Study On Collaborative Decision-making For Seru Formation And Seru Loading

Nowadays,manufacturing industry is confronted with a lot of new challenges.On the one hand,manufacturing factories are forced to compete with competitors all around the world under the influence of globalization,so they have to improve their performance on various aspects,such as cost,quality and time,in order to survive in such a tough environment.On the another hand,the increasingly improved living standard and diversified culture make more and more customers seek for personalization and customized products.As a result,market demand shows characteristics of diversified products,varied product type and fluctuant demand volume,short product life cycle,high quality,and short delivery time.For mass production factories,there is an urgent need to innovate their production mode to deal with various problems.In the 1990s,Sony proposed seru production after a reconfiguration on multi-product conveyor assembly lines.Seru,production with high efficiency and flexibility can help small-lot multi-product manufacturing factories to perform well when product type is varied and demand volume is fluctuant.Seru production has been widely spread in electronics manufacturing industry in Japan because it brought notable improvements in production efficiency,response speed,cost,profit,delivery,quality and et al.However,seru production has not yet been widely adopted by manufacturing factories out of Japan.For one thing,it is hard to access literature on seru production which is mainly published in Japanese;for another,the majority of existed literature focus on implementation experience,and the existed research results are not sufficient to form a theory and method system for seru production and a large number of key problems are still unsolved.Among key decisions unsolved in seru production research field,seru formation is the most important one for sent production system design.Seru formation determines efficiency and flexibility level of the whole production system and influences many other activities,such as workfloor delivery,production planning and scheduling.Almost all existed literature on seru formation focuses on line-seru conversion problems,while research on how to form serus without a conveyor assembly line is sparse.Therefore,this thesis studies seru formation problem from the viewpoint of resources combination.Seru formation can be treated as the supplier of productivity while seru loading can be treated as the consumer.Moreover,the frequent reconfiguration of serus caused by changes in demand always leads to adjustment of corresponding seru loading plans.With the consideration of interaction between seru formation and seru loading,they are solved concurrently in this thesis.According to the impact of different resources on productivity,serus can be classified into two categories,machine-oriented seru and multi-skilled-worker-oriented seru.As a result,the collaborative decision-making for seru formation and seru loading is solved based on machines and multi-skilled workers considering characteristics of different kinds of serus.For machine-based collaborative decision-making for seru formation and seru loading,literature and implementation cases on seru production are reviewed and analyzed firstly,and key factors,such as kanketsu,identical machines,alternative processing routes,flow time,inter-seru workload balance,and seru size,are recognized.On the basis of analysis of these factors,a nonlinear integer programming model considering identical machines,alternative processing routes,processing times,setup times,machine available capacity,demand volumes and the number of serus is formulated.Objectives of the proposed model are minimizing average workload of serus and improving workload balance among serus.Constraints on the number of machines assigned to a seru,kanketsu and available capacity of machines are also considered.In view of the NP-hard nature of the multi-objective optimization problem,an algorithm based on the non-dominated sorting genetic algorithm II is developed.Performance of the proposed mathematical model and algorithm is validated by numerical examples.Then,the impact of the number of serus on objective function values and the impact of the number of machines on kanketsu are analyzed by using numerical examples.To further verify the performance of the proposed algorithm,comparisons between it and BEA;Z-L algorithm are made.For multi-skilled-worker-based collaborative decision-making for seru formation and seru loading,literature and implementation cases on seru production are reviewed and analyzed firstly,and key factors,such as kanketsu,skill set,proficiency level,proficiency-level-based processing time,operator sharing,seru size,workload balance,are recognized.On the basis of analysis of these factors,a nonlinear integer programming model considering worker heterogeneity in skill set and proficiency level,proficiency-level-based processing time,operator sharing,demand volumes and worker available time is formulated.Objectives of the proposed model are improving workload balance among serus and workers simultaneously.Constraints on the number of workers assigned to a seru,the number of tasks of a batch assigned to a worker,kanketsu and available time of workers are also considered.In view of the NP-hard nature of the multi-objective optimization problem,an algorithm based on the non-dominated sorting genetic algorithm II is developed.Performance of the proposed mathematical model and algorithm is validated by numerical examples.Then,the impact of worker heterogeneity and proficiency level on workload balance is analyzed by using numerical examples.To further verify the performance of the proposed algorithm,a comparison between it and an algorithm developed based on PSO algorithm is made.The mathematical models and algorithms proposed for the collaborative decision-making for seru formation and seru loading and the analysis results provide theoretical foundations for researches on relative decisions.Results of this research are favourable for enriching theory and method system of seru production,and provide decision support for manufacturing factories intend to implement seru production.