Assessing the impact of reducing demand variance through improved planning on the performance of a dual resource constrained job shop. (English) Zbl 0917.90165

Fredendall, L. D.; Melnyk, S. A.

Int. J. Prod. Res. 33, No. 6, 1521-1534 (1995).

Summary: This paper examines the role that both the planning and shop floor control systems play in the operation and performance of a dual resource constrained job shop. Using causal analysis, the results show an effective planning system, as it accounts for the largest gain in shop performance. Generating and releasing smoothed schedules (work loads) allows the use of simplified shop floor control procedures such as order review/release (ORR), job dispatching and labour assignment rules without adversely affecting performance. This study uses the results to resolve the current paradox surrounding ORR systems and shows that the ORR rules’ performance is strongly dependent on the planning system, and that ORR rules can be considered moderating variables. Further, the study develops a variance control framework that indicates the necessary managerial actions to improve shop performance. This paper demonstrates that the planning system, not the shop floor control system, is the major determinant of shop performance. By making improvements to the planning system, the shop can use simple ORR rules, job dispatching and labour assignment procedures to control the flow of work without adversely impacting shop performance. These findings will help guide managerial investments in planning and shop floor control systems.

MSC:

90B30

Production models

Keywords:

dual resource constrained job shop; order review/release; job dispatching; planning; labour assignment

References:

[1]	ASHTON J. E., Harvard Business Review 67 pp 106– (1989)
[2]	DOI: 10.1016/0272-6963(83)90022-0
[3]	DOI: 10.1016/0272-6963(83)90009-8
[4]	DOI: 10.1016/0305-0483(89)90009-1
[5]	COHEN J., Applied Multiple Regression/Correlation Analysis for theBehavioral Sciences (1983)
[6]	CONOVER W. J., Practical Nonparametric Statistics (1971)
[7]	DOI: 10.1177/003754977502400202
[8]	DOI: 10.1287/mnsc.19.9.1001
[9]	HARTY J. D., Proceedings of the APICS 12th AnnualConference pp 60– (1969)
[10]	DOI: 10.1080/05695557408974968
[11]	DOI: 10.1016/0272-6963(81)90003-6
[12]	KLEIJNEN J. P. C., Statistical Tools for Simulation Practitioners (1987) · Zbl 0629.62004
[13]	KuESTER J. L., Optimization Techniques with Fortran (1973) · Zbl 0268.65039
[14]	DOI: 10.1287/inte.18.4.84
[15]	MELNYK S. A., Shop Floor Control (1985)
[16]	MELNYK S. A., Production and Inventory Management Journal 33 pp 6– (1992)
[17]	DOI: 10.1080/00207548908942609
[18]	DOI: 10.1016/0272-6963(91)90008-L
[19]	DOI: 10.1080/00949657408810067 · Zbl 0291.62098
[20]	NAKAJIMA S., TPM Development Program (1989)
[21]	NETER J., Applied Linear Statistical Models (1985)
[22]	PARK P. S., The Effects of Input Control in a Dual Resource Constrained Job Shop (1987)
[23]	DOI: 10.1016/0272-6963(89)90026-0
[24]	PEGDF N. C. D., Introduction to SJMAN (1987)
[25]	DOI: 10.1080/00207549208948176
[26]	PLOSSL G. W., Production & Inventory Management 14 pp 31– (1973)
[27]	DOI: 10.1111/j.1540-5915.1988.tb00260.x
[28]	DOI: 10.1080/00207548108956652
[29]	DOI: 10.1016/0377-2217(94)90373-5 · Zbl 0809.90083
[30]	DOI: 10.1080/07408178908966233
[31]	TRIBUS M., Quality First (1988)
[32]	UMBLE M., Synchronous Manufacturing (1990)