Study and application of scheduling method for just-in-time production in flexible job shops

The unsmooth job flow between the production shops along a manufacturing chain is a problem commonly seen in industries due to the inconsistency in processing speed and delivery between the chained production shops. With many factors involved in the coordination between production shops, the problem is complex and few solutions have been provided to date. This study presents an approach able to solve this problem by implementing time-based manufacturing that enables the speed and timing of each shop's job outflow to match those of its successor shop's job inflow. The proposed method is composed of offline schedule making and online job processing control. It aims to complete each job in a just-in-time (JIT) manner at the time the job is wanted by the next production shop. Designed upon a flexible job shop environment, which is easy to be transformed into other shops with similar characters, the proposed method is expected to be widely applicable to JIT scheduling problems. An industrial case study is made and results show that the proposed method has a strong ability in JIT job completion, tardy job prevention and makespan reduction.

[1]  Cheng Wu,et al.  Structural Property and Meta-heuristic for the Flow Shop Scheduling Problem , 2009 .

[2]  Mitsuo Gen,et al.  A hybrid of genetic algorithm and bottleneck shifting for multiobjective flexible job shop scheduling problems , 2007, Comput. Ind. Eng..

[3]  Soo Wook Kim,et al.  Manufacturing Practices and Strategy Integration: Effects on Cost Efficiency, Flexibility, and Market-Based Performance , 2005, Decis. Sci..

[4]  Dug Hee Moon,et al.  A simulation study for dynamic scheduling in a hybrid assembly/job shop considering the JIT context , 1998 .

[5]  Jie Gao,et al.  A Hybrid of Genetic Algorithm and Bottleneck Shifting for Flexible Job-Shop Scheduling Problem , 2005 .

[6]  James C. Chen,et al.  A study of the flexible job shop scheduling problem with parallel machines and reentrant process , 2008 .

[7]  D. Challis,et al.  Impact of technological, organizational and human resource investments on employee and manufacturing performance: Australian and New Zealand evidence , 2005 .

[8]  Süleyman Tüfekci,et al.  Dynamic programming solution to the batching problem in just-in-time flow-shops , 2006, Comput. Ind. Eng..

[9]  Daniel A. Finke,et al.  Multiple machine JIT scheduling: a tabu search approach , 2007 .

[10]  Xi Lifeng,et al.  A filtered-beam-search-based heuristic algorithm for flexible job-shop scheduling problem , 2008 .

[11]  Nhu Binh Ho,et al.  Evolving dispatching rules using genetic programming for solving multi-objective flexible job-shop problems , 2008, Comput. Ind. Eng..

[12]  Jung Woo Jung,et al.  Flowshop-scheduling problems with makespan criterion: a review , 2005 .

[13]  Faizul Huq,et al.  The analysis of scheduling rules in a flexible job shop with non-zero setup costs , 2009 .

[14]  Ramón Alvarez-Valdés,et al.  A heuristic to schedule flexible job-shop in a glass factory , 2005, Eur. J. Oper. Res..