Condition-based maintenance policy optimization using genetic algorithms and Gaussian Markov improvement algorithm
Michael Hoffman, Eunhye Song, Michael Brundage, Soundar R. Kumara
Condition-based maintenance involves monitoring the degrading health of machines in a manufacturing system and scheduling maintenance to avoid costly unplanned failures. As compared with preventive maintenance, which maintains machines on a set schedule based on time or run time of a machine, condition-based maintenance attempts to minimize the number of times maintenance is performed on a machine while still attaining a prescribed level of availability to save on maintenance costs and reduce unwanted downtime over its lifetime. Finding an analytically-optimal condition-based maintenance policy is difficult when the target system has non-uniform machines, stochastic maintenance time, and capacity constraints on maintenance resources. In this work, we find an optimal condition-based maintenance policy for a serial manufacturing line using a genetic algorithm and Gaussian Markov Improvement Algorithm, an optimization via simulation method for a stochastic problem with a discrete solution space. The effectiveness of these two algorithms will be compared. When a maintenance job (i.e., machine) is scheduled, it is placed in a queue that is serviced with either a first-in-first-out discipline or based on a priority. In the latter, we apply the concept of opportunistic window to identify a machine that has the largest potential to disrupt the production of the system and assign a high priority to the machine. A test case is presented to demonstrate this method and its improvement over traditional maintenance methods.
Proceedings of the Annual Conference of the Prognostics and Health Management Society 2018
September 24-27, 2018
Philadelphia, PA, US
Annual Conference of the Prognostics and Health Management Society 2018
, Song, E.
, Brundage, M.
and Kumara, S.
Condition-based maintenance policy optimization using genetic algorithms and Gaussian Markov improvement algorithm, Proceedings of the Annual Conference of the Prognostics and Health Management Society 2018, Philadelphia, PA, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=926343
(Accessed December 5, 2023)