Workload control mechanisms are widely studied in the literature for the control of job-shop systems. The control of these systems involves acceptance, order release and priority dispatching. At the release level, the workload norm controls the "enters" of the jobs; it is relevant how the aggregate workload is computed. Few works have studied new computation methods of the aggregate workload but use the adjusted aggregate workload proposed in the literature. This paper proposes a dynamically adjusted aggregate workload to improve the performance of the workload control mechanism in job-shop systems. The adjusted aggregate workload is updated when each part exits from a workstation; this means that the workload used to release the orders is related to the state of the job shop in real-time. Simulation is used to evaluate and compare the proposed model to the classical models proposed in the literature. The simulation experiments demonstrate improvement of performance and how the model proposed is robust under different manufacturing system conditions.

A dynamic adjusted aggregate load method to support workload control policies

Renna P.
2020-01-01

Abstract

Workload control mechanisms are widely studied in the literature for the control of job-shop systems. The control of these systems involves acceptance, order release and priority dispatching. At the release level, the workload norm controls the "enters" of the jobs; it is relevant how the aggregate workload is computed. Few works have studied new computation methods of the aggregate workload but use the adjusted aggregate workload proposed in the literature. This paper proposes a dynamically adjusted aggregate workload to improve the performance of the workload control mechanism in job-shop systems. The adjusted aggregate workload is updated when each part exits from a workstation; this means that the workload used to release the orders is related to the state of the job shop in real-time. Simulation is used to evaluate and compare the proposed model to the classical models proposed in the literature. The simulation experiments demonstrate improvement of performance and how the model proposed is robust under different manufacturing system conditions.
2020
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11563/143844
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