Decision support tools for preventive maintenance intervals and replacement decisions of engineering assets

Prognostic models for maintenance decisions have inherent limitations due to quality quantity of historical data, assumptions made, and time required in validating models. In this paper, Preventive Maintenance (PM) Intervals, Failure events, cost and maintenance records from Computerized Maintenance Management System (CMMS) are analyzed for reducing downtimes and Operating Expenditure (OPEX). The proposed methodologies for maintenance intervals and replacements with acceptable level of confidence are articulated to asset maintenance of a City Council of Australian Local Government organisation as a case of improved decision making under limited information.IEEE International Conference on Industrial Engineering and Engineering Managemen

Development and implementation of preventive-maintenance practices in Nigerian industries.

A methodology for the development of PM using the modern approaches of FMEA, root-cause analysis, and fault-tree analysis is presented. Applying PM leads to a cost reduction in maintenance and less overall energy expenditure. Implementation of PM is preferable to the present reactive maintenance procedures (still prevalent in Nigeria

A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency

In this paper, we address the problem of asset performance monitoring, with the intention of both detecting any potential reliability problem and predicting any loss of energy consumption e ciency. This is an important concern for many industries and utilities with very intensive capitalization in very long-lasting assets. To overcome this problem, in this paper we propose an approach to combine an Artificial Neural Network (ANN) with Data Mining (DM) tools, specifically with Association Rule (AR) Mining. The combination of these two techniques can now be done using software which can handle large volumes of data (big data), but the process still needs to ensure that the required amount of data will be available during the assets’ life cycle and that its quality is acceptable. The combination of these two techniques in the proposed sequence di ers from previous works found in the literature, giving researchers new options to face the problem. Practical implementation of the proposed approach may lead to novel predictive maintenance models (emerging predictive analytics) that may detect with unprecedented precision any asset’s lack of performance and help manage assets’ O&M accordingly. The approach is illustrated using specific examples where asset performance monitoring is rather complex under normal operational conditions.Ministerio de Economía y Competitividad DPI2015-70842-

After-sales services optimisation through dynamic opportunistic maintenance: a wind energy case study

After-sales maintenance services can be a very profitable source of incomes for original equipment manufacturers (OEM) due to the increasing interest of assets’ users on performance-based contracts. However, when it concerns the product value-adding process, OEM have traditionally been more focused on improving their production processes, rather than on complementing their products by offering after-sales services; consequently leading to difficulties in offering them efficiently. Furthermore, both due to the high uncertainty of the assets’ behaviour and the inherent challenges of managing the maintenance process (e.g. maintenance strategy to be followed or resources to be deployed), it is complex to make business out of the provision of after-sales services. With the aim of helping the business and maintenance decision makers at this point, this paper proposes a framework for optimising the incomes of after-sales maintenance services through: 1) implementing advanced multi-objective opportunistic maintenance strategies that sistematically consider the assets’ operational context in order to perform preventive maintenance during most favourable conditions, 2) considering the specific OEMs’ and users’ needs, and 3) assessing both internal and external uncertainties that might condition the after-sales services’ success. The developed case study for the wind energy sector demonstrates the suitability of the presented framework for optimising the after-sales services.EU Framework Programme Horizon 2020, MSCA-RISE-2014: Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE) (grant agreement number 645733- Sustain-Owner-H2020-MSCA-RISE-2014) and the EmaitekPlus 2016-2017 Program of the Basque Government

Using Proactive Maintenance Strategy for Sustainable Electric Power Production in Nigeria

An unpleasant turn of events would compel and prevail upon power plants owners and operators looking for alternative for keeping maintenance activities up and awake. Thus, causing a break away from outdated traditional system originally practiced in maintenance organizations, which affects operations in terms of costs and energy required for sustainable activity in the power production industry; via Generation, Transmission and Distribution. However, the only inevitably obtainable option as per organizational success in the power industry is through a substituent for a failure based system with success based strategy that is concerned with optimization of complex processes, systems or organization by developing, improving and implementing integrated systems of people, money, knowledge, information and equipment, central to manufacturing and production operations. A platform intended to deliver on plant (a) availability (b) reliability and (c) sustainability, which lead to reduced maintenance costs and increased profitability. Keywords: maintenance management; strategy implementation, power sector, performance optimization DOI: 10.7176/IEL/11-3-03 Publication date:October 31st 202

RELIABILITY CENTERED MAINTENANCE (RCM) FOR ASSET MANAGEMENT IN ELECTRIC POWER DISTRIBUTION SYSTEM

The purpose of Maintenance is to extend equipment life time or at least the mean time to the next failure. Asset Maintenance, which is part of asset management, incurs expenditure but could result in very costly consequences if not performed or performed too little. It may not even be economical to perform it too frequently. The decision therefore, to eliminate or minimize the risk of equipment failure must not be based on trial and error as it was done in the past. In this thesis, an enhanced Reliability-Centered Maintenance (RCM) methodology that is based on a quantitative relationship between preventive maintenance (PM) performed at system component level and the overall system reliability was applied to identify the distribution components that are critical to system reliability. Maintenance model relating probability of failure to maintenance activity was developed for maintainable distribution components. The Markov maintenance Model developed was then used to predict the remaining life of transformer insulation for a selected distribution system. This Model incorporates various levels of insulation deterioration and minor maintenance state. If current state of insulation ageing is assumed from diagnostic testing and inspection, the Model is capable of computing the average time before insulation failure occurs. The results obtained from both Model simulation and the computer program of the mathematical formulation of the expected remaining life verified the mathematical analysis of the developed model in this thesis. The conclusion from this study shows that it is beneficial to base asset management decisions on a model that is verified with processed, analysed and tested outage data such as the model developed in this thesis

Multi-objective model for optimizing railway infrastructure asset renewal

Trabalho inspirado num problema real da empresa Infraestruturas de Portugal, EP.A multi-objective model for managing railway infrastructure asset renewal is presented. The model aims to optimize three objectives, while respecting operational constraints: levelling investment throughout multiple years, minimizing total cost and minimizing work start postponements. Its output is an optimized intervention schedule. The model is based on a case study from a Portuguese infrastructure management company, which specified the objectives and constraints, and reflects management practice on railway infrastructure. The results show that investment levelling greatly influences the other objectives and that total cost fluctuations may range from insignificant to important, depending on the condition of the infrastructure. The results structure is argued to be general and suggests a practical methodology for analysing trade-offs and selecting a solution for implementation.info:eu-repo/semantics/publishedVersio

Strategies for maintenance management of railway track assets

M.Ing. (Engineering Management)Abstract: Population growth and environmental issues are revitalizing the railway sector in a tremendous way. An increase in frequency of passenger traffic and rising loads of freight trains has an impact on dynamic railway track properties and components thereof. The challenge from the railway fraternity is to rise to the challenge by ensuring a safe, reliable and affordable mode of transport. The purpose of this research is to investigate the capacity needed to meet demand by maintaining the track components of the railway infrastructure cost effectively. The railway track is the most critical in terms of safety, influence on maintenance costs, availability and reliability of the train service. Profillidis (2012) highlights the fact that track maintenance expenses represent a significant percentage of total railway infrastructure expenses. In literature, different maintenance strategies, approaches and concepts are discussed in light with arguments raised by different scholars and researchers. The main research methodology utilised was the case study on maintenance strategies from different countries where data was mostly available. The reason for the chosen method was to standardise the research method across different countries as this made it easy to obtain the findings and arrive at recommendations of the research. The broader findings from different maintenance strategies were that the track maintenance approach still has to evolve from working in silos to working in a system that acknowledges that decisions taken from other departments can affect the quality of maintenance in future. The deterioration of the track system is mostly affected by the initial quality of the railway track after commissioning due to workmanship and track design, maintenance approach, type of rolling stock tonnages, speed of rolling stock, and environmental related issues. Design phase of the track acknowledges the systems thinking approach for quality and structural integrity. However, more can still be done to adopt approaches that foster inter-departmental coordination in the maintenance phase of the railway track asset lifecycle. Transnet faces a challenge of fulfilling its obligation by providing quality and cost effective maintenance to increase the reliability, affordability, availability and safety of its infrastructure with the ever-increasing freight volumes. The traditional approach of maintaining railway track assets does not bring in required outcomes that ensure high quality and cost effective maintenance as required by high intensity asset utilisation. Data collected from the..

Developing Hybrid Machine Learning Models to Assign Health Score to Railcar Fleets for Optimal Decision Making

A large amount of data is generated during the operation of a railcar fleet, which can easily lead to dimensional disaster and reduce the resiliency of the railcar network. To solve these issues and offer predictive maintenance, this research introduces a hybrid fault diagnosis expert system method that combines density-based spatial clustering of applications with noise (DBSCAN) and principal component analysis (PCA). Firstly, the DBSCAN method is used to cluster categorical data that are similar to one another within the same group. Secondly, PCA algorithm is applied to reduce the dimensionality of the data and eliminate redundancy in order to improve the accuracy of fault diagnosis. Finally, we explain the engineered features and evaluate the selected models by using the Gain Chart and Area Under Curve (AUC) metrics. We use the hybrid expert system model to enhance maintenance planning decisions by assigning a health score to the railcar system of the North American Railcar Owner (NARO). According to the experimental results, our expert model can detect 96.4% of failures within 50% of the sample. This suggests that our method is effective at diagnosing failures in railcars fleet.Comment: 21 pages, 7 figures, 3 table