An integrated approach to determining the sequence of machining operations for prismatic parts with interacting features

This paper proposed a framework for integrating artificial intelligence (AI) techniques and mechanistic models in the task of generating process plans for prismatic parts. The main issue of process planning addressed in this paper is the determination of the operation sequence for mechanical parts containing interacting features where machining of one feature might adversely affect the surface quality of other features. The informed graph-search strategy in AI is used to achieve the function of operation sequence planning. The search graph is built by considering alternative machining operations in converting a blank stock into the final part configuration. Several heuristic functions concerning machining practices are developed to help to reduce the complexity of the search graph. Mechanistic models of different interaction machining situations are also considered to help the graph-search process so that the process plan generated can ensure the machining of high-quality mechanical parts. this idea of incorporating mechanistic models in operation sequence planning activities makes it possible to build in surface-quality considerations at the early process-planning stage.