Process Planning and Configuration Selection for Reconfigurable Manufacturing System A Simulation Approach

Abstract

Selection of manufacturing system configuration includes the machine arrangements, operation newlineassignment, and equipment selection have a major impact on performance mainly while newlineconsidering the novel paradigm named as Reconfigurable Manufacturing Systems. newlineReconfigurable Manufacturing Systems is capable of reconfiguring the hardware resources and newlinecontrolling the resources of organizational and functional level; this further allows the newlineimmediate scaling in product functionality and capacity for any sudden changes in regularity newlinerequirements or changes in the market. The main aim of the RMS objective is to provide newlinefunctionality and capacity when needed with optimal reconfiguration effort. Rules-guided newlineplanning and stochastic analysis play an important role in producing the multiple parts which newlinefurther aims to achieve the RMS-related objective. In the past several algorithms have been newlineproposed to achieve the RMS-related objectives, however, these mechanism lacks optimality; newlinehence this research aims to develop an evolutionary approach for multipart selection. Moreover, newlinethis research work is divided into two parts where the first part of the research develops an newlineoptimized RMS that aims to reduce the configuration cost through optimal task scheduling. newlineMoreover, this approach is backed by an evolutionary algorithm to find the optimal solution that newlineutilizes machines over the operation set considering each machine part, and later the optimal newlinesolution is found through the probable assignment. Further, model evaluation is carried out newlinethrough a case study by comparing it with the existing model. The second part of the research newlineproposes DSMO (Dual Step Metaheuristic Optimized)-approach that solves the two distinctive newlineissues; these are carried out in two-step. The first step optimizes the change reaction in the newlinedesigned product and the second step optimized layout is developed for machine selection newlinethrough optimization of machine position and its floor arrangement. DSMO is evaluated by newlinecomparing with the existing model of ANC90 f