Purpose – The purpose of this paper is to review the literature on maintenance management and suggest possible gaps from the point of view of researchers and practitionersDesign/methodology/approach – The paper systematically categorizes the published literature and then analyzes and reviews it methodicallyFindings – The paper finds that important issues in maintenance management range from various optimization models, maintenance techniques, scheduling, and information systems etc Within each category, gaps have been identified A new shift in maintenance paradigm is also highlightedPractical implications – Literature on classification of maintenance management has so far been very limited This paper reviews a large number of papers in this field and suggests a classification in to various areas and sub areas Subsequently, various emerging trends in the field of maintenance management are identified to help researchers specifying gaps in the literature and direct research efforts suitablyOriginali

Maintenance management: literature review and directions

The objective of this work is to determine and study, analyze and elaborate, classify and categorize the main risk analysis and risk-assessment methods and techniques by reviewing the scientific literature. The paper consists of two parts: a) the investigation, presentation and elaboration of the main risk-assessment methodologies and b) the statistical analysis, classification, and comparative study of the corresponding scientific papers published by six representative scientific journals of Elsevier B.V. covering the decade 2000–2009. The scientific literature reviewing showed that the risk analysis and assessment techniques are classified into three main categories: (a) the qualitative, (b) the quantitative, and (c) the hybrid techniques (qualitative–quantitative, semi-quantitative). The qualitative techniques are based both on analytical estimation processes, and on the safety managers–engineers ability. According to quantitative techniques, the risk can be considered as a quantity, which can be estimated and expressed by a mathematical relation, under the help of real accidents’ data recorded in a work site. The hybrid techniques, present a great complexity due to their ad hoc character that prevents a wide spreading. The statistical analysis shows that the quantitative methods present the highest relative frequency (65.63%) while the qualitative a lower one (27.68%). Furthermore the hybrid methods remain constantly at a very low level (6.70%) during the entire processing period.

http://risktr.com/dokumanlar/risk%20analysis%20and%20assessment%20methodologies%20in%20th%20work%20sites.pdf

Risk analysis and assessment methodologies in the work sites: On a review, classification and comparative study of the scientific literature of the period 2000–2009

https://pscfiles.tamu.edu/symposia/2005/050%20Arunraj.pdf

Risk-based maintenance—Techniques and applications

Knowledge-assisted BIM-based visual analytics for failure root cause detection in facilities management

The unexpected failures, the down time associated with such failures, the loss of production and, the higher maintenance costs are major problems in any process plant. Risk-based maintenance (RBM) approach helps in designing an alternative strategy to minimize the risk resulting from breakdowns or failures. Adapting a risk-based maintenance strategy is essential in developing cost-effective maintenance policies. The RBM methodology is comprised of four modules: identification of the scope, risk assessment, risk evaluation, and maintenance planning. Using this methodology, one is able to estimate risk caused by the unexpected failure as a function of the probability and the consequence of failure. Critical equipment can be identified based on the level of risk and a pre-selected acceptable level of risk. Maintenance of equipment is prioritized based on the risk, which helps in reducing the overall risk of the plant. The case study of a power-generating unit in the Holyrood thermal power generation plant is used to illustrate the methodology. Results indicate that the methodology is successful in identifying the critical equipment and in reducing the risk of resulting from the failure of the equipment. Risk reduction is achieved through the adoption of a maintenance plan which not only increases the reliability of the equipment but also reduces the cost of maintenance including the cost of failure.

Development of a risk-based maintenance (RBM) strategy for a power-generating plant

The overall objective of the maintenance process is to increase the profitability of the operation and optimize the total life cycle cost without compromising safety or environmental issues. Risk assessment integrates reliability with safety and environmental issues and therefore can be used as a decision tool for preventive maintenance planning. Maintenance planning based on risk analysis minimizes the probability of system failure and its consequences (related to safety, economic, and environment). It helps management in making correct decisions concerning investment in maintenance or related field. This will, in turn, result in better asset and capital utilization. This paper presents a new methodology for risk-based maintenance. The proposed methodology is comprehensive and quantitative. It comprises three main modules: risk estimation module, risk evaluation module, and maintenance planning module. Details of the three modules are given. A case study, which exemplifies the use of methodology to a heating, ventilation and air-conditioning (HVAC) system, is also discussed.

Risk-based maintenance (RBM): a quantitative approach for maintenance/inspection scheduling and planning

Risk-Based Inspection and Maintenance (RBIM): Multi-Attribute Decision-Making with Aggregative Risk Analysis

Process plants deal with hazardous (highly flammable and toxic) chemicals at extreme conditions of temperature and pressure. Proper inspection and maintenance of these facilities is paramount for the maintenance of safe and continuous operation. This article proposes a risk-based methodology for integrity and inspection modeling (RBIIM) to ensure safe and fault-free operation of the facility. This methodology uses a gamma distribution to model the material degradation and a Bayesian updating method to improve the distribution based on actual inspection results. The method deals with the two cases of perfect and imperfect inspections. The measurement error resulting from imperfect inspections is modeled as a zero-mean, normally distributed random process. The risk is calculated using the probability of failure and the consequence is assessed in terms of cost as a function of time. The risk function is used to determine an optimal inspection and replacement interval. The calculated inspection and replacement interval is subsequently used in the design of an integrity inspection plan. Two case studies are presented: the maintenance of an autoclave and the maintenance of a pipeline segment. For the autoclave, the interval between two successive inspections is found to be 19 years. For the pipeline, the next inspection is due after 5 years from now. Measurements taken at inspections are used in estimating a new degradation rate that can then be used to update the failure distribution function.

https://papers.ssrn.com/sol3/Delivery.cfm/risk_705.pdf?abstractid=943190&mirid=1

Risk‐Based Integrity and Inspection Modeling (RBIIM) of Process Components/System

The objective of this paper is to estimate the sample size required to assess the maximum pit size over an entire asset that is subject to pitting corrosion. The Bayesian updating approach and the extreme value method are integrated into a single proposed framework to estimate the sample size. The extreme value method is used to predict the maximum pit size by extrapolating the inspected area (sample) to the entire asset's area. The Bayesian updating approach is used to update prior information obtained from the previous inspection once newly obtained information is available from the current inspection. The estimated sample size ensures that the predicted maximum pit size over the entire asset is within an acceptable margin of error at a specified confidence level. Using the proposed framework, two closed-form formulae are developed for calculating the sample size required to assess pitting corrosion. The two formulae address the two situations when prior information is either available or unavailable. These formulae are compared to the classical method for calculating the sample size through a case study of a pipeline subject to pitting corrosion. The comparison shows that the sample size estimated with the classical method is not large enough to assess the maximum pit size over the entire pipeline.

Inspection sampling of pitting corrosion

The objective of this paper is to select the optimum non-destructive inspection (NDI) technique and its associated in-service inspection interval for welded components subjected to cyclic loading fatigue. The objective function (total cost) is formulated as a function of the decision variables (controllable) and the condition of the inspected asset (uncontrollable). Total cost consists of inspection cost and repair cost over the lifetime of the asset in addition to the cost of unexpected failure as a result of failure to detect a growing crack before reaching a critical size. The decision variables are the reliability of the NDI technique and the inspection interval. Two main parameters are used to quantify the reliability of NDI techniques. These are the Probability of Detection function (POD) and the Probability of False Calls (PFC). The condition of the inspected asset is represented by the probability of existence of a crack in the asset at the inspection time and the expected critical time to failure. The objective function is minimised for different NDI techniques subject to a safety constraint that the probability of failure does not exceed a predefined level. The NDI with the lowest objective function level is chosen as the preferred solution.

Mahmoud M. Haddara

Papers

Risk-based maintenance (RBM): a quantitative approach for maintenance/inspection scheduling and planning

Risk-Based Inspection and Maintenance (RBIM): Multi-Attribute Decision-Making with Aggregative Risk Analysis

Risk‐Based Integrity and Inspection Modeling (RBIIM) of Process Components/System

Inspection sampling of pitting corrosion

Optimal selection of non-destructive inspection technique for welded components