An integrated VPRS model and its application in manufacturing process knowledge acquisition

Knowledge acquisition is a critical and difficult issue in the knowledge-based and intelligent process planning systems. In manufacturing process planning, when confronted with the uncertain problems, experts often make decisions based on different decision thresholds. Knowledge acquisition has been inclined towards a more difficult but more necessary strategy to obtain such thresholds, including confidence level, supportability and strength of the process rules. In this paper, an innovative method that integrates fuzzy clustering and VPRS (Variable Precision Rough Set) is put forward. It can better aid knowledge discovery in process planning to achieve the thresholds compared with the conventional fuzzy decision technique. Finally, the proposed methodology is evaluated on the case of complexity analysis of manufacturing parts. The analysis results show that it is capable of not only simplifying knowledge acquisition but also satisfying the practical manufacturing requirements appropriately.