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    Application of Petri nets towards improved utilization of machines in job shop manufacturing environments

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    Date
    2017
    Author
    Pachpor, Pravin S.
    Shrivastava, R.L.
    Seth, Dinesh
    Pokharel, Shaligram
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    Abstract
    Purpose - The purpose of this paper is to demonstrate the use of Petri nets in a job shop setup for the improvement in the utilization of machines. Design/methodology/approach - The study discusses concepts such as reachable state, token and matrix equations set, and demonstrates the improvements in machines' utilization in a job shop. It makes use of algorithms to generate reachable markings to obtain utilization. The study not only describes the application of theory, but also extends the body of knowledge on Petri nets and job shops. Findings - In this study, machines' utilization has been studied in a job shop with six machines and eight products. The study finds that substantial utilization improvement in job shop set up can be obtained through the application of Petri nets. The study also exposes that Petri nets are mostly used for machines, jobs and tools scheduling problems, but its use in machines' utilization is neglected. The framework and application presented here along with generalizable findings, is the first to report about machine utilization improvement in job shop manufacturing environment. Practical implications - Job shops are characterized by high unit production cost, low investments, low volume and high variety, complex flows, flexible and skilled work force, general purpose machines, high material handling; resulting in poor utilization of machines. Therefore, the findings of this study can help in reducing such costs through better machine utilization. This can help in increasing the competitiveness of the companies. Originality/value - The contribution of study lies in investigating and improving stage wise utilization in a job shop setup. It has never been reported before. Emerald Publishing Limited.
    DOI/handle
    http://dx.doi.org/10.1108/JMTM-05-2016-0064
    http://hdl.handle.net/10576/36677
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    • Mechanical & Industrial Engineering [‎1460‎ items ]

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