The Effect of Workload Dependent Due-Dates on Job Shop Performance
- 1 July 1983
- journal article
- Published by Institute for Operations Research and the Management Sciences (INFORMS) in Management Science
- Vol. 29 (7) , 799-816
- https://doi.org/10.1287/mnsc.29.7.799
Abstract
This study explores the due-date performance of job shop control systems which base job due dates on a time-phased representation of the workload and the machine capacity in the shop. The performance is measured by the mean and the standard deviation of the lateness. Two parameters are used to vary the functioning of the due-date assignment system: a minimum allowance for waiting, denoted by SL, and a maximum fraction of the available capacity allowed for loading, denoted by CLL. The system increases the waiting lime allowance if congestion is observed when loading a new job. The capability of the system to observe congestion is determined by the parameters CLL and SL. Simulation experiments are used to investigate the performance of the assignment system. It is shown that the assignment system performs quite well with respect to reducing the standard deviation of the lateness; the performance is not very sensitive however to the parameter values used; with an expected capacity utilization of 90%, CLL should be set between 0.80 and 1.00 times the mean available capacity and SL should be set between 0.55 and 0.90 times the mean operation waiting time in the shop. The assignment system may also perform well with respect to controlling the mean lateness. If SL is set between 0.55 and 0.75 times the mean expected waiting time in the shop, a constant mean lateness is obtained independent of the utilization of the shop if CLL is set between 0.70 and 0.80 times of the mean available capacity. However, the mean lateness turns out to be quite sensitive to variations in the job-mix of the workload. Finally it is shown that if the values of the assignment parameters are adequate, the mean job lateness is independent of the number of operations in a job. This property can be used to monitor the correctness of the parameter values.Keywords
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