1997International Journal of Production ResearchRequires access

Production scheduling/rescheduling in flexible manufacturing

Anuj Jain, H.A. ElMaraghy

Open publisher page 176 citations

Abstract

Scheduling of production in flexible manufacturing systems (FMSs) has been extensively researched over the past years and it continues to attract the interests of both academic researchers and practitioners. The generation of new and modified production schedules is becoming a necessity in today's complex manufacturing environment. Genetic algorithms are used in this paper to obtain an initial schedule. Uncertainties in the production environment and modelling limitations inevitably result in deviations from the generated schedules. This makes rescheduling or reactive scheduling essential. Four different types of uncertainties that normally cause discrepancies between the actual output and the planned output are considered in this paper. These include unforeseen machine breakdowns, increased order priority, rush orders arrival and order cancellations. In this paper, the current status of the shop is considered while rescheduling. The proposed algorithms revise only those operations that must be rescheduled and can, therefore, be used in conjunction with the existing scheduling methods to improve the efficiency of flexible manufacturing systems.

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What this paper is about

Scheduling of production in flexible manufacturing systems (FMSs) has been extensively researched over the past years and it continues to attract the interests of both academic researchers and practitioners. The generation of new and modified production schedules is becoming a necessity in today's complex manufacturing environment. Genetic algorithms are used in this paper to obtain an initial schedule. Uncertainties in the production environment and modelling limitations inevitably result in deviations from the generated schedules. This makes rescheduling or reactive scheduling essential. Four different types of uncertainties that normally cause discrepancies between the actual output and the planned output are considered in this paper. These include unforeseen machine breakdowns, increased order priority, rush orders arrival and order cancellations. In this paper, the current status of the shop is considered while rescheduling. The proposed algorithms revise only those operations that must be rescheduled and can, therefore, be used in conjunction with the existing scheduling methods to improve the efficiency of flexible manufacturing systems.

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Available abstract

Scheduling of production in flexible manufacturing systems (FMSs) has been extensively researched over the past years and it continues to attract the interests of both academic researchers and practitioners. The generation of new and modified production schedules is becoming a necessity in today's complex manufacturing environment. Genetic algorithms are used in this paper to obtain an initial schedule. Uncertainties in the production environment and modelling limitations inevitably result in deviations from the generated schedules. This makes rescheduling or reactive scheduling essential. Four different types of uncertainties that normally cause discrepancies between the actual output and the planned output are considered in this paper. These include unforeseen machine breakdowns, increased order priority, rush orders arrival and order cancellations. In this paper, the current status of the shop is considered while rescheduling. The proposed algorithms revise only those operations that must be rescheduled and can, therefore, be used in conjunction with the existing scheduling methods to improve the efficiency of flexible manufacturing systems.

Key concepts: Scheduling (production processes), Due date, Schedule, Job shop scheduling, Computer science, Production schedule, Genetic algorithm scheduling, Operations research

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