| The main goal of this research is to develop a methodology for designing an automated manufacturing process planning system by means of a knowledge-based approach for machining parts, which (1) can link directly with and apply to general CAD models; (2) can generate sufficient information regarding process planning; (3) can assist designers to overcome their lack of manufacturing knowledge; (4) can provide information to other manufacturing activities, such as NC generation, scheduling, and tooling and fixturing design.; Knowledge is represented as rules and frames using a uniform symbolic description method. The Parts descriptions can be retrieved and re-interpreted into predicate logic and Prolog automatically to permit feature recognition. The process planning system uses a blackboard software architecture, which uses explicit goals and hypotheses in the plan construction process. The decision-making logic is based on a feature-net model.; Rules are used to make tooling decisions concerning fixturing types and locating and holding surfaces. Rules are used to generate constraint relationships among processing alternatives for the various machinable features. A hierarchical search process then finds an optimal temporal clustering of processes, which efficiently generates a practical and efficient process plan while satisfying the given constraints. |
