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A review of intelligent optimization for group scheduling problems in cellular manufacturing

工程管理前沿:英文版 2023年第3期10卷 406-426页

作者： Yuting WANG Yuyan HAN Dunwei GONG Huan LI School of Computer Science Liaocheng UniversityLiaocheng 252059China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China

Given that group technology can reduce the changeover time of equipment,broaden the productivity,and enhance the flexibility of manufacturing,especially cellular manufacturing,group scheduling problems(GSPs)have elicited considerable attention in the academic and industry practical literature.There are two issues to be solved in GSPs:One is how to allocate groups into the production cells in view of major setup times between groups and the other is how to schedule jobs in each group.Although a number of studies on GSPs have been published,few integrated reviews have been conducted so far on considered problems with different constraints and their optimization methods.To this end,this study hopes to shorten the gap by reviewing the development of research and analyzing these problems.All literature is classified according to the number of objective functions,number of machines,and optimization algorithms.The classical mathematical models of single-machine,permutation,and distributed flowshop GSPs based on adjacent and position-based modeling methods,respectively,are also formulated.Last but not least,outlooks are given for outspread problems and problem algorithms for future research in the fields of group scheduling.

关键词： cellular manufacturing group scheduling flowshop literature review

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A New Human-Robot Collaboration Assembly System for cellular manufacturing

A New Human-Robot Collaboration Assembly System for Cellular...

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第三十届中国控制会议

作者： Jeffrey Too Chuan Tan Tamio Arai Intelligent Systems Division Department of Precision EngineeringSchool of EngineeringThe University of Tokyo113-8656Japan

cellular manufacturing meets the diversified production and quantity requirements flexibly.However,its efficiency mainly depends on the operators’ working performance.In order to improve its efficiency,an effective assembly-support system is required to assist operators during the assembly process.In this paper,a multi-modal assembly-support system(MASS) was proposed,which aims to support operators from both informational aspect and physical aspect.To protect operators in MASS system,several safety designs in both hardware and control levels were also discussed.With the informational support and physical support from the MASS system,the assembly complexity and the operators’ burden are reduced.To evaluate the effect of MASS,a group of operators were required to execute a cable harness task.From the experimental results,it can be concluded that by using this system,the operators’ assembly performance was improved,and the efficiency of the cellular manufacturing was also improved.

关键词： Human-Robot Collaboration cellular manufacturing Safety Strategy

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Solving the rotating seru production problem with dynamic multi-objective evolutionary algorithms

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Journal of Management Science and Engineering 2022年第1期7卷 48-66页

作者： Feng Liu Kan Fang Jiafu Tang Yong Yin School of Management Science and Engineering Dongbei University of Finance and EconomicsDalian116025China College of Management and Economics Tianjin UniversityTianjin300072China Graduate School of Business Doshisha UniversityKyoto602-8580Japan

Today's volatile market conditions in electronic industries have lead to a new production system,seru(which is the Japanese pronunciation for cell),and has been widely implemented in hundreds of Japanese and other Asia companies.In particular,the rotating seru has been widely implemented,where workers are fully cross-trained with the same skill level but may be different on the proficiency of performing tasks.The rotating seru production problem,which determines the rotating sequence of workers as well as the assembling sequence of jobs,is difficult to solve due to conflicting objectives and dynamic release of customer demands.To solve this problem,we propose a dynamic multiobjective NSGA-II based memetic algorithm.Moreover,to preserve desirable population diversity and improve the searching efficiency,we propose different problem-specific evolutionary strategies.Finally,we test the performance of our proposed memetic algorithm with other state-of-the-art multi-objective evolutionary algorithms and demonstrate the effectiveness of our proposed algorithm.

关键词： cellular manufacturing Assembly Rotating seru Dynamic multi-objective optimization Evolutionary algorithms

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Is Full Skill the Best Configuration for Seru Production System?

Is Full Skill the Best Configuration for Seru Production Sys...

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第30届中国控制与决策会议

作者： Wang,Ye Tang,Jiafu School of Management Science and Engineering Dongbei University of Finance and Economics

Seru production system（SPS） is now widely adopted in Japanese manufacturing firms to deal with the dynamic uncertain demand. Multi-skilled workers and compact layout make SPS takes the advantage of both efficiency and flexibility. In this paper, we compared the fulfill rate of three skill levels of SPS（single-skilled, long chain two-skilled and full-skilled）. The purpose of this paper is to testify which skill level performs best for implementing SPS under fluctuated demand. On this basis, we consider the efficiency decline factor（EDF） which represents the processing time of a worker will be longer when he serves more product types. Scenario decomposition method is adopted to estimate the fulfill rate of three skill-leveled SPS. Numerical experiments show that fulfill rate of long chain two-skilled SPS is almost the same as full-skilled SPS, while single-skilled SPS’ fulfill rate decline significantly with the growing of demand fluctuation. Moreover, with considering of EDF, long chain two-skilled SPS performs the best among them.

关键词： Seru production system cellular manufacturing multi-skilled workers long chain training

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