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Probability masses fitting in the analysis of manufacturing flow lines

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  • Jean-Sébastien Tancrez
  • Philippe Chevalier
  • Pierre Semal

Abstract

The analysis of manufacturing systems with finite capacity and with general service time distributions is made of two steps: the distributions have first to be transformed into tractable phase-type distributions, and then the modified system can be analytically modelled. In this paper, we propose a new alternative in order to build tractable phase-type distributions, and study its effects on the global modelling process. Called “probability masses fitting” (PMF), the approach is quite simple: the probability masses on regular intervals are computed and aggregated on a single value in the corresponding interval, leading to a discrete distribution. PMF shows some interesting properties: it is bounding, monotonic, refinable, it approximates distributions with finite support and it conserves the shape of the distribution. With the resulting discrete distributions, the evolution of the system is then exactly modelled by a Markov chain. Here, we focus on flow lines and show that the method allows us to compute upper and lower bounds on the throughput as well as good approximations of the cycle time distributions. Finally, the global modelling method is shown, by numerical experiments, to compute accurate estimations of the throughput and of various performance measures, reaching accuracy levels of a few tenths of a percent. Copyright Springer Science+Business Media, LLC 2011

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  • Jean-Sébastien Tancrez & Philippe Chevalier & Pierre Semal, 2011. "Probability masses fitting in the analysis of manufacturing flow lines," Annals of Operations Research, Springer, vol. 182(1), pages 163-191, January.
    • Handle: RePEc:spr:annopr:v:182:y:2011:i:1:p:163-191:10.1007/s10479-008-0512-1
    DOI: 10.1007/s10479-008-0512-1
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    References listed on IDEAS

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    1. Kerbachea, Laoucine & MacGregor Smith, J., 1987. "The generalized expansion method for open finite queueing networks," European Journal of Operational Research, Elsevier, vol. 32(3), pages 448-461, December.
    2. Tancrez, Jean-Sbastien & Semal, Pierre & Chevalier, Philippe, 2009. "Histogram based bounds and approximations for production lines," European Journal of Operational Research, Elsevier, vol. 197(3), pages 1133-1141, September.
    3. Papadopoulos, H. T. & Heavey, C., 1996. "Queueing theory in manufacturing systems analysis and design: A classification of models for production and transfer lines," European Journal of Operational Research, Elsevier, vol. 92(1), pages 1-27, July.
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    6. Frederick S. Hillier & Ronald W. Boling, 1967. "Finite Queues in Series with Exponential or Erlang Service Times—A Numerical Approach," Operations Research, INFORMS, vol. 15(2), pages 286-303, April.
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    Cited by:

    1. Jean-Sébastien Tancrez, 2020. "A decomposition method for assembly/disassembly systems with blocking and general distributions," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 272-296, June.
    2. Alessandro Barbiero, 2022. "Discrete analogues of continuous bivariate probability distributions," Annals of Operations Research, Springer, vol. 312(1), pages 23-43, May.
    3. Alessandro Barbiero & Asmerilda Hitaj, 2022. "Approximation of continuous random variables for the evaluation of the reliability parameter of complex stress–strength models," Annals of Operations Research, Springer, vol. 315(2), pages 1573-1598, August.

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