Artificial Intelligence Based Inference Techniques for Automated Process Planning for Machined Parts

Many areas of research in manufacturing are increasingly turning to applications of Artificial Intelligence (AI). The problem of developing inference strategies for automated process planning in machining is one such area of successful application of AI based approaches. Given the high complexity of the process planning expertise, development of inference techniques for automated process planning is a big challenge to researchers. The traditional inference methods based on variant and generative approaches using decision trees and decision tables suffer from a number of shortcomings, which have prompted researchers to seek alternative approaches and turn to AI for developing intelligent inference techniques. In this article, we have reviewed, categorized and summarized the research on applications of AI for developing inference methods for automated process planning systems. We have described our ongoing research work on developing an intelligent inference strategy based on artificial neural networks for implementing machining process selection for rotationally symmetric parts.