NDLI: Study on Resource Scheduling Method of Predictive Maintenance for Equipment Based on Knowledge

Content Provider	IEEE Xplore Digital Library
Author	Xin Li Jinqian Wen Rui Zhou Yaoguang Hu
Copyright Year	2015
Description	Author affiliation: Sch. of Mech. Eng., Beijing Inst. of Technol., Beijing, China (Xin Li; Jinqian Wen; Rui Zhou; Yaoguang Hu)
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.
Starting Page	345
Ending Page	350
File Size	192020
Page Count	6
File Format	PDF
e-ISBN	9781467393232
DOI	10.1109/ISKE.2015.13
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-11-24
Publisher Place	Taiwan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Job shop scheduling predictive maintenance Agricultural machinery equipment resource scheduling Preventive maintenance Predictive maintenance knowledge
Content Type	Text
Resource Type	Article

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