Maintenance management has a direct influence on production performance. Existing works have not systematically taken the on-line production information into consideration in determining maintenance work-order priority, which is often assigned either through an ad hoc approach or using largely heuristic and static methods. In this paper, we first present a metric that can be used to quantitatively evaluate the effects of different maintenance priorities. Based on this index, one can employ a search algorithm to obtain maintenance work-order priorities that will lead to improved productivity within the optimization horizon. These concepts and methods are validated through simulation experiments and implementation in a real industrial facility. The results show that the effective utilization of on-line production data in dynamic maintenance scheduling can yield visible production benefit through maintenance priority optimization.
Skip Nav Destination
Article navigation
April 2007
Technical Papers
Maintenance Priority Assignment Utilizing On-line Production Information
Zimin Yang,
Zimin Yang
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical Engineering,
University of Michigan
, 2350 Hayward Street, Ann Arbor, MI 48109-2125
Search for other works by this author on:
Qing Chang,
Qing Chang
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090-9055
Search for other works by this author on:
Dragan Djurdjanovic,
Dragan Djurdjanovic
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical Engineering,
University of Michigan
, 2350 Hayward Street, Ann Arbor, MI 48109-2125
Search for other works by this author on:
Jun Ni,
Jun Ni
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical Engineering,
University of Michigan
, 2350 Hayward Street, Ann Arbor, MI 48109-2125
Search for other works by this author on:
Jay Lee
Jay Lee
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical, Industrial and Nuclear Engineering,
University of Cincinnati
, 598 Rhodes Hall, P. O. Box 210072, Cincinnati, OH 45221-0072
Search for other works by this author on:
Zimin Yang
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical Engineering,
University of Michigan
, 2350 Hayward Street, Ann Arbor, MI 48109-2125
Qing Chang
General Motors Research and Development Center
, 30500 Mound Road, Warren, MI 48090-9055
Dragan Djurdjanovic
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical Engineering,
University of Michigan
, 2350 Hayward Street, Ann Arbor, MI 48109-2125
Jun Ni
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical Engineering,
University of Michigan
, 2350 Hayward Street, Ann Arbor, MI 48109-2125
Jay Lee
Center for Intelligent Maintenance Systems (IMS), Department of Mechanical, Industrial and Nuclear Engineering,
University of Cincinnati
, 598 Rhodes Hall, P. O. Box 210072, Cincinnati, OH 45221-0072J. Manuf. Sci. Eng. Apr 2007, 129(2): 435-446 (12 pages)
Published Online: March 24, 2006
Article history
Received:
April 7, 2005
Revised:
March 24, 2006
Citation
Yang, Z., Chang, Q., Djurdjanovic, D., Ni, J., and Lee, J. (March 24, 2006). "Maintenance Priority Assignment Utilizing On-line Production Information." ASME. J. Manuf. Sci. Eng. April 2007; 129(2): 435–446. https://doi.org/10.1115/1.2336257
Download citation file:
Get Email Alerts
Related Articles
Asset Management Evaluation: A Pilot Case Study
J. Pressure Vessel Technol (February,2007)
On Rationality in Engineering Design
J. Mech. Des (November,2004)
Risk Based Acceptance Criteria for Joints Subject to Fatigue Deterioration
J. Offshore Mech. Arct. Eng (May,2005)
Plant Life Management Models: A Comparison With Analysis of Impact on Both Safety and Nonsafety Issues
J. Pressure Vessel Technol (June,2011)
Related Proceedings Papers
Related Chapters
Computer Aided Manufacturing (CAM)
Computer Aided Design and Manufacturing
Better Decisions
Total Quality Development: A Step by Step Guide to World Class Concurrent Engineering
Multiobjective Decision-Making Using Physical Programming
Decision Making in Engineering Design