-
optimisation models (TODO)
-
not started
-
-
weibull estimation
-
2p complete
-
rank regression (NA)
-
MLE
-
graph
-
confidence interval (hessian, 1 and 2 side)
-
-
-
2p censored
-
rank regression
-
graph
-
confidence interval (median rank)
-
-
MLE
-
graph
-
confidence interval (hessian, 1 and 2 side)
-
-
-
auto selection of fit method
-
-
3p complete
-
rank regression.
-
MLE (todo)
-
Utilisation of information collected by CMMS (computerised maintenance management systems) for improving a maintenance policy is a long-standing problem. In many organisations failure and cost data from their asset is not used at all. This tool will automatically choose most suitable maintenance policy by solving optimisation problems.
-
Component replacement interval
-
Inspection interval
-
Capital equipment replacement interval
-
Maintenance resource requirements
-
Cost.
-
Maintenance cost
-
Operation cost
-
Replacement cost
-
-
Failure rate. WEMIOT has its own module for evaluation parameters of Weibull distribution based on failure information from CMMS.
-
Labib, Ashraf W. "A decision analysis model for maintenance policy selection using a CMMS." Journal of Quality in Maintenance Engineering (2004).
-
Jardine, Andrew KS, and Albert HC Tsang. Maintenance, replacement, and reliability: theory and applications. CRC press, 2013.
-
Aggarwal, Charu C. Linear Algebra and Optimization for Machine Learning: A Textbook. Springer Nature, 2020.