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The Throughput Rate of Multistation Production Lines with Stochastic Servers

Published online by Cambridge University Press:  27 July 2009

Abdullah Alkaff  and
Eginhard J. Muth
Abdullah Alkaff
Affiliation:
Surabaya Institute of Technology, Kampus ITS – KeputihSukolilo, Surabaya, Indonesia
Eginhard J. Muth
Affiliation:
Department of Industrial and Systems EngineeringUniversity of Florida, Gainesville, Florida 32611
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Abstract

A serial production line with an arbitrary number of stations is analyzed using the holding-time model. In contrast to Markovian state models, the holding-time model does not require the service times to be exponentially distributed. The distribution of the interdemand time at the first station is obtained as a function of the distribution of station service times which are of a general nature. The throughput rate of the line is the reciprocal of the mean interdemand time. For service times of phase type, two numerical solution methods, one exact and the other approximate, are presented. Numerical results are given for up to ten stations.

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 1 , Issue 3 , July 1987 , pp. 309 - 326
Copyright
Copyright © Cambridge University Press 1987

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References

1.Alkaff, A. (1985). The throughput rate of multistation production lines. Doctoral dissertation, Department of Industrial and Systems Engineering, University of Florida, Gainesville, FL.Google Scholar
2.Altiok, T. (1982). Approximate analysis of exponential tandem queues with blocking. European Journal of Operational Research 11: 390–397.CrossRefGoogle Scholar
3.Cox, D. R. (1955). A use of complex probabilities in the theory of stochastic processes. Proc. Cambridge Philosophical Society 51: 313–319.Google Scholar
4.Hillier, F. S., & Boling, R. W. (1967). Finite queues in series with exponential or Erlang service times: A numerical approach. Operations Research 15: 286–303.CrossRefGoogle Scholar
5.Langaris, C., & Conolly, B. (1985). Three-stage tandem queue with blocking. European Journal of Operational Research 19: 222–232.CrossRefGoogle Scholar
6.Muth, E. J. (1977). Numerical methods applicable to a production line with stochastic servers. In Neuts, M. F. (ed.), Algorithmic methods in probability (North-Holland/TIMS studies in the Management Sciences, vol. 7). Amsterdam: North-Holland, pp. 143–159.Google Scholar
7.Muth, E. J. (1984). Stochastic processes and their network representations associated with production line queuing model. European Journal of Operations Research 15: 63–83.CrossRefGoogle Scholar