A Markovian model of asynchronous multi-stage manufacturing lines fabricating discrete parts

被引：8

作者：

Magnanini M.C. ^{[1
]}

Tolio T. ^{[1
]}

机构：

[1] Politecnico di Milano, Dipartimento di Meccanica, via La Masa 1, Milano

来源：

Journal of Manufacturing Systems | 2023年 / 68卷

关键词：

Continuous model; Discrete flow; Manufacturing systems; Markov modeling; Performance evaluation;

D O I：

10.1016/j.jmsy.2023.04.006

中图分类号：

学科分类号：

摘要：

Asynchronous serial manufacturing lines that fabricate discrete parts are traditionally used in mass production, which represents a key sector in the global economy. Recent technological solutions for the modularization and standardization of manufacturing stations have led to this type of manufacturing system being reconfigured more often than in the past. Therefore, synthetic but accurate performance-evaluation models have become relevant as kernels in decision supporting tools for the continuous improvement of manufacturing systems. This paper presents a novel analytical model for the performance evaluation of asynchronous unreliable manufacturing lines fabricating discrete parts with finite buffers and deterministic processing times. This approach is based on continuous-time continuous-flow Markov chains. The general concept of operational cycles in discrete production is integrated into the modeling. The proposed model was validated using a discrete event simulation. The results demonstrate the accuracy and robustness of this model in evaluating a wide set of performance measures. The advantages of using this approach with respect to a purely continuous model were demonstrated. The applicability of the model to actual industrial scenarios was also demonstrated in a use case involving a high-volume assembly line. © 2023 The Society of Manufacturing Engineers

引用

页码：325 / 337

页数：12

共 52 条

[11]

Gu X., Modeling of reconfigurable manufacturing system architecture with geometric machines and in-stage gantries, J Manuf Syst, 62, pp. 102-113, (2022)

[12]

Magnanini M.C., Tolio T.A., Robust improvement planning of automated multi-stage manufacturing systems, Selected topics in manufacturing, pp. 61-75, (2022)

[13]

Bai Y., Tu J., Yang M., Zhang L., Denno P., A new aggregation algorithm for performance metric calculation in serial production lines with exponential machines: design, accuracy and robustness, Int J Prod Res, pp. 1-18, (2020)

[14]

Kang Y., Mathesen L., Pedrielli G., Ju F., Lee L.H., Multi-fidelity modeling for analysis and optimization of serial production lines, IEEE Trans Automat Control, (2020)

[15]

Lee J.-H., Li J., Horst J.A., Serial production lines with waiting time limits: Bernoulli reliability model, IEEE Trans Eng Manage, 65, 2, pp. 316-329, (2017)

[16]

Magnanini M.C., Tolio T., Restart policies to maximize production quality in mixed continuous-discrete multi-stage systems, CIRP Ann, (2020)

[17]

Diamantidis A., Lee J.-H., Papadopoulos C.T., Li J., Heavey C., Performance evaluation of flow lines with non-identical and unreliable parallel machines and finite buffers, Int J Prod Res, 58, 13, pp. 3881-3904, (2020)

[18]

Li C., Chang Q., Xiao G., Arinez J., Integrated process-system modeling and performance analysis for serial production lines, IEEE Robot Autom Lett, 7, 3, pp. 7431-7438, (2022)

[19]

Dallery Y., Gershwin S.B., Manufacturing flow line systems: a review of models and analytical results, Queueing Syst, 12, 1-2, pp. 3-94, (1992)

[20]

Buzacott J., Shanthikumar J., Stochastic models of manufacturing systems, (1993)

← 1 2 3 4 5 6 →