Formulations, Features of Solution Space, and Algorithms for Line-PureSeruSystem Conversion

Wei Sun,Ke Ma,Yang Yu,Qianqian Li,Chunhui Huo

doi:10.1155/2016/9748378

Abstract

The line-seruconversion is usually used to improve productivity, especially in volatile business environment. Due to the simplicity, most researches focused on line-pureserusystem conversion. We summarize the two existing models (i.e., a biobjective model and a single-objective model) of line-pure system conversion and formulate the three other usually used single-objective models in an integrated framework by combining evaluated performances and constraints. Subsequently, we analyze the solution space features of line-pureserusystem conversion by dividing the whole solution space into several subspaces according to the number ofserus. We focus on investigating the features betweenCmax(and TLH) and subspaces. Thirdly, according to the distinct features betweenCmax(and TLH) and subspaces, we propose four effective algorithms to solve the four single-objective models, respectively. Finally, we evaluate the computational performance of the developed algorithms by comparing with enumeration based on extensive experiments.

Highlights

The seru production, conceived at Sony, is an innovation of assembly system used widely in the Japanese electronics industry and recognized a new production pattern
We focus on investigating the features between Cmax and total labor hours (TLH) and subspaces with different number of serus
We focus on analyzing the features between Cmax and subspaces with different number of serus

Summary

Introduction

The seru production, conceived at Sony, is an innovation of assembly system used widely in the Japanese electronics industry and recognized a new production pattern. Seru is an assembly unit including several simple equipment and one (or more) multiskilled operator(s). Worker(s) must be multiskilled [1,2,3,4] because workers need to operate most or all the processes of production. There are three types of seru: divisional seru, rotating seru, and yatai [5, 6]. Tasks are divided into different sections and workers are partially cross-trained. Workers in rotating seru or yatai are completely cross-trained and do all tasks. In this research, rotating serus or yatai are considered

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Results

Conclusion