Effective and efficient scheduling of dynamic job shops—Combining the shifting bottleneck procedure with variable neighbourhood search

Scholz‐Reiter, Bernd; Hildebrandt, Torsten; Tan, Yi

doi:10.1016/j.cirp.2013.03.047

Cited by 16 publications

(4 citation statements)

References 17 publications

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“…For instance, Roser, Lorentzen, and Deuse (2015) perform a 'bottleneck walk' to identify the bottleneck by shop floor observations of inventory and process starvation. Other methods include the statistical computation of mean process cycle times or waiting times (Betterton and Silver 2012;Hopp and Spearman 2008;Scholz-Reiter, Hildebrandt, and Tan 2013). A limitation of traditional bottleneck detection methods is their inability to cope with dynamic high-mix production environments.…”

Section: Process Productivitymentioning

confidence: 99%

Using process mining to improve productivity in make-to-stock manufacturing

Lorenz

Senoner

Sihn

et al. 2021

International Journal of Production Research

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This paper proposes a data-driven procedure to improve productivity in make-to-stock manufacturing. By leveraging recent developments in information systems research, the paper addresses manufacturing systems with high process complexity and variety. Specifically, the proposed procedure draws upon process mining to dynamically map and analyse manufacturing processes in an automated manner. This way, manufacturers can leverage data to overcome the limitations of existing process mapping methods, which only provide static snapshots of process flows. By bridging data and process science, process mining can exploit hitherto untapped potential for productivity improvement. The proposed procedure is empirically validated at a leading manufacturer of sanitary products. The field test leads to three concrete improvement suggestions for the company. This research contributes to the literature on production research by demonstrating a novel use of process mining in manufacturing and by guiding practitioners in its implementation.

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Section: Process Productivitymentioning

confidence: 99%

Using process mining to improve productivity in make-to-stock manufacturing

Lorenz

Senoner

Sihn

et al. 2021

International Journal of Production Research

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“…In their approaches, machine capacity constraints or operation precedence constraints are relaxed, and the relaxed problem is decomposed into single machine or single job scheduling subproblems which are solved by fast heuristic algorithms. Shifting bottleneck (SB) [4][5][6] procedure and constraint scheduling algorithm (CSA) [7] iteratively decompose the JSP into a number of single machine scheduling subproblems. At each iteration, a bottleneck or constraint machine is identified and scheduled, with scheduling decisions at subsequent iteration being subordinated to those scheduled earlier.…”

Section: Introductionmentioning

confidence: 99%

Decomposition-based scheduling algorithm for large-scale job shop

Zhai

Dong

Wei

et al. 2013

2013 IEEE International Conference on Information and Automation (ICIA)

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A multi-bottleneck scheduling algorithm based on rolling horizon decomposition is proposed for large-scale job shop scheduling problems, in which the total weighted tardiness must be minimized. The algorithm divides the original problem into a number of subproblems according to the process route of each job, and gets the solution of the original problem by constructing and solving the subproblems iteratively. A multibottleneck detection method based on critical path method is proposed to detect the bottlenecks in the problem. According to the principle of "bottleneck machines lead non-bottleneck machines" in TOC, the operations processed on bottleneck machines are scheduled by genetic algorithm, and the operations processed on non-bottleneck machines are scheduled by dispatching rules to improve the computing efficiency. Simulation results show that the algorithm is effective for largescale job shop scheduling problems.

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“…A review of the existing solution approach for this scheduling problem can be found in Kellerer (2004) and (Pinedo, 2008, chap.9). Further approaches addressing similar scheduling problems are presented in Benmansour et al (2012), Scholz-Reiter et al (2013), Gafarov et al (2014).…”

Section: State Of the Artmentioning

confidence: 99%

A branch-and-bound approach for the single machine maximum lateness stochastic scheduling problem to minimize the value-at-risk

Urgo

Váncza

2018

Flex Serv Manuf J

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The research in the field of robust scheduling aims at devising schedules which are not sensitive -to a certain extent -to the disruptive effects of unexpected events. Nevertheless, the protection of the schedule from rare events causing heavy losses is still a challenging aim. The paper presents a novel approach for protecting the quality of a schedule by assessing the risk associated to the different scheduling decisions. The approach is applied to a stochastic scheduling problem with a set of jobs to be sequenced on a single machine. The release dates and processing times of the jobs are generally distributed independent random variables, while the due dates are deterministic. A branch-and-bound approach is taken to minimise the value-at-risk (VaR) of the distribution of the maximum lateness. The viability of the approach is demonstrated through a computational experiment and the application to an industrial problem in the tool making industry.

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Effective and efficient scheduling of dynamic job shops—Combining the shifting bottleneck procedure with variable neighbourhood search

Cited by 16 publications

References 17 publications

Using process mining to improve productivity in make-to-stock manufacturing

Using process mining to improve productivity in make-to-stock manufacturing

Decomposition-based scheduling algorithm for large-scale job shop

A branch-and-bound approach for the single machine maximum lateness stochastic scheduling problem to minimize the value-at-risk

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