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Assessing manufacturing flow lines under uncertainties in processing time: An application based on max-plus equations, multicriteria decisions, and global sensitivity analysis

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  • Rocco, Claudio M.
  • Hernandez-Perdomo, Elvis
  • Mun, Johnathan

Abstract

In this paper, a novel application on how uncertainties in a manufacturing flow line − MFL (e.g., times required to perform an action) could be analyzed and what the benefits are of such analysis. The approach proposed investigates three main goals: i) Uncertainty analysis, ii) Stochastic dominance, and iii) Sensitivity analysis. In particular, this paper extends the application of max-plus algebra to model MFL with different flow configurations and buffer capacities and provides the approximated probability density functions (PDFs) of selected performance indicators (e.g., the total idle time in the whole line, output rates, throughputs, among others). As a result, it is possible to quantify the variability of the selected output, compare different possible configurations among MFL, choose the best one, and identify critical variables and risk drivers (e.g., the processing times that affect the most a KPI − key performance indicator). The approach, illustrated by analyzing a case study of the literature, emphasizes the benefits for a decision-maker in charge of the design or managing of the manufacturing system.

Suggested Citation

  • Rocco, Claudio M. & Hernandez-Perdomo, Elvis & Mun, Johnathan, 2021. "Assessing manufacturing flow lines under uncertainties in processing time: An application based on max-plus equations, multicriteria decisions, and global sensitivity analysis," International Journal of Production Economics, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:proeco:v:234:y:2021:i:c:s0925527321000463
    DOI: 10.1016/j.ijpe.2021.108070
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Hiba Baroud & Jose E. Ramirez‐Marquez & Kash Barker & Claudio M. Rocco, 2014. "Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows," Risk Analysis, John Wiley & Sons, vol. 34(7), pages 1317-1335, July.
    3. Chang, Ping-Chen & Lin, Yi-Kuei & Chiang, Yu-Min, 2019. "System reliability estimation and sensitivity analysis for multi-state manufacturing network with joint buffers––A simulation approach," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 103-109.
    4. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
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