Publication
Scheduling Operations and SMED: Complementary Ways to Improve Productivity
| Summary: | In most real cases the problem of scheduling operations are sequence de-pendent, that is, the setup time depends on the sequencing of tasks/batches in the ma-chine. Given the current industrial manufacturing trends and requirements such as high variability, customization and reduction of product life cycles, organizations seek to implement new methodologies to adapt and respond with more flexibly to new demands of the global markets. Thus, this work sought to analyse, inspired by a real case of the textile industry, how production scheduling can be understood as a complement to SMED in order to achieve productivity improvement. In the case under analysis we presented the problem of scheduling tasks in uniform parallel machines with sequence-dependent setup times. The main objective of this work was to minimize the total pro-duction time. To this goal, optimization heuristics were used, in this case, simulated annealing algorithm, that demonstrated how the use of heuristics can be an advantage to reduce setup times when associated with other methodologies such as SMED. |
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| Main Authors: | Santos, Fernando Charrua |
| Other Authors: | Santos, Beatrice Paiva; Calderón-Arce, Cindy; Figueroa-Mata, Geovanni; Lima, Tânia M. |
| Subject: | Uniform Parallel Machines Scheduling Simulated Annealing |
| Year: | 2019 |
| Country: | Portugal |
| Document type: | book part |
| Access type: | restricted access |
| Associated institution: | Universidade da Beira Interior |
| Language: | English |
| Origin: | uBibliorum |
| Summary: | In most real cases the problem of scheduling operations are sequence de-pendent, that is, the setup time depends on the sequencing of tasks/batches in the ma-chine. Given the current industrial manufacturing trends and requirements such as high variability, customization and reduction of product life cycles, organizations seek to implement new methodologies to adapt and respond with more flexibly to new demands of the global markets. Thus, this work sought to analyse, inspired by a real case of the textile industry, how production scheduling can be understood as a complement to SMED in order to achieve productivity improvement. In the case under analysis we presented the problem of scheduling tasks in uniform parallel machines with sequence-dependent setup times. The main objective of this work was to minimize the total pro-duction time. To this goal, optimization heuristics were used, in this case, simulated annealing algorithm, that demonstrated how the use of heuristics can be an advantage to reduce setup times when associated with other methodologies such as SMED. |
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