E3S Web Conf.
Volume 218, 20202020 International Symposium on Energy, Environmental Science and Engineering (ISEESE 2020)
|Number of page(s)||5|
|Section||Research on Energy Technology Application and Consumption Structure|
|Published online||11 December 2020|
Research on Management Strategy of Cost-based Intelligent Manufacturing System
Ocean University of China, University of Waterloo
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.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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