Sequencing, dispatching and switching in a dynamic manufacturing environment

Matsuura, Haruki; Tsubone, Hitoshi; Kanezashi, Masakazu

doi:10.1080/00207549308956816

Cited by 50 publications

(25 citation statements)

References 5 publications

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“…Moreover, the distribution of operation processing times has been recognized as an important area, within the manufacturing planning and control system, where the variance can be more easily created (Melnyk et al 1992, Matsuura et al 1993.…”

Section: Processing Time Variabilitymentioning

confidence: 99%

Comparison of Order Review and Release techniques in a dynamic and uncertain job shop environment

Cigolini¹,

Perona²,

Portioli³

1998

International Journal of Production Research

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This paper proposes a new methodological pattern to assess the e ectiveness of Order Review and Release (ORR) techniques in a job shop environment. The standpoint for this new method lies in the following remarks: (i) comparisons among ORR models should be performed in dynamic and uncertain environments; (ii) ORR techniques robustness toward the shop uncertainty and perturbations should be considered; and (iii) ORR models should be compared by changing their features one at a time, instead of comparing completely di erent ORR techniques.Consistently, we present a comparison among three ORR models, previously developed in literature, aimed at investigating: (i) the impact of a dynamic and uncertain environment on the performances achieved; (ii) the robustness of these ORR models when facing some environmental perturbations, like the system workload, the mix imbalance, the machine unavailability and the processing time variability, that usually take place in real life job shops; and (iii) the overall e ectiveness of the way workload is accounted for over time, since the models di erentiate only by this item, while any other feature of the release mechanism is the same.Simulation results highlight that the performances of the ORR techniques tested depend on how perturbed the environment where they are implemented is. Moreover, the ORR techniques tested greatly di er in their robustness against environment perturbations.

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Section: Processing Time Variabilitymentioning

confidence: 99%

Comparison of Order Review and Release techniques in a dynamic and uncertain job shop environment

Cigolini¹,

Perona²,

Portioli³

1998

International Journal of Production Research

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show abstract

“…(ii) From a methodological point of view, the simulation model can be improved through a deeper insight in the analytic relationships that link the parameters upon which the system's running primarily depends. (iii) While this research addressed the batch problem in a deterministic way, uncertainty frequently causes disturbances in production control, sometimes resulting in rescheduling at short intervals [33]. For this reason, the dynamic events that may occur in real-life shop oors and which upset production activities (i.e.…”

Section: Concluding Remarks and Future Research Pathsmentioning

confidence: 99%

A new dynamic look-ahead scheduling procedure for batching machines

et al. 2002

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SUMMARYThe management of batching machines has raised a wide interest among researchers and practitioners in the recent years. The problem lies in that, whenever less than a full load is queuing at a batching machine, production planners have to decide whether to start processing the incomplete load or to wait for additional jobs. This paper proposes a new procedure for scheduling several products on parallel batching machines. This new procedure, motivated by shop oor control in semiconductor manufacturing, has been developed and tested by means of a simulation model of a re-entrant owmanufacturing environment, which allows multiple loops along the job routings. The proposed procedure is shown to yield a better performance than the actual industrial practice from the point of view of ow-time-related indexes without adversely a ecting the system's utilization rate.

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“…Matsuura et al [5] stated that they are the events of errors in estimated processing time, machine breakdowns, specification changes, errors in routing data, which specify machines that a job will visit, cancellation of orders, and rush orders, which apparently varied. Errors in estimated processing times would bring the same effect as machine breakdowns with short time intervals.…”

Section: Dynamic Manufacturing Environmentmentioning

confidence: 99%

Real-time GA-based rescheduling approach for the pre-sewing stage of an apparel manufacturing process

Wong

Leung

2004

AMT

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In this paper, a real-time segmentation rescheduling (RSR) approach using genetic algorithms to handle the production planning and scheduling problem in dynamic apparel manufacturing environment is proposed. Experiments based on the actual production data were conducted to validate the performance of the RSR approach. The experimental results indicated that the makespan and the influence caused by the change of schedule could be minimised.

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Sequencing, dispatching and switching in a dynamic manufacturing environment

Cited by 50 publications

References 5 publications

Comparison of Order Review and Release techniques in a dynamic and uncertain job shop environment

Comparison of Order Review and Release techniques in a dynamic and uncertain job shop environment

A new dynamic look-ahead scheduling procedure for batching machines

Real-time GA-based rescheduling approach for the pre-sewing stage of an apparel manufacturing process

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