作者: Vishwa Vijay Kumar , Mayank Kumar Pandey , MK Tiwari , David Ben-Arieh , None
DOI: 10.1007/S10845-008-0175-4
关键词:
摘要: Simultaneous optimization of interrelated manufacturing processes viz. part sequencing and operation is required for the efficient allocation production resources. Present paper addresses this problem with an integrated approach Single Stage Multifunctional Machining System (SSMS), identifies best sequence available in part-mix. A mathematical model has been formulated to minimize broad objectives set-up cost time simultaneously. The proposed more realistic attributes as fixture related intricacies are also taken into account formulation. It solved by a new variant particle swarm (PSO) algorithm named Chaos embedded Taguchi (CE-TPSO) that draws its traits from chaotic systems, statistical design experiments varying acceleration coefficients (TVAC). simulated case study adopted literature effectiveness proved. results obtained different variants own compared along basic PSO Genetic Algorithm (GA) reveal superiority algorithm.