The dynamic aspects of a production scheduling problem

Farn, Cheng-Kiang; Muhlemann, A. P.

doi:10.1080/00207547908919591

Cited by 28 publications

(3 citation statements)

References 8 publications

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“…They concluded that a periodic policy (scheduling/rescheduling periodically) is very effective in the dynamic job shop environments. Later, Farn and Muhleman (1979) compared dispatching rules and optimum seeking algorithms for the static and dynamic single machine scheduling problems. Again, new schedules are generated periodically in a dynamic environment.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of reactive scheduling problems in a job shop environment

Sabuncuoğlu

Bayiz²

2000

European Journal of Operational Research

166

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In this paper, we study the reactive scheduling problems in a stochastic manufacturing environment. Specifically, we test the several scheduling policies under machine breakdowns in a classical job shop system. In addition, we measure the effect of system size and type of work allocation (uniform and bottleneck) on the system performance. The performance of the system is measured for the mean tardiness and makespan criteria. We also investigate a partial scheduling scheme under both deterministic and stochastic environments for several system configurations

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Section: Literature Reviewmentioning

confidence: 99%

Analysis of reactive scheduling problems in a job shop environment

Sabuncuoğlu

Bayiz²

2000

European Journal of Operational Research

166

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“…The problem of scheduling n jobs on m machines in a flow-shop environment has attracted an enormous amount of attention in scheduling research. Most of this attention has focused on the single-machine (m = 1), sequence-dependent setup times (SDST) sequencing problem (e.g., Driscoll and Emmons 1977;Farn and Muhlemann 1979;Lockett and Muhlemann 1972). This problem is analogous to the traveling salesman problem and is NP-complete.…”

Section: Flow-shop Literature Reviewmentioning

confidence: 99%

An efficient heuristic for scheduling batches of parts in a flexible flow system

Das

Khumawala

1991

Int J Flex Manuf Syst

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Flexible manufacturing systems (FMSs) are a class of automated systems that can be used to improve productivity in batch manufacturing. Four stages of decision making have been defined for an FMS--the design, planning, scheduling, and control stages. This research focuses on the planning stage, and specifically in the area of scheduling batches of parts through the system.The literature to date on the FMS planning stage has mostly focused on the machine grouping, tool loading, and parttype selection problems. Our research carries the literature a step further by addressing the problem of scheduling batches of parts. Due to the use of serial-access material-handling systems in many FMSs, the batch-scheduling problem is modeled for a flexible flow system (FFS). This model explicitly accounts for setup times between batches that are dependent on their processing sequence.A heuristic procedure is developed for this batch-scheduling problem--the Maximum Savings (MS) heuristic. The MS heuristic is based upon the savings in time associated with a particular sequence and selecting the one with the maximum savings. It uses a two-phase method, with the savings being calculated in phase I, while a branchand-bound procedure is employed to seek the best heuristic solution in phase II. Extensive computational results are provided for a wide variety of problems. The results show that the MS heuristic provides good-quality solutions.

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“…Scheduling research on the problem of sequence dependent setup times (Allahverdi et al , 1999; Brucker and Thiele, 1996; Farn and Muhlemann, 1979; Missbauer, 1997; O'Grady and Harrison, 1988; White and Wilson, 1977) reflects a typical need for efficient shop floor operations. However, the problem is NP‐hard (Karp, 1972) and is mainly applied to a single‐machine shop (Allahverdi et al , 1999; Haase and Kimms, 2000) or a flow shop (Chen and Chyu, 2003) environment.…”

Section: Introductionmentioning

confidence: 99%

Sequencing shop floor operations: a practical approach

Yeh

2005

Journal of Manufacturing Technology Management

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PurposeThe work sequence indicated by a production schedule generated by existing scheduling techniques may not necessarily meet the need for efficient sequencing of day‐to‐day shop floor operations in a dynamic job shop environment. The purpose of this paper is to present a new practical approach to efficiently sequencing day‐to‐day shop floor operations of a job shop.Design/methodology/approachA color coding and priority system is introduced to identify production jobs that are to be processed at work centers which have a work sequence preference for performing various jobs. Based on a realistic production schedule, a three‐phase sequencing method is developed to create a truly feasible shop schedule, with the most efficient work sequence possible.FindingsSpecific features of the approach are presented and illustrated with a numerical example. It enables production jobs to be run in the best possible way at individual work centers. Various options of implementing the approach in practical applications are discussed.Research limitations/implicationsThe approach serves as an enhanced supplement to a job shop operations scheduling system for efficient sequencing of shop floor operations. It is to be implemented at the shop floor level.Practical implicationsThe approach can be implemented as a real‐time computer integrated shop dispatching system to ensure an efficient work sequence for shop floor operations of job shops in actual industrial settings.Originality/valueThe paper addresses the need for effectively coordinating production jobs of varying routings on the shop floor, which cannot be met by existing scheduling techniques or shop dispatching practice. It provides manufacturing practitioners with a structured approach for managing shop floor operations.

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The dynamic aspects of a production scheduling problem

Cited by 28 publications

References 8 publications

Analysis of reactive scheduling problems in a job shop environment

Analysis of reactive scheduling problems in a job shop environment

An efficient heuristic for scheduling batches of parts in a flexible flow system

Sequencing shop floor operations: a practical approach

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