Using Risk Based Maintenance Optimization RBMO to Save Costs

2021 ◽  
Author(s):  
Khaled Ahmed Farouk Mohamed
Keyword(s):  
Risk Mitigation ◽  
Critical Item ◽  
Cost Benefit ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Critical Systems ◽  
Risk Matrix ◽  
Monetary Value ◽  
Maintenance Program ◽  
Systems Maintenance

Abstract Maintenance is a crucial pillar in plant integrity and availability. Saving money in maintenance should be established without affecting the asset's integrity. Based on this, the core of work is to maximize the maintenance return on investment (ROI). Maintenance ROI is the ratio between invested money in maintenance to mitigated risks due to maintenance actions. The objective is to minimize maintenance cost while maximizing assets integrity and availability. RBMO starts with ‘Maintenance Criticality Assessment’ (MCA) at unit/system level to define high (20 % of systems that represent 80% of risks), medium (20% of systems that represent 15% of risks), and low critical systems (60% of systems that represent only 5% of risks). Based on system criticality, a dedicated risk assessment is implemented to evaluate risks at tag level to define the worst maintenance action/s. High critical systems’ maintenance programs are developed using ‘Reliability-Centered Maintenance’ (RCM). Medium critical system maintenance program is developed using ‘Failure Mode, Effects and criticality analysis’ (FMECA). "Maintenance strategy for Low Critical item" guideline document is developed to define the best maintenance strategy for low critical units. All risks are evaluated using the standard ADNOC risk matrix. The risk is converted to monetary value in $ to evaluate maintenance actions using a formula. A special program was developed to facilitate MCA evaluation for each system and represent risk as monetary value using ADNOC Risk Matrix taking into consideration the redundancy and demand on a system during operation. MCAs were completed for all ADNOC Onshore Assets, see results below. Optimization starts by evaluating maintenance programs for low critical systems to save costs where low critical systems represent 50% to 60% of total systems in ADNOC Onshore. Based on this the total number of work orders has decreased by 6856, which is equivalent to saving $1M annually. In parallel, RCMs are conducted on high critical systems. Risk mitigation calculator in $ value was developed and embedded in the RCM information sheet to calculate cost benefit from implementing maintenance programs that were developed. RBMO is a systematic and traceable methodology to minimize maintenance cost and at the same time maximize system integrity and availability. This work showed the importance of reviewing the low critical systems’ maintenance program, as a first step in RBMO after implementing MCA, where low critical systems represent 50% to 60% of total assets and only 5% of total risks. ADNOC Onshore developed a dedicated guideline document "Maintenance Strategy for Low Critical Item" to facilitate decision making for proper maintenance strategy for low critical systems. Adding RCM risk mitigation calculator to RCM to calculate RCM cost benefit.

scholarly journals Reliability Guarantee Strategy for Complex System Based on Cost-Benefit Importance

2020 ◽  
Vol 38 (6) ◽  
pp. 1316-1321
Author(s):  
Cheng Wang ◽  
Jianxin Xu ◽  
Zhenming Zhang ◽  
Hongjun Wang
Keyword(s):  
Complex System ◽  
System Reliability ◽  
Cost Benefit ◽  
Maintenance Cost ◽  
Critical Systems ◽  
Preventive Replacement ◽  
Equipment Safety ◽  
Operation Process ◽  
The Cost ◽  
Component Replacement

In order to ensure the long-term stable and economic operation of complex system, the system operation process is described and the problems is solved, and a system reliability model and an optimization model for component replacement are constructed. Based on the theory of marginal utility and importance measures, a reliability guarantee strategy for complex system based on cost-benefit importance is presented, which aims to find a component preventive replacement sequence with minimum maintenance cost on the constraints of system reliability lower threshold and running time. When the system reliability drops to a preset threshold, the cost-benefit importance of each component is calculated, the component with the greatest cost-benefit importance to replace is selected, and then iterate until the operation task is completed to form an optimal component replacement sequence. The feasibility of the present strategy is verified by taking a complex system which can be equivalent to a series-parallel system as an example. The present strategy has certain reference significance of ensuring the reliable operation of some high-end equipment safety-critical systems.

scholarly journals Analisa sistem perawatan pada mesin las MIG dengan metode Failure Mode and Effect Analysis: Studi kasus di PT. TE

2020 ◽  
Vol 12 (1) ◽  
pp. 13
Author(s):  
Alloysius Vendhi Prasmoro
Keyword(s):  
Failure Mode ◽  
Production Systems ◽  
Maintenance Strategy ◽  
Risk Matrix ◽  
Strategy Analysis ◽  
Effect Analysis ◽  
Whole Process ◽  
Maintenance Program ◽  
Study Results

Maintenance is a process that is done to maintain the reliability, availability and the nature of being able to take care of the components or machines. Maintenance program that will effectively and efficiently support the increase in productivity of production systems. But often ignored the needs of actual maintenance program of components or machines. To get the program effective and efficient maintenance required maintenance study based on reliability. Reliability Centered Maintenance (RCM) is a systematic risk-based analysis to create a maintenance method accurate, focused, and optimal with the aim of achieving optimal reliability of assets. RCM studies have been done on the machinery industry, one welding machine industry, carrosserie. The study was conducted by following these RCM, which is the determination of the scope of the study, Failure Mode and Effect Analysis (FMEA), and the determination of the maintenance strategy. Analysis of the risk based on risk matrix drawn up through consensus of all stakeholders.  Risk matrix covers the areas the incidence (occurrence), detection, as well as the level of risk (severity). Subsequently based on this calculated risk matrix Risk Priority Number (RPN). Based on the RPN value, a maintenance strategy is proposed for each type of failure mode.  The whole process is aided by the use of RCM software Minitab 18 made specifically for this purpose.  This study results that the value of the RPN for all equipment ranges from 72 to 900.Study of the RCM have also managed to establish a maintenance strategy appropriate for each failure mode, which provided the basis for drafting the new maintenance program.

scholarly journals A Framework for Risk-Based Cost–Benefit Analysis for Decision Support on Hydrogeological Risks in Underground Construction

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 82
Author(s):  
Johanna Merisalu ◽  
Jonas Sundell ◽  
Lars Rosén
Keyword(s):  
Decision Support ◽  
Cost Benefit Analysis ◽  
Risk Mitigation ◽  
Ground Surface ◽  
Cost Benefit ◽  
Expert Elicitation ◽  
Benefit Analysis ◽  
Underground Construction ◽  
Groundwater Leakage ◽  
Risk Reducing

Construction below the ground surface and underneath the groundwater table is often associated with groundwater leakage and drawdowns in the surroundings which subsequently can result in a wide variety of risks. To avoid groundwater drawdown-associated damages, risk-reducing measures must often be implemented. Due to the hydrogeological system’s inherent variability and our incomplete knowledge of its conditions, the effects of risk-reducing measures cannot be fully known in advance and decisions must inevitably be made under uncertainty. When implementing risk-reducing measures there is always a trade-off between the measures’ benefits (reduced risk) and investment costs which needs to be balanced. In this paper, we present a framework for decision support on measures to mitigate hydrogeological risks in underground construction. The framework is developed in accordance with the guidelines from the International Standardization Organization (ISO) and comprises a full risk-management framework with focus on risk analysis and risk evaluation. Cost–benefit analysis (CBA) facilitates monetization of consequences and economic evaluation of risk mitigation. The framework includes probabilistic risk estimation of the entire cause–effect chain from groundwater leakage to the consequences of damage where expert elicitation is combined with data-driven and process-based methods, allowing for continuous updating when new knowledge is obtained.

scholarly journals The ALARP Principle in the Cost-Benefit Analysis for the Acceptability of Investment Risk

2018 ◽  
Vol 10 (12) ◽  
pp. 4668 ◽  
Author(s):  
Antonio Nesticò ◽  
Shuquan He ◽  
Gianluigi De Mare ◽  
Renato Benintendi ◽  
Gabriella Maselli
Keyword(s):  
Cost Benefit Analysis ◽  
Risk Mitigation ◽  
Cost Benefit ◽  
Economic Evaluations ◽  
Investment Risk ◽  
Benefit Analysis ◽  
Mitigation Design ◽  
The Cost

The process of allocating financial resources is extremely complex—both because the selection of investments depends on multiple, and interrelated, variables, and constraints that limit the eligibility domain of the solutions, and because the feasibility of projects is influenced by risk factors. In this sense, it is essential to develop economic evaluations on a probabilistic basis. Nevertheless, for the civil engineering sector, the literature emphasizes the centrality of risk management, in order to establish interventions for risk mitigation. On the other hand, few methodologies are available to systematically compare ante and post mitigation design risk, along with the verification of the economic convenience of these actions. The aim of the paper is to demonstrate how these limits can be at least partially overcome by integrating, in the traditional Cost-Benefit Analysis schemes, the As Low as Reasonably Practicable (ALARP) logic. According to it, the risk is tolerable only if it is impossible to reduce it further or if the costs to mitigate it are disproportionate to the benefits obtainable. The research outlines the phases of an innovative protocol for managing investment risks. On the basis of a case study dealing with a project for the recovery and transformation of an ancient medieval village into a widespread-hotel, the novelty of the model consists of the characterization of acceptability and tolerability thresholds of the investment risk, as well as its ability to guarantee the triangular balance between risks, costs and benefits deriving from mitigation options.

Optimization of equal-cycle maintenance strategy considering imperfect preventive maintenance

2021 ◽  
pp. 095440892110638
Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Action Unit ◽  
Cost Rate ◽  
Equipment Reliability ◽  
Optimal Maintenance ◽  
Important Means ◽  
Maintenance Decision

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

Public policy issues: Earthquake prediction

1979 ◽  
Vol 69 (5) ◽  
pp. 1533-1547
Author(s):  
Marie-Elisabeth Paté ◽  
Haresh C. Shah
Keyword(s):  
San Francisco ◽  
Earthquake Prediction ◽  
Earthquake Engineering ◽  
Cost Benefit Analysis ◽  
Risk Mitigation ◽  
Monitoring Program ◽  
Cost Benefit ◽  
Economic Life ◽  
Prediction Program ◽  
Prediction Techniques

abstract The object of this paper is to provide a method of cost-benefit analysis of earthquake prediction as a means of mitigation of earthquake effects. The research in earthquake prediction may or may not be successful and involves an initial cost. Earthquake prediction, if achieved, on the one hand provides society with information which allows it to take protective measures. On the other hand, each prediction involves the costs of those measures and the consequent disruption of economic life. The question is to assess the value of such information in a given state of the prediction technology. The evaluation of a fault-monitoring program and its consequences for the public at the time of predictions is performed over a 50-year period. A rate of growth, a social rate of discount, and a rate of improvement over time of earthquake prediction techniques are assumed. A model “TREE” is developed; it allows computation, for each year, of the expected value of the earthquake prediction information—expected costs minus expected benefits. The life component and the dollar component of the net result are kept separate throughout the evaluation. The final result is an expected cost per life saved through the earthquake prediction program over a 50-year time period. This allows comparison with the results of earthquake engineering and building codes (see Paté, 1978). It also allows comparison with the results obtained in other public sectors involving risk mitigation—health and transportation, for example. A numerical example has been worked out for the case of the San Francisco Bay Area; it gives a first approach to the results that can be expected from a prediction system with different assumptions on the success of research in that field. This paper is based on the doctoral thesis at Stanford University of M-E. Paté, under the supervision of Professor H. C. Shah.

scholarly journals Adaptive decision support for suggesting a machine tool maintenance strategy

2018 ◽  
Vol 24 (3) ◽  
pp. 376-399 ◽  
Author(s):  
Abubaker Shagluf ◽  
Simon Parkinson ◽  
Andrew Peter Longstaff ◽  
Simon Fletcher
Keyword(s):  
Decision Support ◽  
Machine Tool ◽  
Cost Estimation ◽  
Expert Knowledge ◽  
Production Costs ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Content Type ◽  
Machine Tool Accuracy

Purpose The purpose of this paper is to produce a decision support aid for machine tool owners to utilise while deciding upon a maintenance strategy. Furthermore, the decision support tool is adaptive and capable of suggesting different strategies by monitoring for any change in machine tool manufacturing accuracy. Design/methodology/approach A maintenance cost estimation model is utilised within the research and development of this decision support system (DSS). An empirical-based methodology is pursued and validated through case study analysis. Findings A case study is provided where a schedule of preventative maintenance actions is produced to reduce the need for the future occurrences of reactive maintenance actions based on historical machine tool accuracy information. In the case study, a 28 per cent reduction in predicted accuracy-related expenditure is presented, equating to a saving of £14k per machine over a five year period. Research limitations/implications The emphasis on improving machine tool accuracy and reducing production costs is increasing. The presented research is pioneering in the development of a software-based tool to help reduce the requirement on domain-specific expert knowledge. Originality/value The paper presents an adaptive DSS to assist with maintenance strategy selection. This is the first of its kind and is able to suggest a preventative strategy for those undertaking only reactive maintenance. This is of value for both manufacturers and researchers alike. Manufacturers will benefit from reducing maintenance costs, and researchers will benefit from the development and application of a novel decision support technique.

An Approach for Cost Effective Assessment in Risk-Based Maintenance as a Life-Cycle Maintenance (LCM) Model

2004 ◽  
Author(s):  
Masataka Yatomi ◽  
Akio Fuji ◽  
Noriko Saito ◽  
Toshiaki Yoshida
Keyword(s):  
Life Cycle ◽  
Power Plants ◽  
Cost Effective ◽  
Life Extension ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Original Design ◽  
Maintenance Strategies ◽  
Effective Assessment ◽  
Maintenance Plan

For aged power plants in Japan, the life extension with retaining the safety and cost-effective beyond the original design lifetime is proposed. Therefore it is important to minimise the risk and maintenance cost to keep operating the plants. Life-Cycle Maintenance (LCM) is proposed for optimising maintenance plan with reliability in the life of the plants. Risk Based Maintenance (RBM) is included in the LCM to assess the risk of components in the plants. LCC and the investment assessment may be also conducted to decide the most cost effective maintenance strategy, if several maintenance strategies are proposed in RBM. In this paper, concept and an application of the LCM are described to optimise maintenance plan in the lifetime of a plant. It was found that the LCM is quite useful method to plan the most cost effective maintenance strategies in the lifetime of the plant.

scholarly journals A data-driven predictive maintenance strategy based on accurate failure prognostics

2021 ◽  
Vol 23 (2) ◽  
pp. 387-394
Author(s):  
Chuang Chen ◽  
Cunsong Wang ◽  
Ningyun Lu ◽  
Bin Jiang ◽  
Yin Xing
Keyword(s):  
Predictive Maintenance ◽  
Data Driven ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Engineering Systems ◽  
Data Set ◽  
Periodic Maintenance ◽  
Maintenance Decisions ◽  
Aero Engines ◽  
Failure Prognostics

Maintenance is fundamental to ensure the safety, reliability and availability of engineering systems, and predictive maintenance is the leading one in maintenance technology. This paper aims to develop a novel data-driven predictive maintenance strategy that can make appropriate maintenance decisions for repairable complex engineering systems. The proposed strategy includes degradation feature selection and degradation prognostic modeling modules to achieve accurate failure prognostics. For maintenance decision-making, the perfect time for taking maintenance activities is determined by evaluating the maintenance cost online that has taken into account of the failure prognostic results of performance degradation. The feasibility and effectiveness of the proposed strategy is confirmed using the NASA data set of aero-engines. Results show that the proposed strategy outperforms the two benchmark maintenance strategies: classical periodic maintenance and emerging dynamic predictive maintenance.

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