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A Heuristic Scheduling Algorithm for Minimizing Makespan and Idle Time in a Nagare Cell
Author(s) -
Mr. A. M. J. Muthukumaran,
S. Muthu
Publication year - 2012
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1155/2012/895463
Subject(s) - gantt chart , cellular manufacturing , job shop scheduling , computer science , idle , scheduling (production processes) , schedule , algorithm , flow shop scheduling , group technology , heuristic , mathematical optimization , engineering , manufacturing engineering , mathematics , artificial intelligence , operating system , systems engineering
Adopting a focused factory is a powerful approach for today manufacturing enterprise. This paper introduces the basic manufacturing concept for a struggling manufacturer with limited conventional resources, providing an alternative solution to cell scheduling by implementing the technique of Nagare cell. Nagare cell is a Japanese concept with more objectives than cellular manufacturing system. It is a combination of manual and semiautomatic machine layout as cells, which gives maximum output flexibility for all kind of low-to-medium- and medium-to-high- volume productions. The solution adopted is to create a dedicated group of conventional machines, all but one of which are already available on the shop floor. This paper focuses on the development of heuristic scheduling algorithm in step-by-step method. The algorithm states that the summation of processing time of all products on each machine is calculated first and then the sum of processing time is sorted by the shortest processing time rule to get the assignment schedule. Based on the assignment schedule Nagare cell layout is arranged for processing the product. In addition, this algorithm provides steps to determine the product ready time, machine idle time, and product idle time. And also the Gantt chart, the experimental analysis, and the comparative results are illustrated with five (1×8 to 5×8) scheduling problems. Finally, the objective of minimizing makespan and idle time with greater customer satisfaction is studied through

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