Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems
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| Title: | Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems |
|---|---|
| Authors: | Roy, Sayantee |
| Committee Members: | Thorsten Wuest; Imtiaz Ahmed; John Saldanha |
| Summary: | Nowadays, industries put a significant emphasis on finding the optimum order for carrying out jobs in sequence. This is a crucial element in determining net productivity. Depending on the demand criterion, all production systems, including flexible manufacturing systems, follow a predefined sequence of job-based machine operations. The complexity of the problem increases with increasing machines and jobs to sequence, demanding the use of an appropriate sequencing technique. The major contribution of this work is to modify an existing algorithm with a very unusual machine setup and find the optimal sequence which will really minimize the makespan. This custom machine setup completes all tasks by maintaining precedence and satisfying all other constraints. This thesis concentrates on identifying the most effective technique of sequencing which will be validated in a lab environment and a simulated environment. It illustrates some of the key methods of addressing a circular non permutation flow shop sequencing problem with some additional constraints. Additionally, comparisons among the various heuristics algorithms are presented based on different sequencing criteria. The optimum sequence is provided as an input to a real-life machine set up and a simulated environment for selecting the best performing algorithm which is the basic goal of this research. To achieve this goal, at first, a code using python programming language was generated to find an optimum sequence. By analyzing the results, the makespan is increasing with the number of jobs but additional pallet constraint shows, adding more pallets will help to reduce makespan for both flow shops and job shops. Though the sequence obtained from both algorithms is different, for flow shops the makespan remains same for both cases but in the job shop scenario Nawaz, Enscore and Ham (NEH) algorithms always perform better than Campbell Dudek Smith (CDS) algorithms. For job shops with different combinations the makespan decreases mostly for maximum percentage of easy category jobs combined with equal percentage of medium and complex category jobs. |
| URL: | https://researchrepository.wvu.edu/etd/11493 |
| Database: | OpenDissertations |
| FullText | Text: Availability: 0 |
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| Header | DbId: ddu DbLabel: OpenDissertations An: ddu.oai.researchrepository.wvu.edu.etd.12456 AccessLevel: 6 PubType: Dissertation/ Thesis PubTypeId: dissertation PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Roy%2C+Sayantee%22">Roy, Sayantee</searchLink> – Name: Author Label: Committee Members Group: Au Data: <searchLink fieldCode="CO" term="%22Thorsten+Wuest%22">Thorsten Wuest</searchLink>; <searchLink fieldCode="CO" term="%22Imtiaz+Ahmed%22">Imtiaz Ahmed</searchLink>; <searchLink fieldCode="CO" term="%22John+Saldanha%22">John Saldanha</searchLink> – Name: Abstract Label: Summary Group: Ab Data: Nowadays, industries put a significant emphasis on finding the optimum order for carrying out jobs in sequence. This is a crucial element in determining net productivity. Depending on the demand criterion, all production systems, including flexible manufacturing systems, follow a predefined sequence of job-based machine operations. The complexity of the problem increases with increasing machines and jobs to sequence, demanding the use of an appropriate sequencing technique. The major contribution of this work is to modify an existing algorithm with a very unusual machine setup and find the optimal sequence which will really minimize the makespan. This custom machine setup completes all tasks by maintaining precedence and satisfying all other constraints. This thesis concentrates on identifying the most effective technique of sequencing which will be validated in a lab environment and a simulated environment. It illustrates some of the key methods of addressing a circular non permutation flow shop sequencing problem with some additional constraints. Additionally, comparisons among the various heuristics algorithms are presented based on different sequencing criteria. The optimum sequence is provided as an input to a real-life machine set up and a simulated environment for selecting the best performing algorithm which is the basic goal of this research. To achieve this goal, at first, a code using python programming language was generated to find an optimum sequence. By analyzing the results, the makespan is increasing with the number of jobs but additional pallet constraint shows, adding more pallets will help to reduce makespan for both flow shops and job shops. Though the sequence obtained from both algorithms is different, for flow shops the makespan remains same for both cases but in the job shop scenario Nawaz, Enscore and Ham (NEH) algorithms always perform better than Campbell Dudek Smith (CDS) algorithms. For job shops with different combinations the makespan decreases mostly for maximum percentage of easy category jobs combined with equal percentage of medium and complex category jobs. – Name: URL Label: URL Group: URL Data: <link linkTarget="URL" linkTerm="https://researchrepository.wvu.edu/etd/11493" linkWindow="_blank">https://researchrepository.wvu.edu/etd/11493</link> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ddu&AN=ddu.oai.researchrepository.wvu.edu.etd.12456 |
| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English Subjects: – SubjectFull: Sequencing Type: general – SubjectFull: Bottleneck Type: general – SubjectFull: Makespan Type: general – SubjectFull: Idle Time Type: general – SubjectFull: Simulation Type: general – SubjectFull: Processing Time Type: general – SubjectFull: Operations Research, Systems Engineering and Industrial Engineering Type: general Titles: – TitleFull: Bottleneck Management through Strategic Sequencing in Smart Manufacturing Systems Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Roy, Sayantee IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2022 |
| ResultId | 1 |
