A review on condition-based maintenance optimization models for stochastically deteriorating system

© 2016 Elsevier Ltd Condition-based maintenance (CBM) is a maintenance strategy that collects and assesses real-time information, and recommends maintenance decisions based on the current condition of the system. In recent decades, research on CBM has been rapidly growing due to the rapid development of computer-based monitoring technologies. Research studies have proven that CBM, if planned properly, can be effective in improving equipment reliability at reduced costs. This paper presents a review of CBM literature with emphasis on mathematical modeling and optimization approaches. We focus this review on important aspects of the CBM, such as optimization criteria, inspection frequency, maintenance degree, solution methodology, etc. Since the modeling choice for the stochastic deterioration process greatly influences CBM strategy decisions, this review classifies the literature on CBM models based on the underlying deterioration processes, namely discrete- and continuous-state deterioration, and proportional hazard model. CBM models for multi-unit systems are also reviewed in this paper. This paper provides useful references for CBM management professionals and researchers working on CBM modeling and optimization

A sequential inspection and replacement policy for degradation-based systems

© 2017 IEEE. Condition-based maintenance (CBM) has been extensively studied. However, the majority of existing CBM research either consider a periodic inspection schedule or a fixed preventive maintenance threshold. While policies with periodic inspections and/or fixed maintenance threshold are easy to implement in practice, they may incur more-than-necessary inspections and induce more failures. In this paper, we develop a sequential CBM policy for systems subject to stochastic degradation. The aim of the proposed policy is to prevent or delay failures and perform maintenance activities just in time. Unlike conventional preventive maintenance that often fixes the inspection interval and the preventive maintenance threshold, both the next inspection time and the corresponding maintenance threshold in this paper are dynamically determined based on the current state of the system. The proposed sequential predictive maintenance policy is particularly important and applicable for general non-homogeneous degradation processes. The proposed model enables optimal scheduling of inspection and preventive maintenance decisions, in order to minimize the long-run maintenance cost rate including inspection, preventive and corrective maintenance costs. The performance of the proposed predictive maintenance policy is evaluated using a simulation-based optimization approach. Frequency of system failures and total maintenance cost rates are computed and compared with a bench mark maintenance policy, a periodic inspection/replacement policy. Our results show that there can be potential savings from the proposed predictive maintenance policy

Reliability Analysis of Crude Unit Overhead Piping Based on Wall Thickness Degradation Process

Assuring the reliability of crude unit pipelines in the downstream oil and gas industry is highly essential since unexpected failures of these pipelines can result in a number of negative impacts to the business, including safety, environmental, and economic impacts. The objective of this work is to understand the degradation behavior of the piping system so we can know in advance when the degraded pipeline will reach the minimum thickness threshold

Condition-based maintenance using the inverse Gaussian degradation model

10.1016/j.ejor.2014.11.029European Journal of Operational Research2431190-19

Optimal maintenance policies for degrading hydrocarbon pipelines using Markov decision process

© 2020 IEEE. The random nature of deterioration of piping systems used to transport hydrocarbons, is identified by periodic or continuous inspection. At a minimum threshold tmin of pipe wall thickness, the pipeline is in a failed state, with a leak or pipe rapture imminent.We modeled the maintenance policy of a pipeline, based on an infinite horizon Markov decision process, taking into consideration the current state of the pipe, the action performed and the transition probabilities from one state to the other. This provides an optimal decision-making strategy or policy to minimize total maintenance cost