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Performance Prediction and Evaluation Based on the Variability Theory in Production Lines Using ARENA Simulation

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Abstract

The level of performance is an important aspect of the design and control in a production line. Particularly, the level of performance of variable production line (VPL) is one of the most important influential factors in deciding production line’s flexibility. The majority of the existing solution methods for performance prediction and evaluation problems of VPL assume that the processing times, time between failures and repair times are deterministic or exponentially distributed, which could not be applied to all the problems in real cases. This paper relaxes these restrictions by proposing an ARENA simulation model for performance prediction and evaluation based on the variability theory in Factory Physics. The variable properties of time interval between product arrivals and VPL are simulated, which combining with the coefficients of variations, are presented. Through the simulation, how the variable factors influence the performance of VPL is demonstrated. The methodology in this paper can be applied to effectively predict and evaluate the performance in VPL in various production scenarios before implementing them in reality.

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Acknowledgements

The authors are thankful to the anonymous reviewers for their constructive and helpful comments that have led to this much improved manuscript. This work was supported by the National Natural Science Foundation of China (Grant: 71671026) and Science & Technology Department of Sichuan Province (Grant: 18ZDYF2575).

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Authors and Affiliations

  1. School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu, People’s Republic of China

    Changjun Li, Jingye Liu & Bo Li

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  1. Changjun Li
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  2. Jingye Liu
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  3. Bo Li
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Correspondence to Bo Li.

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Li, C., Liu, J. & Li, B. Performance Prediction and Evaluation Based on the Variability Theory in Production Lines Using ARENA Simulation. Wireless Pers Commun 103, 897–920 (2018). https://doi.org/10.1007/s11277-018-5486-y

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