Research on Management Strategy of Cost-based Intelligent Manufacturing System

The reliability, efficiency and accuracy of CNC machines as work cells of intelligent manufacturing systems (IMS) are criteria to measure the processing level of the latter. In order to improve the reliability of the IMS and reduce the maintenance cost, very sound preventive maintenance and manageme...

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Main Authors: Cong Haoting, Che Jinyi
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/78/e3sconf_iseese2020_01029.pdf
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author Cong Haoting
Che Jinyi
author_facet Cong Haoting
Che Jinyi
author_sort Cong Haoting
collection DOAJ
description The reliability, efficiency and accuracy of CNC machines as work cells of intelligent manufacturing systems (IMS) are criteria to measure the processing level of the latter. In order to improve the reliability of the IMS and reduce the maintenance cost, very sound preventive maintenance and management strategies concerning the CNC machines should be defined. We realized a parameter estimation of our reliability model for CNC machine units in an IMS environment, carried out a linear correlation test and a distribution fitting test for the model and obtained the failure distribution function and failure rate function. We then built a post-failure maintainability model and realized a maintainability evaluation. Following the above analyses, we built a cost-based preventive maintenance cycle model and obtained its optimal value by using the particle swarm optimization (PSO) algorithm. This research and its result can on the one hand guide the setting-up of preventive maintenance planning and management schemes and on the other hand reduce the production cost and enhance enterprise efficiency.
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spelling doaj.art-e3357090d61145e885fdb70fd405953d2022-12-21T23:50:41ZengEDP SciencesE3S Web of Conferences2267-12422020-01-012180102910.1051/e3sconf/202021801029e3sconf_iseese2020_01029Research on Management Strategy of Cost-based Intelligent Manufacturing SystemCong Haoting0Che Jinyi1Ocean University of China, University of WaterlooOcean University of China, University of WaterlooThe reliability, efficiency and accuracy of CNC machines as work cells of intelligent manufacturing systems (IMS) are criteria to measure the processing level of the latter. In order to improve the reliability of the IMS and reduce the maintenance cost, very sound preventive maintenance and management strategies concerning the CNC machines should be defined. We realized a parameter estimation of our reliability model for CNC machine units in an IMS environment, carried out a linear correlation test and a distribution fitting test for the model and obtained the failure distribution function and failure rate function. We then built a post-failure maintainability model and realized a maintainability evaluation. Following the above analyses, we built a cost-based preventive maintenance cycle model and obtained its optimal value by using the particle swarm optimization (PSO) algorithm. This research and its result can on the one hand guide the setting-up of preventive maintenance planning and management schemes and on the other hand reduce the production cost and enhance enterprise efficiency.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/78/e3sconf_iseese2020_01029.pdf
spellingShingle Cong Haoting
Che Jinyi
Research on Management Strategy of Cost-based Intelligent Manufacturing System
E3S Web of Conferences
title Research on Management Strategy of Cost-based Intelligent Manufacturing System
title_full Research on Management Strategy of Cost-based Intelligent Manufacturing System
title_fullStr Research on Management Strategy of Cost-based Intelligent Manufacturing System
title_full_unstemmed Research on Management Strategy of Cost-based Intelligent Manufacturing System
title_short Research on Management Strategy of Cost-based Intelligent Manufacturing System
title_sort research on management strategy of cost based intelligent manufacturing system
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/78/e3sconf_iseese2020_01029.pdf
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