Investigation on the use of energy efficiency for condition-based maintenance decision-making

IFAC-PapersOnLine

Volumn 49, Issue 28, 2016, Pages 73-78

  Hoang, Anh ^a   Do, Phuc ^a   Iung, Benoît ^a  

^a UNIVERSITÉ DE LORRAINE   (France)

Author keywords

condition based maintenance; cost model; decision making; energy cost; Energy Efficiency

Indexed keywords

DECISION MAKING; ENERGY EFFICIENCY; ENERGY UTILIZATION; MAINTENANCE; OPTIMIZATION;

BENEFITS AND COSTS; CONDITION BASED MAINTENANCE; COST MODELING; ENERGY COST; ENERGY EFFICIENCY INDICATOR; MAINTENANCE COST MODEL; MAINTENANCE OPTIMIZATION; OPTIMIZATION MODELING;

COSTS;

EID: 85006427793     PISSN: None     EISSN: 24058963     Source Type: Conference Proceeding    
DOI: 10.1016/j.ifacol.2016.11.013     Document Type: Conference Paper

References (18)

1. Banks, J. C, Lebold, M, Reichard, K. M., Hines, J. A., & Brought, M. S. (2014). Platform degrader analysis for the complex systems for the design and application of condition based maintenance. In 2014 IEEE Aerospace Conference (pp. 1-12). IEEE.
2. Ben Ali, J., Chebel-Morello, B., Saidi, L., Malinowski, S., Fnaiech, F., Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network. Mechanical Systems and Signal Processing, 56-57, 2015, 150–172.
3. Do, P., Berenguer, C., Condition based maintenance model for a production deteriorating system. 2010 Conference on Control and Fault-Tolerant Systems (SysTol), 2010, 424–429.
4. Do, P., & Berenguer, C. (2015). Condition-based maintenance with both perfect and imperfect maintenance actions. Reliability Engineering and System Safety, 133, CDROM.
5. Fritzsche, R., Gupta, J.N.D.N.D., Lasch, R., Optimal prognostic distance to minimize total maintenance cost: The case of the airline industry. International Journal of Production Economics 151 (2014), 76–88.
6. Hoang, A., Do, P., & lung, B. (2015 PHM-Beijing).
7. Hoang, A., Do, P., lung, B., Levrat, E., & Voisin, A. (2014). Prognostics and Energy Efficiency: Survey and Investigations. In European Conference of the Prognostics and Health Management Society 2014 (pp. 147-161).
8. lung, B., Levrat, E., Advanced Maintenance Services for Promoting Sustainability. 3rd International Conference on Through-life Engineering Services Advanced 22 (2014), 15–22.
9. Mora, M., Vera, J., Rocamora, C, Abadia, R., Energy Efficiency and Maintenance Costs of Pumping Systems for Groundwater Extraction. Water Resources Management 27 (2013), 4395–4408.
10. Muchiri, P.N., Pintelon, L., Martin, H., Chemweno, P., Modelling maintenance effects on manufacturing equipment performance: results from simulation analysis. International Journal of Production Research 52 (2013), 3287–3302.
11. ROSS, S., Stochastic Processes. Wiley Series in Probability and statistics, 1996, John Wiley & Sons, Inc.
12. Shafiee, M., Finkelstein, M., Bérenguer, C., An opportunistic condition-based maintenance policy for offshore wind turbine blades subjected to degradation and environmental shocks. Reliability Engineering & System Safety 142 (2015), 463–471.
13. Sun, J., Zuo, H., Wang, W., Pecht, M.G., Prognostics uncertainty reduction by fusing on-line monitoring data based on a state-space-based degradation model. Mechanical Systems and Signal Processing 45 (2014), 107–396.
14. Van Noortwijk, J.M., A survey of the application of gamma processes in maintenance. Reliability Engineering and System Safety 94 (2009), 2–21.
15. Wang, H., A survey of maintenance policies of deteriorating systems. European Journal of Operational Research 139 (2002), 469–489.
16. Xu, W., Cao, L., Energy efficiency analysis of machine tools with periodic maintenance. International Journal of Production Research, 2014, 1–13.
17. Yildirim, M.B., Nezami, F.G., Integrated maintenance and production planning with energy consumption and minimal repair. The International Journal of Advanced Manufacturing Technology 74 (2014), 1419–1430.
18. Zhou, Z.-J., Hu, C.-H., Han, X.-X., He, H.-F., Ling, X.-D., Zhang, B.-C., A model for online failure prognosis subject to two failure modes based on belief rule base and semi-quantitative information. Knowledge-Based Systems 70 (2014), 221–230.