Feature clustering based approach for generation of reconfigurable machining process plan with kinematic configuration

Abstract

Reconfigurable manufacturing systems (RMS) found a novel manufacturing model of mass customization and co-evolution and are measured as the prospect of manufacturing because of their variable and adjustable nature. As the product of design and its manufacturing abilities are narrowly related, the manufacturing system is anticipated to be customizable to accommodate for all the design modifications at any granularity level from machining to product assembly. This research work is based on mass customization and co-evolution concepts for RMS and generates a framework for reconfigurable process planning of the whole part family instead of single part variant. The part variety decomposition model (PVDM), developed by Qing’s, is used with reconfigurable machining operation plans (RMOPs) developed in matlab by using the feature clustering from models and cutting tool charts data and precedence relationships (PRs) developed for part family. To extract the configurations of part and RPP, for part variant of the same part family dynamic constraint satisfaction problem (DCSP) in constraint logic programming (CLP) language Eclipse is used. The data obtained from DCSP is then used to develop process plan and kinematic configurations for the required part variant of the part family.