Study on resource scheduling method of predictive maintenance for equipment based on knowledge

Xin Li*, Jinqian Wen, Rui Zhou, Yaoguang Hu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Citations (Scopus)

Abstract

At present, heavy industrial competition makes more manufacturing pay attention to the service based on their products. Therefore, product service system has caused the extensive value of the academic circles. Service resource scheduling is the key step in the product service delivery, which depends on the knowledge mined from history service data and product information in the use process, namely the different fault maintenance scheme, technicians' skill, equipment state information, fault prediction information, work plan, etc. Based on this, this paper puts forward a resource scheduling method for predictive maintenance services of equipment whose location change dynamically, aiming at eliminating potential failure, minimizing service cost and outage cost, considering the technicians' ability of different maintenance task, fault prediction information, equipment operation plan and other constraints. First, a mathematical model is set up to describe this problem. Then this paper adopts a hybrid algorithm to resolve that. Last, the result that the best time of servicing, route planning and the reasonable technician, shows this method can improve the service level and reduce total cost.

Original languageEnglish
Title of host publicationProceedings - The 2015 10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages345-350
Number of pages6
ISBN (Electronic)9781467393225
DOIs
Publication statusPublished - 13 Jan 2016
Event10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015 - Taipei, Taiwan, Province of China
Duration: 24 Nov 201527 Nov 2015

Publication series

NameProceedings - The 2015 10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015

Conference

Conference10th International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2015
Country/TerritoryTaiwan, Province of China
CityTaipei
Period24/11/1527/11/15

Keywords

  • equipment
  • knowledge
  • predictive maintenance
  • resource scheduling

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