Abstract—Condition-based strategy refers to avoiding unnecessary maintenance and making timely actions through analyzing the received signals from monitoring devices. These signals sometimes may not be sensed, transmitted, or received precisely due to unexpected situations. Therefore, the fuzzy Bayesian model for condition monitoring of a system is proposed in this study. In order to apply the Bayesian concept, the fuzzy signals are assumed as fuzzy random variables with fuzzy prior distribution. Using the fuzzy signals, the newly developed model calculates the risk of operation for the system that results in determining the service time at minimum cost. A numerical example is also presented to demonstrate the application of the model.
Index Terms—Maintenance management, Condition-based maintenance, Fuzzy Bayesian decision theory
K. Jenab is a faculty member of the department of mechanical and industrial engineering at Ryerson University, Toronto, Canada, (corresponding author phone: 416-979-5000 ext6424; fax: 416-979-5265; e-mail: jenab@ryerson.ca).
K. Rashidi is MASc student in the department of mechanical and industrial engineering at Ryerson University. (e-mail: kamyar.rashidi@ryerson.ca).
Cite: K. Jenab and K. Rashidi, "Fuzzy Bayesian Condition Monitoring Model based on Exponential Distribution," International Journal of Engineering and Technology vol. 1, no. 2, pp. 172-178, 2009.
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