A case-adaptive assembly planning system

Currently, a case adaptive assembly planning system (CAAPS) which integrates neural computing techniques and rule-based systems has been developed. The neural network computing captures designer´s design concept and self-organizes similar experienced designs. The CBAPM (CLIPS-based assembly planning module), a component of CAAPS, generates a task-level assembly plan automatically. The design concept is expressed by a standard pattern format representing components´ 3D geometry. A feature-based model translates the conceptual design into a preliminary boundary representation (B-rep). The neural-network design module is to augment the designer´s memory when designing an assembly system. The purpose of the CAAPS is to provide an engineer with an environment in which he/she can think of assembly in terms of high level features and synthesize such assembly rapidly. At all stages of the design process the designer can consult the Design Cluster Memory (DCM) and Plan Cluster Memory (PCM) to see what “experience” knows of similar assembly. Efficient use of prior experiences is emphasized