Sequencing Rules and Due-Date Assignments in a Job Shop

Baker, Kenneth R.

doi:10.1287/mnsc.30.9.1093

Cited by 442 publications

(210 citation statements)

References 14 publications

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“…To solve statistic and deterministic scheduling problems a lot of analytical and optimization algorithms have been developed (Baker, 1984). If the problems are small, it is possible to generate optimal schedules using a branch or a bound approach (Brucker et al, 1993).…”

Section: Literature Reviewmentioning

confidence: 99%

An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

Ahmed¹,

Khan²,

Haque³

et al. 2016

American Journal of Engineering and Applied Sciences

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This paper aims at developing a dynamic job shop scheduling by establishing fuzzy rule based system and comparing its effectiveness with the traditional priority rules. In order to understand the priorities of different jobs in a job shop, the paper investigates all the contributing criteria of different parameters. Since the traditional priority rules only emphasis on a single parameter at a time, the authors propose a method of obtaining a schedule which incorporates all the desired contribution criteria of the parameters used. This method includes establishing a Fuzzy priority rule. Fuzzy is an appropriate model when uncertainty and irregularities are present. It also allows modeling of a significant number of alternatives across different parameters considered in a job shop. Hence, a dynamic job shop schedule can be developed using the established fuzzy priority rule. This research is based on an example of jobs arriving in a regular semi-automated job shop, not a fully automated or software based job shop. The practical implications of this paper is to identify the proper parameters and evaluate their contribution criteria on the required conditions so that managers can determine the proper scheduling and sequence of the jobs to be machined in the job shop. This study provides a deterministic method for local managers to assess the effects of job shop scheduling and sequence of jobs.

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Section: Literature Reviewmentioning

confidence: 99%

An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

Ahmed¹,

Khan²,

Haque³

et al. 2016

American Journal of Engineering and Applied Sciences

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“…In this particular FMS these are: F, flow allowance factor which measures due date tightness [19]; NAMO: number of alternative machines for an operation; MU: mean utilization of the manufacturing system; U i : utilization of machine i; WIP: mean number of parts in the system; RBM: ratio of the utilization of the bottleneck machine to the mean utilization of the manufacturing system; RSDU: ratio of the standard deviation of individual machine utilizations to mean utilization.…”

Section: B Generating Training and Test Examplesmentioning

confidence: 99%

Real-Time Scheduling of Flexible Manufacturing Systems Using Support Vector Machines and Case-Based Reasoning

Priore¹,

Pino²,

Parreño³

et al. 2015

JOEBM

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Abstract-Dispatching rules are usually applied to schedule jobs in Flexible Manufacturing Systems (FMSs) dynamically. Despite their frequent use, one of the drawbacks that they display is that the state the manufacturing system is in dictates the level of performance of the rule. As no rule is better than all the other rules for all system states, it would highly desirable to know which rule is the most appropriate for each given condition, and to this end this paper proposes a scheduling approach that employs Support Vector Machines (SVMs) and case-based reasoning (CBR). Using these latter techniques, and by analysing the earlier performance of the system, "scheduling knowledge" is obtained whereby the right dispatching rule at each particular moment can be determined. A module that generates new control attributes is also designed in order to improve the "scheduling knowledge" that is obtained. Simulation results show that the proposed approach leads to significant performance improvements over existing dispatching rules.

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“…Cheng (1994) and Luss and Rosenwein (1993) examine ways to optimize due-date assignment in manufacturing environments. Baker, (1984), Wein (1991) and Via and Dolley (1991) examine the interaction and integration of due-date setting policies and scheduling procedures. Ozdamar and Yazgac (1997) and Udo (1993) examine the relationship between manufacturing capacity and due-date setting policies.…”

Section: Related Literaturementioning

confidence: 99%

Melt Scheduling to Trade Off Material Waste and Shipping Performance

Naphade

Storer

et al. 2001

Operations Research

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The ingot formation or "melt" process is the first step in many steel making operations. This process involves melting steel and alloys for desired chemical composition, then pouring it into a variety of ingot molds. Complex technological and resource constraints can make the planning and scheduling of such processes extremely challenging. In this paper, we report our experience in developing solution methods for this "melt scheduling" problem at BethForge, a division of the Bethlehem Steel Corporation, and a manufacturer of custom-made heavy steel forgings. We describe the main issues associated with generic melt scheduling problem as well as constraints that are specific to BethForge. The problem at BethForge is particularly challenging due to the need to keep the ingot at a high temperature before forging, their high product variety, and the need to consider trade-offs between two conflicting objectives. We first formulate the base melt scheduling problem as a mixed integer program. We then decouple the scheduling decisions into two levels and develop a local search algorithm based on Storer and Wu's problem space neighborhood. Our aim is to generate a family of efficient schedules that allow decision makers to balance the tradeoff between two criteria. Computational experiments are performed using data from BethForge. The melt scheduling procedure developed herein has been implemented and installed at BethForge. It made fundamental improvement in their melt scheduling process. 1Steel ingots form the raw material for a variety of steel products that are processed through forging, heat treatment and other similar steel manufacturing processes. Steel manufacturers either have ingots delivered to them or have ingot formation processes at the front end of the plant. The ingot formation or "melt" process is extremely critical because of its capital and energy intensive nature, and the effect it has on the material flow of the downstream production processes. These factors, coupled with a complex set of resource and technological constraints, make melt scheduling a very challenging problem. When we started our study at BethForge in 1995 melt scheduling was carried out manually by seasoned schedulers who were intimately familiar with the complex engineering rules and constraints involved in the process. Later in 1995, Bethlehem Steel decided to move the melt operation from within the Bethlehem plant to Steelton, PA (some 80 miles away), where ingots for other steel products are also poured. The forging, heat treatment and machining processes remain in the Bethlehem plant. Steel ingots are poured on a weekly basis at Steelton, then transported by rail carts to Bethlehem. This new process creates major challenges to the manual scheduling system as the melt operation is now limited to a specific time slot during the week, strict weight restrictions are imposed by the Steelton melting resources, and frequent rescheduling becomes necessary due to variations in crew configuration, maintenance plan, resource availa...

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Sequencing Rules and Due-Date Assignments in a Job Shop

Cited by 442 publications

References 14 publications

An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

An Approach to Develop a Dynamic Job Shop Scheduling by Fuzzy Rule Based System and Comparative Study with the Traditional Priority Rules

Real-Time Scheduling of Flexible Manufacturing Systems Using Support Vector Machines and Case-Based Reasoning

Melt Scheduling to Trade Off Material Waste and Shipping Performance

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