A Multivariate Gamma Process for Dependent Degradation Modelling and Life Phenomena

Remaining service life of infrastructure assets is governed by functionality and structural integrity, both deteriorate with time. In this paper, we propose a multivariate gamma process model to model the stochastically dependent deterioration phenomena that collectively define the asset life. The temporal uncertainty is characterized by nonstationary gamma processes with independent increments while dependence among degradation processes is characterized with a correlation matrix in the copula space. Parameter estimation is done by the maximum likelihood method. For the lifetime prediction, a component experiencing multiple degradation phenomena is said to fail based on a number of scenarios. So the remaining lifetime distribution will be based on the current state of the component as well as failure thresholds of all phenomena. The proposed methodology is illustrated with a case study of a highway pavement experiencing multiple degradation such as rutting, cracking, and surface smoothness

Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency

[EN] The reliability, availability and maintainability (RAM) modelling of safety equipment has long been a topic of major concern. Some RAM models have focused on explicitly addressing the effect of component degradation and surveillance and maintenance policies, searching for an optimum level of the safety component RAM by adjusting surveillance and maintenance related parameters. As regards the reliability contribution, these components normally have two main types of failure mode that contribute to the probability of failure on demand (PFD): (1) by demand-caused and (2) standby-related failures. The former is normally associated with a demand failure probability, which is affected by the degradation caused by demand-related stress. Surveillance testing therefore not only introduces a positive effect, but also an adverse one, which it compensates by performing maintenance activities to eliminate or reduce the accumulated degradation. This paper proposes a new model for the demand failure probability that explicitly addresses all aspects of the effect of demand-induced stress (mostly test-induced stress), maintenance effectiveness (PAS or PAR model) and test efficiency. A case study is included on an application to a typical motor-operated valve in a nuclear power plant.The authors are grateful to the Spanish Ministry of Science and Innovation for the financial support received (Research Projects ENE2013-45540-R and ENE2016-80401-R) and the doctoral scholarship awarded (BES-2014-067602). The study also received financial support from the Spanish Research Agency and the European Regional Development Fund.Martorell-Aygues, P.; Martón Lluch, I.; Sánchez Galdón, AI.; Martorell Alsina, SS. (2017). Unavailability model for demand-caused failures of safety components addressing degradation by demand-induced stress, maintenance effectiveness and test efficiency. Reliability Engineering & System Safety. 168:18-27. https://doi.org/10.1016/j.ress.2017.05.044S182716

Appropriate building repair and maintenance strategies using multicriteria decision-making analysis – a Delphi study

As an influential and significant factor in improving the service of building components and elements, maintenance plays an essential role in maintaining reliability, availability, and quality, as well as increasing efficiency and security. Therefore, how to define this maintenance system and determine the appropriate criteria and strategies for that play an important role in the cost and longevity of the buildings after construction and during their operation. The purpose of the article is to determine the effective criteria for evaluating buildings based on maintenance and repair (R&M) and finally determining the appropriate strategy for the maintenance of residential buildings, using multicriteria decision-making methods. These criteria were first identified by reviewing the literature and using the Delphi method to obtain the opinions of maintenance experts. The criteria were then prioritized, based on the SWARA method, and the results were compared and evaluated. Based on comparison, safety, health, environment, and proper utilisation were rated the top four criteria to consider for building R&M. Finally, using the VIKOR2 method, it was found that the breakdown maintenance (BM) and corrective maintenance (CM) strategies are the best strategies to use for the R&M of residential buildings

Condition-based maintenance for a system subject to multiple degradation processes with stochastic arrival intensity

In this work, a system subject to different deterioration processes is analysed. The arrival of the degradation processes to the system is modelled using a shot-noise Cox process. The degradation processes grow according to an homogeneous gamma process. The system fails when a degradation process exceeds a failure threshold. The combined process of initiation and growth of the degradation processes is modelled and the system reliability is obtained. Heterogeneities are also integrated in the model assuming that the inverse of the scale parameter follows a uniform distribution. A maintenance strategy is implemented in this system and the state of the system is checked in inspection times. If the system is working at inspection time, a preventive replacement is performed if the deterioration level of a degradation process exceeds a certain threshold. A corrective replacement is performed if the system is down at inspection time. Under this maintenance strategy, the expected cost rate is obtained. Sensitivity analysis on the main parameters of the gamma process is performed.Comment: 30 pages, 10 figure

Optimising Maintenance Cost by Prioritising Maintenance of Facilities Services in Residential Buildings

Purpose – The paper illustrates the maintenance prioritising for facilities services in high-rise residential buildings in Peninsular Malaysia. Maintenance prioritisation is becoming more prominent in the building maintenance industry due to budget constraints, poor maintenance management and to yield better maintenance performance. Design/methodology/approach – Two main categories with eleven facilities services that require maintenance were identified through extensive literature review. A total of 321 returned questionnaires were analysed to distinguish the relationship between the maintenance priority and cost variance. Semi-structured interviews were then conducted to validate the findings. Findings – The findings revealed that five essential facilities services were significantly correlated to cost variance and a prediction model which examines the probability of over-budget was developed. Meanwhile, the interviews recognised that maintenance prioritisation has impact towards maintenance cost. Research limitations/implications – This research focuses on the maintenance priorities of facilities services and their effects to maintenance cost. However, it is undeniable that the maintenance cost can be affected by other factors, contributing to a lower percentage of the total variance in the prediction model. Thus, it creates research opportunity to study the factors (i.e. manpower, materials, wear and tear, etc.) affecting the variance of maintenance cost. Practical implications – This study is useful to property managers in efforts to enhance the cost performance via appropriate maintenance prioritisation. The essential facilities services should be highly prioritised compared to the value-added facilities services. Originality/value – The paper signifies the importance of maintenance prioritisation. It serves as a guide to plan and execute maintenance planning in a more logical way within budget and time constraints. Keywords: maintenance priority, facilities services, residential, high-rise building, building maintenance, maintenance cos

Condition-based maintenance for systems with aging and cumulative damage based on proportional hazards model

This paper develops a condition-based maintenance (CBM) policy for systems subject to aging and cumulative damage. The cumulative damage is modeled by a continuous degradation process. Different from previous studies which assume that the system fails when the degradation level exceeds a specific threshold, this paper argues that the degradation itself does not directly lead to system failure, but increases the failure risk of the system. Proportional hazards model (PHM) is employed to characterize the joint effect of aging and cumulative damage. CBM models are developed for two cases: one assumes that the distribution parameters of the degradation process are known in advance, while the other assumes that the parameters are unknown and need to be estimated during system operation. In the first case, an optimal maintenance policy is obtained by minimizing the long-run cost rate. For the case with unknown parameters, periodic inspection is adopted to monitor the degradation level of the system and update the distribution parameters. A case study of Asphalt Plug Joint in UK bridge system is employed to illustrate the maintenance policy.The work described in this paper was partially supported by a theme-based project grant (T32-101/15-R) of University Grants Council, and a Key Project (71532008) supported by National Natural Science Foundation of China

Maintenance optimization in industry 4.0

This work reviews maintenance optimization from different and complementary points of view. Specifically, we systematically analyze the knowledge, information and data that can be exploited for maintenance optimization within the Industry 4.0 paradigm. Then, the possible objectives of the optimization are critically discussed, together with the maintenance features to be optimized, such as maintenance periods and degradation thresholds. The main challenges and trends of maintenance optimization are, then, highlighted and the need is identified for methods that do not require a-priori selection of a predefined maintenance strategy, are able to deal with large amounts of heterogeneous data collected from different sources, can properly treat all the uncertainties affecting the behavior of the systems and the environment, and can jointly consider multiple optimization objectives, including the emerging ones related to sustainability and resilience