Application of design of experiments on the simulation of a process in automotive industry

Montevechi, J. A. B.; Pinho, Alexandre Ferreira de; Leal, Fabiano; Marins, Fernando Augusto Silva

doi:10.1109/wsc.2007.4419779

Cited by 59 publications

(46 citation statements)

References 16 publications

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“…Nazzala, Mollaghasemi and Anderson (2006) integrated the design of experiment, simulation and economic analysis in the process of decision making at a semiconductor company, applying the validated technique of simulation model. The advantage of the DOE along with the computer simulation is mostly a great help to improve the performance of the simulation process, decreasing the trial and error to seek solutions (Montevechi, Pinho, Leal & Marins, 2007). A comparison of experimental designs for simulation-based symbolic regression of manufacturing systems was made by Can and Heavey (2011).…”

Section: Literature Reviewmentioning

confidence: 99%

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

Zahraee

Chegeni

Toghtamish

2016

JIEM

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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, -487-Journal of Industrial Engineering and Management -http://dx.doi.org/10.3926/jiem.1425 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.

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Section: Literature Reviewmentioning

confidence: 99%

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

Zahraee

Chegeni

Toghtamish

2016

JIEM

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“…The benefits of DOE enable the possibility of improving simulation process performance by avoiding trial-and-error searches for solutions [38]. More specifically, the use of factorial design can minimize or even eliminate the disadvantages brought about by experimenting with simulated systems instead of the real system.…”

Section: Simulated Experiments Designmentioning

confidence: 99%

Sensitivity Analysis in Discrete Event Simulation Using Design of Experiments

Montevechi¹,

Miranda²,

Friend³

2012

Discrete Event Simulations - Development and Applications

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“…Authors such as Chwif (1999) and Montevechi et al (2007) show a sequence of steps for a simulation project, countering the false idea that simulation consists only in the model's computer programming. The positioning of verification and validation activities, before the experimental phase, can be observed in Figure 1.…”

Section: Validation Of Discrete Simulation Modelsmentioning

confidence: 99%

A practical guide for operational validation of discrete simulation models

Leal

Costa²,

Montevechi

et al. 2011

Pesqui. Oper.

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ABSTRACT. As the number of simulation experiments increases, the necessity for validation and verification of these models demands special attention on the part of the simulation practitioners. By analyzing the current scientific literature, it is observed that the operational validation description presented in many papers does not agree on the importance designated to this process and about its applied techniques, subjective or objective. With the expectation of orienting professionals, researchers and students in simulation, this article aims to elaborate a practical guide through the compilation of statistical techniques in the operational validation of discrete simulation models. Finally, the guide's applicability was evaluated by using two study objects, which represent two manufacturing cells, one from the automobile industry and the other from a Brazilian tech company. For each application, the guide identified distinct steps, due to the different aspects that characterize the analyzed distributions.

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Application of design of experiments on the simulation of a process in automotive industry

Cited by 59 publications

References 16 publications

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

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

Sensitivity Analysis in Discrete Event Simulation Using Design of Experiments

A practical guide for operational validation of discrete simulation models

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