Criticality analysis for preventive maintenance optimization purposes in gas network infrastructures

2018 ◽  
Vol 232 (4) ◽  
pp. 464-472
Author(s):  
Javier Serra Parajes ◽  
Adolfo Crespo Márquez ◽  
Antonio Sola Rosique
Keyword(s):  
Preventive Maintenance ◽  
Maintenance Optimization ◽  
Maintenance Strategy ◽  
Maintenance Strategies ◽  
Gas Network ◽  
Operation And Maintenance ◽  
Relative Value ◽  
Criticality Analysis ◽  
Corporate Level

Identification and quantification of cost and value of industrial assets is a field in which much terminology has been developed. When we try to analyze the importance of an asset for our business, the discussion about its costs should not be separated from the value provided by the asset. Most of the time, managers use the term “cost” because it seems to be more objective. The concept of value is more subjective and more difficult to define. However, we shall henceforth use definitions as amortization, inflation, or replacement value in order to simplify the concept of “value” to improve our decisions. The economic retribution of the facilities is based on a legal normative for regulated companies, so the concept of “cost” may turn out to be quite useless. Therefore, it is important to use a methodology that allows us to estimate the value of our assets. We have developed a criticality analysis of our infrastructure in order to assess the relative value of these items for the company. The target is to optimize the operation and maintenance strategies at a corporate level. This must have a relevant impact on the OPEX of our company, and there may also be an impact on future CAPEX. This article is a case study of the methodology and presents clear examples of how operation and maintenance strategy is transformed according to criticality assessments.

Preventive maintenance optimization for repairable products considering two-dimensional warranty and customer satisfaction

2018 ◽  
Vol 233 (4) ◽  
pp. 553-566
Author(s):  
Yukun Wang ◽  
Yiliu Liu ◽  
Aibo Zhang
Keyword(s):  
Customer Satisfaction ◽  
Preventive Maintenance ◽  
Product Performance ◽  
Maintenance Optimization ◽  
Two Dimensional ◽  
Maintenance Strategy ◽  
Minimal Repair ◽  
Proposed Model ◽  
Useful Life ◽  
Practical Implications

Customer satisfaction with a purchased product is closely related to the product performance within the warranty region and even the performance during the remainder of its useful life. Every satisfied customer may boost the future sales of the same product with positive evaluations and recommendations to others, and thus will create more profits for the manufacturer. During the useful life of the product, the expected cost to the manufacturer normally depends on the warranty policy, product reliability and specific servicing strategies implemented. In this article, considering the effect of customer satisfaction on the manufacturer’s incurred cost, we investigate a periodic and imperfect preventive maintenance strategy for repairable products sold with a two-dimensional warranty policy. The customer satisfaction is measured with the probability of the customer making a repeat purchase from the same manufacturer. In the proposed model, the number of preventive maintenance actions and corresponding maintenance level are jointly derived with the objective of minimizing the expected total cost per product to the manufacturer. The performance of the proposed preventive maintenance strategy is compared with that of minimal repair corrective maintenance strategy in a numerical example, so as to illustrate its applicability. In addition, some practical implications from a detailed sensitivity analysis are elaborated.

scholarly journals Maintenance Optimization of Offshore Wind Turbines Based on an Opportunistic Maintenance Strategy

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2650 ◽  
Author(s):  
Lubing Xie ◽  
Xiaoming Rui ◽  
Shuai Li ◽  
Xin Hu
Keyword(s):  
Wind Turbines ◽  
Preventive Maintenance ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Maintenance Optimization ◽  
Maintenance Strategy ◽  
Distribution Method ◽  
Opportunistic Maintenance ◽  
Maintenance Costs ◽  
Offshore Wind Turbines

Owing to the late development of offshore wind power in China, operational data and maintenance experience are relatively scarce. Due to the harsh environmental conditions, a reliability analysis based on limited sample fault data has been regarded as an effective way to investigate maintenance optimization for offshore wind farms. The chief aim of the present work is to develop an effective strategy to reduce the maintenance costs of offshore wind turbines in consideration of their accessibility. The three-parameter Weibull distribution method was applied to failure rate estimation based on limited data. Moreover, considering the impacts of weather conditions on the marine maintenance activities, the Markov method and dynamic time window were used to depict the weather conditions. The opportunistic maintenance strategy was introduced to cut down on the maintenance costs through optimization of the preventive maintenance age and opportunistic maintenance age. The simulation analysis we have performed showed that the maintenance costs of the opportunistic maintenance strategy were 10% lower than those of the preventive maintenance strategy, verifying the effectiveness of the proposed maintenance strategy.

Preventive Maintenance Optimization of Availability for NC Machine

2014 ◽  
Vol 988 ◽  
pp. 653-658
Author(s):  
Gang Lei ◽  
Chao Deng ◽  
Bo Sheng
Keyword(s):  
Probability Density Function ◽  
Machine Tool ◽  
Preventive Maintenance ◽  
Maintenance Optimization ◽  
Maintenance Strategy ◽  
Maintenance Period ◽  
Nc Machine Tool ◽  
Nc Machine ◽  
Function Module ◽  
Fault Information

This paper addresses the problem of preventive maintenance optimization for NC machine tool. Firstly, the NC machine tool is divided into four subsystems according to the function module. The failure probability density function of each subsystem is estimated with the fault information records. Then, the optimal preventive maintenance period is estimated for each subsystem considering the availability. The optimal periods of all the subsystems are used to derive the preventive maintenance strategy of the whole machine. Finally, a numerical case is presented and the result shows the performance of the proposed approach.Keywords: NC machine tool, subsystem, availability, preventive maintenance

Maintenance and Availability Study of a Manufacturing Company: Case Study of a Flour Mill Company

2013 ◽  
Vol 824 ◽  
pp. 584-594
Author(s):  
Ralph O. Edokpia ◽  
P.C. Oparah
Keyword(s):  
Preventive Maintenance ◽  
Maintenance Strategy ◽  
Production Ratio ◽  
Optimal Replacement ◽  
Equipment Availability ◽  
Flour Mill ◽  
Manufacturing Company ◽  
Maintenance Activities

The focus of this study is to carry out a maintenance and availability study of a manufacturing company using a flour mill company as a case study. To properly evaluate the maintenance activities of the company, some sets of performance ratios were used. The performance ratios used in the assessment include; equipment availability, maintenance to production ratio, equipment shutdown intensity, overall equipment effectiveness. The result obtained showed that equipment availability was 93.7%, 93.38%, 93.18%, 92.42%, 91.28%, for year 2006, 2007, 2008, 2009 and 2010 respectively. Maintenance to production ratio was 0.03, 0.04, 0.04, 0.05, and 0.06 for year 2006, 2007, 2008, 2009 and 2010 respectively. Intensity of shutdown ranged from 0.07, 0.7, 0.07, 0.08, and 0.10 for year 2006, 2007, 2008, 2009 and 2010 respectively. Overall equipment effectiveness was 86.30%, 85.10%, 84.92%, 83.33%, 81.40% for year 2006, 2007, 2008, 2009 and 2010 respectively. Comparing the results obtained, revealed the following; the availability of the mill declined with age, from 93.7% in 2006 to 91.28% in 2010. The proportion of time spent on maintenance as against production was on the increase from 0.03 in 2006 to 0.06 in 2010. The intensity of shutdown of the mill increased by the years from 0.07 in 2006 to 0.10 in 2010. The overall equipment effectiveness of the mill was unsatisfactory from the year when optimal replacement was supposed to have been done (year 2009), according to existing standards. OEE was 83.33% in 2009 and 81.40% in 2010. Further study also revealed that an average of 244 million was lost annually due to down time. For optimal availability, the most effective maintenance strategy needs to be adopted and preventive maintenance is recommended.

An opportunistic maintenance strategy for offshore wind turbine based on accessibility evaluation

2019 ◽  
Vol 44 (5) ◽  
pp. 455-468
Author(s):  
Xie Lubing ◽  
Rui Xiaoming ◽  
Li Shuai ◽  
Hu Xin
Keyword(s):  
Wind Turbine ◽  
Preventive Maintenance ◽  
Wind Farm ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Maintenance Strategy ◽  
Offshore Wind Farm ◽  
Opportunistic Maintenance ◽  
Operation And Maintenance

The maintenance costs of offshore wind turbines operated under the irregular, non-stationary conditions limit the development of offshore wind power industry. Unlike onshore wind farms, the weather conditions (wind and waves) have greater impacts on the operation and maintenance of offshore wind farm. Accessibility is a key factor related to the operation and maintenance of offshore wind turbine. Considering the impact of weather conditions on the maintenance activities, the Markov method and dynamic time window are applied to represent the weather conditions, and an index used to evaluate the maintenance accessibility is then proposed. As the wind turbine is a multi-component complex system, this article uses the opportunistic maintenance strategy to optimize the preventive maintenance age and opportunistic maintenance age for the main components of the wind turbine. Taking the minimum expectation cost as objective function, this strategy integrates the maintenance work of the key components. Finally, an offshore wind farm is taken for simulation case study of this strategy; the results showed that the maintenance cost of opportunistic maintenance strategy is 10% lower than that of the preventive maintenance strategy, verifying the effectiveness of the opportunistic maintenance.

Maintenance strategy selection using AHP and ANP algorithms: a case study

2012 ◽  
Vol 18 (1) ◽  
pp. 16-29 ◽  
Author(s):  
Selim Zaim ◽  
Ali Turkyılmaz ◽  
Mehmet F. Acar ◽  
Umar Al‐Turki ◽  
Omer F. Demirel
Keyword(s):  
Decision Making ◽  
General Purpose ◽  
Strategy Selection ◽  
Maintenance Strategy ◽  
Maintenance Strategies ◽  
Content Type ◽  
Network Process ◽  
Practical Implications ◽  
Selection Of

PurposeThe purpose of this paper is to demonstrate the use of two general purpose decision‐making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements.Design/methodology/approachThe Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey.FindingsThe two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise.Practical implicationsThe techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step‐by‐step approach for easier adaptation by practitioners in all types of organizations.Originality/valueThe value of the paper is in applying AHP and ANP decision‐making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.

Research on Optimization of Preventive Maintenance Interval Decision for Vessel Equipment

2013 ◽  
Vol 850-851 ◽  
pp. 981-985
Author(s):  
Bo Yang ◽  
Ya Chen
Keyword(s):  
Preventive Maintenance ◽  
Engine Fuel ◽  
Limited Time ◽  
Multi Objective Optimization ◽  
Maintenance Strategies ◽  
Decision Making Problem ◽  
Unlimited Time ◽  
Multi Attribute Decision Making ◽  
Single Objective

Optimization of preventive maintenance interval decision for vessel equipment is a multi-attribute decision making problem. But the current studies on the preventive maintenance strategies are mostly with single-objective and based on the assumptions that equipments operating for unlimited time. In this paper, a multi-objective optimization model in limited time is established basing on the existing studies. And the case study of a certain type diesel engine fuel system is used to illustrate the methodology.

Maintenance strategy selection for optimum efficiency – application of AHP constant sum

Facilities ◽  
2019 ◽  
Vol 38 (5/6) ◽  
pp. 421-444
Author(s):  
Hector Martin ◽  
Fey Mohammed ◽  
Kevin Lal ◽  
Shannon Ramoutar
Keyword(s):  
Structured Interview ◽  
Maintenance Strategy ◽  
Analytic Hierarchy ◽  
Maintenance Strategies ◽  
Content Type ◽  
Factors Affecting ◽  
Desirable Outcome ◽  
Business Efficiency ◽  
Optimum Solution

Purpose There are limited studies addressing how choosing a maintenance strategy can contribute towards maximising outputs from given inputs, thereby minimising costs and improving a company’s competitiveness. The analytic hierarchy constant sum method (AHCSM) is used to access the appropriateness of maintenance strategies for improving the overall efficiency of a structural steel fabrication construction company. Design/methodology/approach A semi-structured interview was formulated with the stakeholders of the quality department to understand the company’s maintenance portfolio and its current functional capability. The information from this case study was then dissected to represent the factors that the company deemed appropriate for evaluating their maintenance strategy. The AHCSM approach provided a framework, which ranked the importance of factors that are sensitive to the construction industry and rank the suitability of maintenance strategies. Findings Factors affecting the selection of maintenance strategies to improve business efficiency are productivity, quality, reliability, cost, safety and work environment, morale, inventory and flexibility. Total productive maintenance strategy produces the most desirable outcome; however, the predictive or condition-based maintenance strategy provides an optimum solution for the case study company while considering the equipment usage, frequency of production and the current economic climate. Originality/value The approach presented allows practitioners to consider ways to increase the level of production and improve the efficiency of construction businesses without a high increase in investment. The findings can inform gaps in existing maintenance approaches in achieving business objectives.

A Comparison of Multi-Criteria Decision Making Approaches for Maintenance Strategy Selection (A Case Study)

2016 ◽  
Vol 7 (3) ◽  
pp. 51-69 ◽  
Author(s):  
Malek Tajadod ◽  
Mohammadali Abedini ◽  
Ali Rategari ◽  
Mohammadsadegh Mobin
Keyword(s):  
Decision Making ◽  
Fuzzy Ahp ◽  
Multiple Criteria Decision Making ◽  
Strategic Decision ◽  
Strategy Selection ◽  
Maintenance Strategy ◽  
Manufacturing Companies ◽  
Maintenance Strategies ◽  
Decision Elements

The growth of world-class manufacturing companies and global competition caused significant changes in the manufacturing companies operations. These changes have affected maintenance and made its role even more crucial to stay ahead of the competition. Maintenance strategy selection is one of the strategic decision-making issues that manufacturing companies in the current competitive world are facing. In this paper, a comparison between different Multiple Criteria Decision Making (MCDM) approaches is conducted in a dairy manufacturing factory to rank the maintenance strategies. The aim is to suggest an appropriate approach for the best selection of the maintenance strategy. The decision-making elements including evaluation criteria/sub-criteria and problem alternatives, i.e., maintenance strategies are determined and a group of experts from the case-study factory are asked to make their pair-wise comparisons. The pair-wise comparison matrix is constructed by using the crisp and triangular fuzzy numbers, while the aggregation of individual priorities (AIP) approach is utilized to aggregate the decision-makers' judgments. The priority vectors of decision elements are calculated by Mikhailov's fuzzy preference programming (FPP) methods and the final weights of the decision elements are found. Results show that when the effectiveness of one element on the other elements is higher, it will have greater weights; and therefore, the results from the analytic network process (ANP) method is completely different from those of the analytic hierarchy process (AHP). The reason for the differences between the AHP and Fuzzy AHP (FAHP) with the ANP and Fuzzy ANP (FANP) is that both AHP and FAHP evaluate the criteria only based on the level of importance and do not consider the interdependencies and interactions among the evaluation elements. In this research, a predictive maintenance is selected as the most appropriate strategy in the case company and the preventive strategies outperformed the corrective strategies. The results of this research are consistent with the results of previous studies found in the literature.

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