Quality, Reliability and Maintenance Laboratory

The research in this laboratory is driven by practical problems such as the development of optimal policies for condition-based maintenance (CBM), the optimal multivariate quality control for both short and long production runs, and the development of optimal sampling schemes for monitoring partially observable stochastic processes.

Challenging theoretical problems include the analysis of structural properties of optimal control policies in the partially observable process framework as well as estimation and process modeling which includes the development of off-line and on-line model parameter estimation procedures and optimal filtering.

The practical applications include the development of fault detection schemes and diagnostic methods for on-line implementation in real CBM systems.

The top-notch research unique in the world has produced results published in the top international journals such as Operations Research, Mathematics of Operations Research, Journal of Applied Probability, Advances in Applied Probability, European Journal of OR and Naval Research Logistics. The recently published optimality results for multivariate quality and process control are the only such results published in the world.

Number of inventions have been developed which have been registered as IP Disclosures with UofT Research Council. Based on the research results and inventions obtained, a user-friendly software is currently under development with the sponsoring Canadian maintenance software development company Cetaris which will be implemented as a unique module in their CBM support software distributed worldwide, with majority of large client companies in the United States and Canada.

September 16, 2010: Technical Report MIE-OR-TR2010-10, Availability maximization under partial observations.

January 14, 2010: Technical Report MIE-OR-TR2010-01, Parameter Estimation for Partially Observable Systems Subject to Random Failure.

December 11, 2009: Download IMA Appendix Yin, Makis R2 09/12

Director: Viliam Makis, Ph.D., Dipl. Ing.
Contact email:
Phone: (416) 978 4631
Fax: (416) 978 7753
Lab location: MC314E