The computer-assisted configuration of progressive die is a computationally mixed problem. This paper describes the progressive die design problem and reviews some existing research related to the configuration of progressive dies. It explains the model-based reasoning approach used to configure the intermediate and final solutions to the design problem. In particular, the various shape representation and spatial reasoning techniques are presented. Finally, a computer software architecture for the die design system is presented.

Precision machines are necessary to manufacture parts and subassemblies that require tight tolerances. During the design of precision machines, like any design, it is critical that the best concept is chosen in the early stages of the design process because 80% of the final cost and quality of a product are designed in at this phase. In addition, changes and optimization late in the design process have limited impact on cost and quality. Typically, during the design of precision machines, engineers and skilled machinists develop several machine concepts and down select based on heuristics and past design experience rather than quantitative measures. This paper describes a computation tool, Precision Machine Design Assistant (PMDA), which automates basic machine error simulation and concept evaluation. The tool uses a combination of machine error motion modelling and constraint-based design methods. By combining these methods in a computational environment, multiple machine concepts may be rapidly modeled, analyzed, and compared. The goal of the program is to assist the designer in the selection of a superior concept for detail design. The PMDA methods and implementation are demonstrated in an example.

Evolutionary and Adaptive strategies (ES & AS) for diverse multilevel search across a preliminary, whole-system design hierarchy defined by discrete and continuous variable parameters are described. Such strategies provide high-level decision support when integrated with preliminary design software describing the major elements of an engineering system. Initial work involving a Structured Genetic Algorithm (stGA) with appropriate mutation regimes to encourage search diversity is described and preliminary results are presented. The shortcomings of the stGA approach are identified and alternative strategies are introduced. A dual agent strategy (GAANT) involving elements of an ant colony search and an evolutionary search concurrently manipulating the discrete and continuous variable parameter sets is presented. Appropriate communication between the two search agents results in a more efficient search across the hierarchy than that achieved by the stGA, while also simplifying the chromosomal representation. This simplification allows the further development of the preliminary design hierarchy in terms of complexity. The technique therefore represents a significant contribution to configuration design where multilevel, mixed discrete/continuous parameter design problems can be prevalent.

Existing product models do not adequately support the modelling of weld products during the early design stages. A newly developed aggregate product model for welding is introduced, which forms part of CAPABLE, a concurrent engineering toolkit for machining and welding. This product model supports the representation of the design at multiple levels of detail and allows the rapid modelling of alternative designs where solid model representation is inappropriate. The potential applications of the aggregate product model in weld product design, such as the integration of joint design and weldability assessment, are discussed using simple examples. The design of weld products must consider process-dependent properties including geometry, materials combinations, and weld joint characteristics to arrive at a near-optimal configuration. The object-oriented and feature-based model structure of CAPABLE enhances the design process by the automatic generation of compatible options and allows rapid design evaluation. The aggregate product model provides the input data necessary for tasks like process selection, optimization, process sequencing, fixture design and welding orientation selection. The main advantage of this product model over traditional CAD environments is that planning of the welding and fabrication operations can start during the conceptual and embodiment stages of the design process, thus ensuring the concurrency of design and planning tasks and resulting in product and process improvement and cost reduction.

Adaptation of design cases is usually the most challenging part in building any case-based reasoning design system. The success of the adaptation process in finding a solution for a new design problem determines the success of the entire case-based reasoning (CBR) system. The techniques used for generating design solutions have many common aspects among the various engineering design classes that make them amenable to be captured in a generic framework for an acceptable level of abstraction. This paper proposes a design-plan-oriented methodology for adapting design cases to produce a solution to a new design problem in the domain of engineering design. The proposed methodology uses multicase adaptation and case built-in adaptation knowledge to produce a design plan for a new design problem. We first define the model of case representation to work with the proposed methodology. We then define the overall structure of the procedural framework of this methodology and its subprocesses. The system is then demonstrated through an application from the structural engineering domain.