NDLI: Maintenance scheduling incorporating dynamics of production system and real-time information from workstations

Content Provider	Springer Nature Link
Author	Arab, Ali Ismail, Napsiah Lee, Lai Soon
Copyright Year	2011
Abstract	In this paper, a new approach to maintenance scheduling for a multi-component production system which takes into account the real-time information from workstations including remaining reliability of equipments as well as work-in-process inventories in each workstation is proposed. To model dynamics of the system, other information like production line configuration, cycle times, buffers’ capacity and mean time to repair of machines are also considered. Using factorial experiment design the problem is formulated to comprehensively monitor the effects of each possible schedule on throughput of the production system. The optimal maintenance schedule is searched by genetic algorithm-based optimization engine implemented in a simulation optimization platform. The proposed approach exploits all of makespans of planning horizon to find the best opportunity to perform maintenance actions on degrading machines in a way that maximizes the system throughput and mitigates the production losses caused by imperfect traditional maintenance strategies. Finally the proposed method is tested in a real production line to magnify the accuracy of proposed scheduling method. The experimental results indicate that the proposed approach guarantees the operational productivity and scheduling efficiency as well.
Starting Page	695
Ending Page	705
Page Count	11
File Format	PDF
ISSN	09565515
Journal	Journal of Intelligent Manufacturing
Volume Number	24
Issue Number	4
e-ISSN	15728145
Language	English
Publisher	Springer US
Publisher Date	2012-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Maintenance scheduling System dynamics Simulation optimization Production/Logistics/Supply Chain Manufacturing, Machines, Tools Control, Robotics, Mechatronics
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Artificial Intelligence Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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