Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Qualitative spatial reasoning: the CLOCK project
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Spatial Planning: A Configuration Space Approach
IEEE Transactions on Computers
Plastic injection mould cooling system design by the configuration space method
Computer-Aided Design
Plastic injection mould cooling system design by the configuration space method
Computer-Aided Design
Automation in the design of EDM electrodes
Computer-Aided Design
Visibility-based conformal cooling channel generation for rapid tooling
Computer-Aided Design
A new C-space method to automate the layout design of injection mould cooling system
Computer-Aided Design
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The cooling system of an injection mould is very important to the productivity of the injection moulding process and the quality of the moulded part. Despite the various research efforts that have been directed towards the analysis, optimization, and fabrication of cooling systems, support for the layout design of the cooling system has not been well developed. In the layout design phase, a major concern is the feasibility of building the cooling system inside the mould insert without interfering with the other mould components. This paper reports a configuration space (C-space) method to address this important issue. While a high-dimensional C-space is generally required to deal with a complex system such as a cooling system, the special characteristics of cooling system design are exploited in the present study, and special techniques that allow C-space computation and storage in three-dimensional or lower dimension are developed. This new method is an improvement on the heuristic method developed previously by the authors, because the C-space representation enables an automatic layout design system to conduct a more systematic search among all of the feasible designs. A simple genetic algorithm is implemented and integrated with the C-space representation to automatically generate candidate layout designs. Design examples generated by the genetic algorithm are given to demonstrate the feasibility of the method.