An efficient simulation optimization methodology to solve a multi-objective problem in unreliable unbalanced production lines

Motlagh, Maedeh Mosayeb; Azimi, Parham; Amiri, Maghsoud; Madraki, Golshan

doi:10.1016/j.eswa.2019.112836

Cited by 25 publications

(12 citation statements)

References 93 publications

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“…Durieux and Pierreval [37] introduced a meta-model using regression for a system involving logistics equipment in an automated line composed of parallel machines, and they analyzed the effects of design factors on system efficiency using the meta-model. Recently, Motlagh et al [38] developed a meta-model for evaluating throughput in unreliable, unbalanced serial lines, and applied the meta-model to optimization problems. In addition, Dengiz and Akbay [39], Um, Cheon and Lee [40], Dengiz, Tanselİç, and Belgin [41], and others investigated meta-modelling methods using regression methods in various manufacturing system design problems.…”

Section: Meta-modelingmentioning

confidence: 99%

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Automotive Body Shop Design Problems Using Meta-Models Considering Product-Mix Change and Reconfiguration Strategy

2021

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The estimation of production rate (or throughput) is important in manufacturing system design. Herein, we consider the manufacturing system of an automotive body shop in which two types of car are produced, and one car (engine car) is substituted by the other car (electric car) gradually. In this body shop, two different underbody lines are installed because the underbody structures of the two types of cars differ completely; however, the side body line and main body line are shared by the two cars. Furthermore, we assume that the underbody lines are reconfigurable based on an increase in the product mix of the electric car. A simulation-based meta-model, which is in the form of a quadratic polynomial function, is developed to estimate the production rate. In the meta-modelling process, we group some buffer locations and represent them as one variable to reduce the number of variables included in the meta-model. Subsequently, the meta-models have been used to optimize two types of buffer allocation problems, and optimal solutions are obtained easily.

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Section: Meta-modelingmentioning

confidence: 99%

“…As described in Section 2.2, the most widely used meta-models in manufacturing system design problems are regression models [36][37][38][39][40][41]. In this study, the quadratic polynomial model was used.…”

Section: Shape Determination Of Meta-modelmentioning

confidence: 99%

Automotive Body Shop Design Problems Using Meta-Models Considering Product-Mix Change and Reconfiguration Strategy

2021

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“…By dividing the problems into local and global optimization category, they further classified on the basis of discrete or continuous nature. Maedeh et al [26] solved a multi-objective problem using a hybrid of SO with regression analysis for unreliable and unbalanced production lines. In a recent review, classified applications of simulation optimization to supply chain problems in general with focus on resilience was found.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation Optimization of Manufacturing Takt Time for a Leagile Supply Chain with a De-coupling Point

Pattanaik¹

2021

Int J Ind Eng Manag

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“…Several approaches can be found for obtaining the metamodels of performance indicators: neural networks applied to asynchronous lines in series and with failures [18]; 2 K experimental design combined with simulation [19]; fractional factorial designs [20] to obtain the production rate of a line with assembly and failures; response surface methods to obtain a model for production in an unreliable system [21]. A general conclusion is that models with interactions between buffers predict T h, T C, or W IP more accurately than linear models.…”

Section: Previous Workmentioning

confidence: 99%

Buffer allocation problem in a shoe manufacturing line: A metamodeling approach

Vázquez

Hernández-González

Vázquez

et al. 2021

Rev.Fac.Ing.Univ.Antioquia

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Footwear production is subject to the variability inherent in any process, and producers often need to apply tools that allow them to make the right decisions. This work documents the process to optimize the buffer allocation in a shoe manufacturing line minimizing the cycle time in the system, applying a metamodeling approach. It was found that the Front sewing operation, and the interaction between the Lining sewing operation and the assembly operation have the greatest effect on the flow time of the product within the process; the optimum assignment of spaces follows a non-uniform arrangement on the line saturating the slower stations; the cycle time follows a non-linear behavior vs. the total number of spaces (N) in the line. For a certain value of N, the cycle time reaches a minimum value.

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An efficient simulation optimization methodology to solve a multi-objective problem in unreliable unbalanced production lines

Cited by 25 publications

References 93 publications

Automotive Body Shop Design Problems Using Meta-Models Considering Product-Mix Change and Reconfiguration Strategy

Automotive Body Shop Design Problems Using Meta-Models Considering Product-Mix Change and Reconfiguration Strategy

Simulation Optimization of Manufacturing Takt Time for a Leagile Supply Chain with a De-coupling Point

Buffer allocation problem in a shoe manufacturing line: A metamodeling approach

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