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Publication Type : Journal Article
Thematic Areas : Wireless Network and Application
Publisher : ARPN Journal of Engineering and Applied Sciences, Asian Research Publishing Network
Source : ARPN Journal of Engineering and Applied Sciences, Asian Research Publishing Network, Volume 11, Number 9, p.6082-6086 (2016)
Campus : Coimbatore
School : School of Engineering
Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)
Department : Mechanical Engineering, Center for Computational Engineering and Networking (CEN)
Year : 2016
Abstract : In recent days many business organizations make huge investment in establishing their shop floors, installing most mechanized machines. These mechanized machines ought to operate in tandem with other machines, whose productivity level are usually different, which leads to individual machines working in maximum efficiency and the overall shop floor working in sub-optimal level. A spool shop assembles flanges, valves and nozzles to lengthier pipe, which are used in the construction of power plant, petroleum refinery, and cement plant. Longer cycle time at different work stations, lengthier job queue waiting for processing, high level of work-in-progress are inherent issues in a spool shop. Individual machines operating at maximum efficiency without analyzing the flow metrics in a spool shop leads to bottleneck. Current study, aims at spotting and decongesting the bottle neck at various machines, improve the output of the spool shop and optimize individual machine utilization. Four simulation models are developed using ARENA and each one of them are evaluated on the following metrics: Output from spool shop per time period, utilization of individual machines per time period, value added time per unit of pipe, average queue length at each machine, average waiting time of a pipe and work-in-progress. First model depicts the data captured in the existing spool shop. In second model, high priority is assigned to the jobs that ought to be further processed in shot blasting machine and heat treatment furnace, thus minimizing the wait time. In third model, a modification is suggested to the existing annealing process, where the job is allowed to cool outside the furnace, thus making the furnace available for the next job. Forth model uses the priority rule in the suggested modified model. In all these models, inter-arrival time of job from storage yard to spool shop is maintained constant. Evaluating each model against performance statistics and queue statistics helps rank models based on each metrics. Models with high priority for further processing make use of single piece flow, a proven lean principle technique that has enhanced the overall efficiency. This eventually motivates practicing shop floor manager to incorporate flow metrics in designing the layout and machine capacity for optimal overall utilization. © 2006-2016 Asian Research Publishing Network (ARPN). All rights reserved.
Cite this Research Publication : Sathishkumar V. R., Dr. Anbuudayasankar S. P., and M. Thennarasu, “Design and Development of Simulation based Model to Rank Job Flow Strategies”, ARPN Journal of Engineering and Applied Sciences, vol. 11, pp. 6082-6086, 2016.