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The Output Process of Serial Production Lines of General Machines with Finite Buffers

Author

Listed:
  • Kevin B. Hendricks

    (School of Business, The College of William and Mary, Williamsburg, Virginia 23187)

  • John O. McClain

    (The Johnson Graduate School of Management, Malott Hall, Cornell University, Ithaca, New York 14853)

Abstract

Little is known about the interaction among manufacturing subsystems in a factory. The output of one manufacturing subsystem is usually the input to one or more others in the plant. For example, a production line may provide input to another manufacturing stage, a shipping system, or an automated parts conveyor. In all of these examples, the characteristics of the output from the production line can affect the subsequent process. This paper examines the output process of a serial production line of N machines with general processing time distributions and finite buffer capacities. Simulation is used to examine the effects of line length, buffer capacity, and buffer placement on the inter-departure distribution and correlation structure (autocorrelation function) of the output process of the production line. Results from this analysis are useful in setting production line design parameters and in determining the extent to which buffer placement can be used to control the variability of the output process, and thereby the amount of work-in-process present in downstream subsystems. Additional insights are provided to help explain why small buffers in production lines are normally adequate and to help us better understand the effects of buffers on tightly coupled production systems. By using a variety of processing time distributions, previously unknown effects attributed to skew of processing time are revealed. Since skew can often be reduced or eliminated by operator training, these effects are of particular interest since they can help to quantify some of the benefits of training.

Suggested Citation

  • Kevin B. Hendricks & John O. McClain, 1993. "The Output Process of Serial Production Lines of General Machines with Finite Buffers," Management Science, INFORMS, vol. 39(10), pages 1194-1201, October.
    • Handle: RePEc:inm:ormnsc:v:39:y:1993:i:10:p:1194-1201
    DOI: 10.1287/mnsc.39.10.1194
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    Citations

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    Cited by:

    1. Nan Chen & Yuan Yuan & Shiyu Zhou, 2011. "Performance analysis of queue length monitoring of M/G/1 systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(8), pages 782-794, December.
    2. Stephen G. Powell & Kenneth L. Schultz, 2004. "Throughput in Serial Lines with State-Dependent Behavior," Management Science, INFORMS, vol. 50(8), pages 1095-1105, August.
    3. Hadjinicola, George C. & Soteriou, Andreas C., 2003. "Reducing the cost of defects in multistage production systems: A budget allocation perspective," European Journal of Operational Research, Elsevier, vol. 145(3), pages 621-634, March.
    4. Chen, Chin-Tai & Yuan, John, 2004. "Transient throughput analysis for a series type system of machines in terms of alternating renewal processes," European Journal of Operational Research, Elsevier, vol. 155(1), pages 178-197, May.
    5. G C Hadjinicola, 2010. "Manufacturing costs in serial production systems with rework," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(2), pages 342-351, February.
    6. Tan, Baris, 1997. "Variance of the throughput of an N-station production line with no intermediate buffers and time dependent failures," European Journal of Operational Research, Elsevier, vol. 101(3), pages 560-576, September.
    7. John O. McClain & Kenneth L. Schultz & L. Joseph Thomas, 2000. "Management of Worksharing Systems," Manufacturing & Service Operations Management, INFORMS, vol. 2(1), pages 49-67, July.
    8. Manafzadeh Dizbin, Nima & Tan, Barış, 2020. "Optimal control of production-inventory systems with correlated demand inter-arrival and processing times," International Journal of Production Economics, Elsevier, vol. 228(C).
    9. Papadopoulos, H. T., 1998. "An approximate method for calculating the mean sojourn time of K-station production lines with no intermediate buffers," International Journal of Production Economics, Elsevier, vol. 54(3), pages 297-305, May.
    10. Tan, Baris, 1998. "Effects of variability on the due-time performance of a continuous materials flow production system in series," International Journal of Production Economics, Elsevier, vol. 54(1), pages 87-100, January.
    11. Nima Manafzadeh Dizbin & Barış Tan, 2019. "Modelling and analysis of the impact of correlated inter-event data on production control using Markovian arrival processes," Flexible Services and Manufacturing Journal, Springer, vol. 31(4), pages 1042-1076, December.
    12. Lutz, Christian M. & Roscoe Davis, K. & Sun, Minghe, 1998. "Determining buffer location and size in production lines using tabu search," European Journal of Operational Research, Elsevier, vol. 106(2-3), pages 301-316, April.
    13. Kalir, Adar A. & Sarin, Subhash C., 2009. "A method for reducing inter-departure time variability in serial production lines," International Journal of Production Economics, Elsevier, vol. 120(2), pages 340-347, August.

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