Optimal lead time policies

Article Abstract:

An analysis of a general single class production system with multiple stages and unlimited buffer capacities was conducted. It addressed the two due-date setting problems first explored by Wein (1991) in a multiclass M/G/1 queueing system. These problems minimize the weighted average lead time of jobs with a constraint on the fraction of tardy jobs, which is concern of the first problem, or the average job tardiness, which is the focus of the second. This examination reveals that the optimal due-date setting rule in the first problem results in unethical practice while the due-date setting rule found in the second problem is more acceptable. The second problem generates policies that set lead times that are singularly increasing as the congestion level increases. Also, the second problem has the characteristics of a broadly utilized and easy-to-compute policy.

Production Planning & Control, Lead time

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Finding optimal material release times using simulation-based optimization

Article Abstract:

An approach has been developed for determining release schedules for tasks having due dates in a stochastic production flow line for which the order of the succession of the tasks has been set. Since this method considers a transient situation, the flow line usually includes tasks that had already been released to the system, known as work in process. The model developed, which considers both stochastic process times and down times, constitutes a first step in the use of simulation-based optimization for scheduling in the manufacturing sector. It may be useful as an interface between the formation of a Manufacturing Resources Planning pool and the Manufacturing Execution Systems job release module to determine more accurately which tasks to release.

Models, Manufacturing processes, Manufacturing, Stochastic processes

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An analytic congestion model for closed production systems with IFR processing times

Article Abstract:

An analytic congestion model is presented for a closed production system made up of a network of queues having IFR processing times. The model relates the number of jobs in the system to the mean cycle time. The model's advantages are: accuracy, an analytic closed form, and its involvement of three meaningful parameters. The model's derivation is based on the observed relationship between work in process (WIP) procedures and mean cycle time.

Research, Process control

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