Service Optimization of Production Process of Polyester Fiber Based on Immune and Endocrine Regulation Algorithm
A service optimization method for polyester fiber production process is proposed. According to the production batch and production specifications, the method considers the service cost as the optimization objective, and uses data model to determine the specific process parameters in the polyester fi...
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Published in | IEEE transactions on industrial informatics Vol. 17; no. 10; pp. 6776 - 6785 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
Piscataway
IEEE
01.10.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
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Summary: | A service optimization method for polyester fiber production process is proposed. According to the production batch and production specifications, the method considers the service cost as the optimization objective, and uses data model to determine the specific process parameters in the polyester fiber production process. First, two options for the overall process of polyester fiber are introduced: on-demand manufacturing and product development. Second, the impact of different batch request tasks on the performance index of each stage is determined. Finally, the service optimization measures of different batches are proposed. By comparing the similarity between the current data samples and the overall data, the optimal production plan of the overall production process is formed. Simulation results show that the immune algorithm inspired from endocrine regulation has the best performance on the optimal decision-making combination, which is helpful for the development of new polyester products. We investigate how to reduce energy consumption of system resources, and how to choose the best service from a large number of candidate services. In the overall polyester fiber production process, users are not only consumers, but also designers and producers, achieving the real "integration of production and consumption". |
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ISSN: | 1551-3203 1941-0050 |
DOI: | 10.1109/TII.2020.3040965 |