge specifies the basic reasoning steps and inference structure. Such analysis and construction process distinguishes the knowledge types in a hierarchy, which guides us to probe into the development of the knowledge intensive system by a process comparable to software engineering. The knowledge retrieved contains not only the static knowledge, but also the organization knowledge and reasoning control knowledge concerning fixture design problem solving, which provides us with a foundation for algorithms research and knowledge system building.Reuse of design knowledge has become an urgent problem for computer-aided fixture design. Ontology is widely used to represent the conceptual model of information systems at the semantic knowledge level and makes the model reusable. Therefore an ontology based representation and inference approach on fixture design is proposed. Following the structural modeling method of CommonKADS, the fixture design knowledge ontology is established and represented by ontology modeling language OWL. The ontology is corresponding to the domain knowledge model of CommonKADS and comprises a detailed specification of the types and relations of the data involved in fixture design process. Assisted by the Protege system, the basic concepts such as fixturing feature, fixture component, relation and constraint, are defined, amongst which the layered conceptual structure are constructed. Based on the ontology, the concept of Rule-type is defined to accommodate specific design rules. The rules of CAFD are expressed in Semantic Web Rule Language (SWRL), which improves the interoperability between the rules and the ontology. The facts and rules are captured into the knowledge base with explicit semantic. This ontology has an advantage of good expansibility and can be easily transferred for reasoning.Due to the complexity of workpiece and machining process, the optimization of fixture planning is seldom researched and is often forced in fixture verification phase. The thesis presents the algorithm of fixturing surfaces grouping and selection based on Kohonen Self-Organizing Neural Network and the algorithm of optimizing locating points based on Genetic Algorithm. Artificial Neural Network is utilized to deal with the complicated influencing factors in fixturing surfaces selection to select the best fixturing surfaces. Based on the results of fixture verification, the stiffness and deformation of the workpiece is simulated. Genetic Algorithm is then adopted to optimize the combination of locating points.Fixture configuration design is the kernel of CAFD system. But the effect of existing case-based reasoning (CBR) method and generating-based method has been far from ideal. The thesis introduces the concept of typical structure to extend the conceptual model of fixture configuration design, which contains design intention and configuration information. The layered fixture configuration model is improved therefrom, so as to decompose the design problem and reuse the design elements. Furthermore, with the layered model, an approach based on graphplan algorithm for fixture configuration design is presented, which transforms the design problem into a planning problem. During design process, the typical structures and their construction order are firstly determined, forming the skeleton of fixture configuration. Then in functional unit layer underneath, planning-graph is expanded from goal states, and is searched forward to generate functional units. Because the goal-directed graphplan is applied on localized fixture configuration and is heuristically guided, the method reduces the scale of the planning graph, improves the efficiency.Based on the study above, a prototype intelligent fixture design system has been developed, which supports sub-automated mode and interactive mode of fixture design. The architecture and the developing platform are introduced. The application of the prototype system verifies the feasibility and effectiveness of the building method based on knowledge engineering.