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The Impact of Routing and Operation Flexibility on the Performance of Matrix Production Compared to a Production Line

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Advances in Production Research (WGP 2018)

Abstract

An increasing number of product variants and a decrease in demand certainty challenge manufacturing companies. Lean, flow-oriented production lines are best-practice to assure efficient production in a predictable environment. However, with the increase in complexity and uncertainty, more flexible production systems such as matrix production currently receive much attention. Having neither a common takt time nor a rigid linkage, they offer new degrees of freedom regarding process order and machine choice. This paper contributes to answering the question under which conditions a matrix production is favourable compared to a production line. To answer this question, the effects of MTTF and MTTR as driving factor to choose a matrix production over a production line are analysed. Regarding the material flow in the matrix, the benefits of routing flexibility and operation flexibility concerning throughput time, tardiness and output of the matrix production are evaluated. The results show that a rule based approach has its limits especially regarding the exploitation of operation flexibility. For low levels of routing flexibility, the rule based approach tends to generate sup-optimal solutions due to a lack of coordination between the agents.

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References

  1. Greschke, P.I.: Matrix-Produktion als Konzept einer taktunabhängigen Fließfertigung, Vulkan Verlag (2016)

    Google Scholar 

  2. Jesse, T.: Herausforderungen und Konzepte für die Großserien-Kraftfahrzeugendmontage der Zukunft (2017)

    Google Scholar 

  3. Echsler Minguillon, F., Lanza, G.: Maschinelles Lernen in der PPS. In: Wt Werkstatttechnik Online, vol. 107, pp. 630–634 (2017)

    Google Scholar 

  4. Browne, J., Dubois, D., Rathmill, K., Sethi, S.P., Stecke, K.E.: Classification of flexible manufacturing systems. FMS Mag. 2, 114–117 (1984)

    Google Scholar 

  5. Caprihan, R., Wadhwa, S.: Impact of routing flexibility on the performance of an FMS—a simulation study. Int. J. Flex. Manuf. Syst. 9, 273–298 (1997). https://doi.org/10.1023/A:1007917429815

    Article  Google Scholar 

  6. Scholz-Reiter, B., de Beer, C., Bose, F., Windt, K.: Evolution in der Logistik Selbststeuerung logistischer Prozesse. In: VDI BERICHTE, vol. 1978, p. 179 (2007)

    Google Scholar 

  7. Mahmoodi, F., Mosier, C.T., Morgan, J.R.: The effects of scheduling rules and routing flexibility on the performance of a random flexible manufacturing system. Int. J. Flex. Manuf. Syst. 11, 271–289 (1999). https://doi.org/10.1023/A:1008165212489

    Article  Google Scholar 

  8. Chan, F.T.S.: Impact of operation flexibility and dispatching rules on the performance of a flexible manufacturing system. Int. J. Adv. Manuf. Technol. 24, 447–459 (2004). https://doi.org/10.1007/s00170-003-1594-1

    Article  Google Scholar 

  9. Joseph, O.A., Sridharan, R.: Effects of routing flexibility, sequencing flexibility and scheduling decision rules on the performance of a flexible manufacturing system. Int. J. Adv. Manuf. Technol. 56, 291–306 (2011)

    Article  Google Scholar 

  10. Sharma, P., Jain, A.: Effect of routing flexibility and sequencing rules on performance of stochastic flexible job shop manufacturing system with setup times: simulation approach (2015). https://doi.org/10.1177/0954405415576060

    Article  Google Scholar 

  11. Lu, C.-L., Chiu, S.-Y., Wu, J., Chao, L.-P.: Dynamic Monte-Carlo tree search algorithm for multi-objective flexible job-shop scheduling problem. Appl. Math. Inf. Sci. 10, 1531–1539 (2016). https://doi.org/10.18576/amis/100431

    Article  Google Scholar 

  12. Scholz-Reiter, B., de Beer, C., Peters, K.: Autonomous control of shop floor logistics. Manuf. Model. Manag. Control 2004, 47 (2006)

    Google Scholar 

  13. Stricker, N., Kuhnle, A., Sturm, R., Friess, S.: Reinforcement learning for adaptive order dispatching in the semiconductor industry. CIRP Ann. (2018)

    Google Scholar 

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Correspondence to Constantin Hofmann , Nadine Brakemeier , Carmen Krahe , Nicole Stricker or Gisela Lanza .

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Hofmann, C., Brakemeier, N., Krahe, C., Stricker, N., Lanza, G. (2019). The Impact of Routing and Operation Flexibility on the Performance of Matrix Production Compared to a Production Line. In: Schmitt, R., Schuh, G. (eds) Advances in Production Research. WGP 2018. Springer, Cham. https://doi.org/10.1007/978-3-030-03451-1_16

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  • DOI: https://doi.org/10.1007/978-3-030-03451-1_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03450-4

  • Online ISBN: 978-3-030-03451-1

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