scholarly journals Risk-Based Predictive Maintenance for Safety-Critical Systems by Using Probabilistic Inference

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Tianhua Xu ◽  
Tao Tang ◽  
Haifeng Wang ◽  
Tangming Yuan
Keyword(s):  
High Speed ◽  
Probabilistic Inference ◽  
Evolution Model ◽  
Predictive Maintenance ◽  
Maintenance Cost ◽  
Dynamic Evolution ◽  
Critical Systems ◽  
Maintenance Time ◽  
Safety Constraints ◽  
Optimal Maintenance

Risk-based maintenance (RBM) aims to improve maintenance planning and decision making by reducing the probability and consequences of failure of equipment. A new predictive maintenance strategy that integrates dynamic evolution model and risk assessment is proposed which can be used to calculate the optimal maintenance time with minimal cost and safety constraints. The dynamic evolution model provides qualified risks by using probabilistic inference with bucket elimination and gives the prospective degradation trend of a complex system. Based on the degradation trend, an optimal maintenance time can be determined by minimizing the expected maintenance cost per time unit. The effectiveness of the proposed method is validated and demonstrated by a collision accident of high-speed trains with obstacles in the presence of safety and cost constrains.

scholarly journals A Study on the Predictive Maintenance Method of Fully Mechanized Mining Equipment based on Cost and Time Factors

2021 ◽  
Author(s):  
Xiangang Cao ◽  
Tianbo Xu ◽  
Youjun Zhao ◽  
Jiangbin Zhao ◽  
Yan Wang
Keyword(s):  
Time Factors ◽  
Predictive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Planning ◽  
Mining Equipment ◽  
Cost Rate ◽  
Maintenance Time ◽  
Maintenance Cycle ◽  
Optimal Maintenance ◽  
Single Objective

Abstract In view of the problems of excessive maintenance and insufficient utilization of equipment service life caused by preventive maintenance of fully mechanized mining equipment with fixed cycle, a predictive maintenance method is proposed. Firstly, based on Weibull distribution function and evolution rules of equipment decay, the evolution model of equipment failure rate is established; Then, the single-objective decision-making models of equipment maintenance cost rate and maintenance downtime rate are established respectively. On this basis, the multi-objective predictive maintenance planning model of fully mechanized mining equipment with comprehensive cost and time factors is established, and the optimal predictive maintenance cycle planning sequence is obtained. Combined with the coal production continuation plan, this paper puts forward a method to determine the optimal maintenance time by making suitable choices between advance maintenance and delay maintenance. The result confirms the effectiveness and superiority of the proposed method.

A preventive, opportunistic maintenance strategy for the catenary system of high-speed railways based on reliability

2019 ◽  
Vol 234 (10) ◽  
pp. 1149-1155
Author(s):  
Hongbo Cheng ◽  
Yufan Cao ◽  
Jiaxin Wang ◽  
Wei Zhang ◽  
Han Zeng
Keyword(s):  
High Speed ◽  
Maintenance Cost ◽  
Opportunistic Maintenance ◽  
Maintenance Schedule ◽  
Maintenance Time ◽  
Study Results ◽  
Railway System ◽  
Vital Component ◽  
Catenary System ◽  
Maintenance Schedules

The catenary is a vital component of the electrified railway system. It consists of many parts which are interrelated; the maintenance schedule of the catenary system should consider the influence of the interrelationship. In this study, a preventive, opportunistic maintenance method is proposed to schedule the maintenance process of the catenary system. First, the reliability of the key parts of the catenary is modeled using Weibull distribution. Second, a reliability margin is proposed to expand the maintenance time from point to interval, and the reliability margin is optimized to minimize the maintenance cost. Then, a preventive opportunistic maintenance schedule can be arranged on the basis of the optimal reliability margin. Case study results verify that the proposed preventive opportunistic maintenance method can reduce the number of maintenance schedules and can effectively save the maintenance cost.

scholarly journals Optimal Maintenance Probabilities and Preventive Replacement Maintenance Policy for Photocopy Machines

2021 ◽  
Author(s):  
Nse Udoh ◽  
Akaninyene Udom ◽  
Fredrick Ohaegbunem
Keyword(s):  
Minimum Cost ◽  
Maintenance Cost ◽  
Logistic Distribution ◽  
Maintenance Policy ◽  
Preventive Replacement ◽  
Maintenance Time ◽  
Replacement Model ◽  
Cumulative Function ◽  
Optimal Maintenance ◽  
Preventive Maintenance Policy

The need for suitable replacement policies are essential to minimize down time, maintenance cost and maximize the availability and reliability of equipment. On this premise, this work models the failure rate of Photocopy machines and obtain its optimal preventive maintenance policy that would prevent damage and its attendant losses to both users and end-product consumers. The failure distribution of the machine was shown to follow the Log-Logistic distribution with shape parameter, αˆ=1.723339368 and scale parameter, βˆ=763.9219635. Optimal probabilities of the distribution were obtained and utilized in both the cumulative failure function and cumulative hazard function-based replacement models to formulate a replacement maintenance policy for the machine. The failure cumulative function-based replacement model was found to be a better model which yields optimal replacement maintenance time of 166 hours at a minimum cost of 113 Naira for maintaining the machine per cycle time with 96% availability, 94% reliability and 0.07% chance of failure occurrence in the machine.

scholarly journals Optimization method of fatigue maintenance for cable-beam anchorage zone of suspension bridge

2020 ◽  
Vol 103 (3) ◽  
pp. 003685042095013
Author(s):  
Hongmei Tan ◽  
Yong Zeng ◽  
Qianping Zhang
Keyword(s):  
Failure Probability ◽  
Life Cycle Cost ◽  
Structural Reliability ◽  
Relative Proportion ◽  
Suspension Bridge ◽  
Optimization Method ◽  
Maintenance Cost ◽  
Time Interval ◽  
Maintenance Time ◽  
Optimal Maintenance

The cable-beam anchorage zone is the vital load-bearing component in suspension bridge. For maintenance of such structure, a method of probabilistic optimization was proposed by combining linear elastic fracture mechanics, structural reliability and life cycle cost analysis. In this method, the optimal maintenance time is obtained by determining the relative proportion between the costs under the condition that the structural reliability is higher than the minimum allowable reliability. While, the minimum total maintenance cost is obtained by determining the maintenance interval. Then, an example is presented to verify this method, with the following conclusions: the reliability index is inversely proportional to the failure probability, the change of maintenance cost and failure cost affects the optimal maintenance time, the optimal maintenance time will be ahead of time when consider the risk cost. And finally, when the maintenance time interval is determined, the optimal maintenance cost is affected by the maintenance probability and the failure probability.

Multi-component maintenance grouping optimization based on stochastic dependency

2020 ◽  
pp. 1748006X2094751
Author(s):  
Vimal Vijayan ◽  
Sanjay K Chaturvedi
Keyword(s):  
Diesel Engine ◽  
Cost Optimization ◽  
Maintenance Cost ◽  
Substantial Cost ◽  
Maintenance Time ◽  
Optimal Maintenance ◽  
Air Intake ◽  
Maintenance Activities ◽  
Preparatory Work

Maintenance activities often require an identical preparatory work. Therefore, a joint execution of such maintenance activities may save a substantial cost. In this work, we consider the problem of optimizing the total maintenance cost of a multi-component repairable system by grouping of components and carrying out maintenance activities on group(s) of components of a complex system. More specifically, we propose a maintenance grouping cost optimization model based on the stochastic dependency as well as economic dependency among components in a system. The stochastic dependency modeling is done using Bayesian network by considering the failure probability of components as a measure of failure interactions among components. Penalty functions are formulated due to the shift of individual optimal maintenance time of components to find the optimum joint maintenance interval and associated cost benefits. Finally, a case study on a diesel engine of a diesel power plant involving 10 components (components of diesel engine, air intake system, and turbocharger) is presented to illustrate the proposed approach.

scholarly journals The Proposed Maintenance Task for Plastic Injection Machine Using Reliability and Risk Centered Maintenance (RRCM) method in Manufacturing Industry

2019 ◽  
Vol 10 (2) ◽  
Author(s):  
Liza Nafiah Maulidina ◽  
Fransiskus Tatas Dwi Atmaji ◽  
Judi Alhilman
Keyword(s):  
Manufacturing Industry ◽  
Maintenance Cost ◽  
Time Interval ◽  
Maintenance Policy ◽  
Risk Matrix ◽  
Maintenance Time ◽  
Optimal Maintenance ◽  
Critical Components ◽  
The Cost ◽  
Plastic Injection

The objective of this research was to determine the optimal maintenance time interval for the selected critical components and the total cost of maintenance of a plastic injection machine. In determining the critical components, a risk matrix was used, and three components were selected, namely, hydraulic hose, barrel, and motor. Using the Reliability and Risk Centered Maintenance (RRCM) method, the researchers got a proposed maintenance policy and the total maintenance cost. Based on the result, it shows that there are seven proposed maintenance tasks with three scheduled oncondition tasks and four scheduled restoration tasks with an average maintenance interval of two months. The total maintenance cost proposed is IDR91.595.318. The cost is smaller compared to the actual maintenance costs of the company.

Availability analysis and maintenance optimization for multiple failure mode systems considering imperfect repair

2021 ◽  
pp. 1748006X2110127
Author(s):  
Qingan Qiu ◽  
Baoliang Liu ◽  
Cong Lin ◽  
Jingjing Wang
Keyword(s):  
Failure Modes ◽  
Maintenance Cost ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Availability Analysis ◽  
Long Run ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Periodic Inspections

This paper studies the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The repair time distribution and maintenance cost are both dependent on the failure modes. We investigate the instantaneous availability and the steady state availability of the system maintained through several imperfect repairs before a replacement is allowed. Analytical expressions for system availability under continuous and periodic inspections are derived respectively. The availability models are then utilized to obtain the optimal inspection and imperfect maintenance policy that minimizes the average long-run cost rate. A numerical example for Remote Power Feeding System is presented to demonstrate the application of the developed approach.

scholarly journals Dynamic Evolution Model of a Collaborative Innovation Network from the Resource Perspective and an Application Considering Different Government Behaviors

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 138 ◽  
Author(s):  
Wu ◽  
Shao ◽  
Feng
Keyword(s):  
Network Evolution ◽  
Evolution Model ◽  
Dynamic Evolution ◽  
Innovation Network ◽  
Transfer Policy ◽  
Collaborative Innovation ◽  
Innovation Output ◽  
The Government ◽  
Small Change ◽  
Innovative Behaviors

The evolution of a collaborative innovation network depends on the interrelationships among the innovation subjects. Every single small change affects the network topology, which leads to different evolution results. A logical relationship exists between network evolution and innovative behaviors. An accurate understanding of the characteristics of the network structure can help the innovative subjects to adopt appropriate innovative behaviors. This paper summarizes the three characteristics of collaborative innovation networks, knowledge transfer, policy environment, and periodic cooperation, and it establishes a dynamic evolution model for a resource-priority connection mechanism based on innovation resource theory. The network subjects are not randomly testing all of the potential partners, but have a strong tendency to, which is, innovation resource. The evolution process of a collaborative innovation network is simulated with three different government behaviors as experimental objects. The evolution results show that the government should adopt the policy of supporting the enterprises that recently entered the network, which can maintain the innovation vitality of the network and benefit the innovation output. The results of this study also provide a reference for decision-making by the government and enterprises.

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.

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