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.
Highlights
In the manufacturing industry with complex processes, managers and engineers are seeking to find methods for eliminating the common problems in production lines such as bottlenecks and waiting times (Zahraee, Golroudbary, Hashemi, Afshar & Haghighi, 2014)
In this study the behavior of the welding unit of manufacturing industry was simulated and the model outputs were used as the raw data of Taguchi approach
The authors suggested the design of a robust production line, which takes productivity into account in the welding unit of a selected manufacturing industry
Summary
In the manufacturing industry with complex processes, managers and engineers are seeking to find methods for eliminating the common problems in production lines such as bottlenecks and waiting times (Zahraee, Golroudbary, Hashemi, Afshar & Haghighi, 2014) This is due to the fact that all of these kinds of problems impose extra cost on the companies. Discrete-event simulation modeling is a popular method for predicting the performance of complex systems with complex processes, systems that include random phenomena This is where the design of simulation experiments plays a leading role. The novelty of this study lies on integration of simulation and Taguchi method in a Welding Unit of Manufacturing Industry which will lead to a predictable model for optimization of the best scenario for the production line considering two perspectives of controllable and noise factors
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