TY - JOUR
T1 - Bivariate preventive maintenance of systems with lifetimes dependent on a random shock process
AU - Cha, Ji Hwan
AU - Finkelstein, Maxim
AU - Levitin, Gregory
N1 - Funding Information:
The authors thank the referees for helpful comments and constructive suggestions. The work of the first author was supported by Priority Research Centers Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology ( 2009-0093827 ). The work of the second author was supported by the National research foundation (NRF) of South Africa (Grant No: 103613 ).
Publisher Copyright:
© 2017 Elsevier B.V.
PY - 2018/4/1
Y1 - 2018/4/1
N2 - We consider a bivariate model for preventive maintenance for items operating in a random environment modeled by a Poisson process of shocks. An item is replaced either on failure or on the predetermined replacement time or on a shock with the predetermined number, whichever comes first. Each shock in our stochastic model has a double effect. First, it acts directly on the failure rate of an item, which results in the corresponding stochastic intensity process, secondly, each shock causes additional ‘damage’ which can be attributed, e.g., to a short drop in the output of a system. The corresponding bivariate optimization problem is considered and illustrated by detailed numerical examples.
AB - We consider a bivariate model for preventive maintenance for items operating in a random environment modeled by a Poisson process of shocks. An item is replaced either on failure or on the predetermined replacement time or on a shock with the predetermined number, whichever comes first. Each shock in our stochastic model has a double effect. First, it acts directly on the failure rate of an item, which results in the corresponding stochastic intensity process, secondly, each shock causes additional ‘damage’ which can be attributed, e.g., to a short drop in the output of a system. The corresponding bivariate optimization problem is considered and illustrated by detailed numerical examples.
KW - Bivariate optimization
KW - Intensity process
KW - Maintenance
KW - Poisson shock process
KW - Preventive maintenace
UR - http://www.scopus.com/inward/record.url?scp=85032221089&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2017.09.021
DO - 10.1016/j.ejor.2017.09.021
M3 - Article
AN - SCOPUS:85032221089
SN - 0377-2217
VL - 266
SP - 122
EP - 134
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -