The optimal parameter design for a welding unit of manufacturing industry by Taguchi method and computer simulation

Seyed Mojib Zahraee, Ali Chegeni, Arshin Toghtamish

Abstract


Purpose: Manufacturing systems include a complicated combination of resources, such as materials, labors, and machines. Hence, when the manufacturing systems are faced with a problem related to the availability of resources it is difficult to identify the root of the problem accurately and effectively. Managers and engineers in companies are trying to achieve a robust production line based on the maximum productivity. The main goal of this paper is to design a robust production line, taking productivity into account in the selected manufacturing industry.

Design/methodology/approach: This paper presents the application of Taguchi method along with computer simulation for finding an optimum factor setting for three controllable factors, which are a number of welding machines, hydraulic machines, and cutting machines by analyzing the effect of noise factors in a selected manufacturing industry.

Findings and Originality/value: Based on the final results, the optimal design parameter of welding unit of in the selected manufacturing industry will be obtained when factor A is located at level 2 and B and C are located at level 1. Therefore, maximum productive desirability is achieved when the number of welding machines, hydraulic machines, and cutting machines is equal to 17, 2, and 1, respectively. This paper has a significant role in designing a robust production line by considering the lowest cost and timely manner based on the Taguchi method.


Keywords


Taguchi method, computer simulation, optimal parameter design, manufacturing industry

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DOI: http://dx.doi.org/10.3926/jiem.1425


Licencia de Creative Commons 

This work is licensed under a Creative Commons Attribution 4.0 International License

Journal of Industrial Engineering and Management, 2008-2019

Online ISSN: 2013-0953; Print ISSN: 2013-8423; Online DL: B-28744-2008

Publisher: OmniaScience