Multi-criteria decision making support tools for maintenance of marine machinery systems

PhD ThesisFor ship systems to remain reliable and safe they must be effectively maintained through a sound maintenance management system. The three major elements of maintenance management systems are; risk assessment, maintenance strategy selection and maintenance task interval determination. The implementation of these elements will generally determine the level of ship system safety and reliability. Reliability Centred Maintenance (RCM) is one method that can be used to optimise maintenance management systems. However the tools used within the framework of the RCM methodology have limitations which may compromise the efficiency of RCM in achieving the desired results. This research presents the development of tools to support the RCM methodology and improve its effectiveness in marine maintenance system applications. Each of the three elements of the maintenance management system has been considered in turn. With regard to risk assessment, two Multi-Criteria Decision Making techniques (MCDM); Vlsekriterijumska Optimizacija Ikompromisno Resenje, meaning: Multi-criteria Optimization and Compromise Solution (VIKOR) and Compromise Programming (CP) have been integrated into Failure Mode and Effects Analysis (FMEA) along with a novel averaging technique which allows the use of incomplete or imprecise failure data. Three hybrid MCDM techniques have then been compared for maintenance strategy selection; an integrated Delphi-Analytical Hierarchy Process (AHP) methodology, an integrated Delphi-AHP-PROMETHEE (Preference Ranking Organisation METHod for Enrichment Evaluation) methodology and an integrated Delphi-AHP-TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methodology. Maintenance task interval determination has been implemented using a MCDM framework integrating a delay time model to determine the optimum inspection interval and using the age replacement model for the scheduled replacement tasks. A case study based on a marine Diesel engine has been developed with input from experts in the field to demonstrate the effectiveness of the proposed methodologies.Tertiary Education Trust Fund (TETFUND), a scholarship body of the Federal Republic of Nigeria for providing the fund for this research. My gratitude also goes to Federal University of Petroleum Resource, Effurun, Nigeria for giving me the opportunity to be a beneficiary of the scholarship

Review on ship onboard machinery maintenance strategy selection using multi-criteria optimization

Abstract: Marine shipping is an important aspect of the transportation system in Canada. It is estimated that 70-80% of items that we are surrounded by and use daily are brought by ships. Canadian businesses need to sell to the world and ships carries their products abroad. For people that live in Canada’s island or northern communities, marine shipping is often the only source they have for essentials. It is estimated that marine shipping directly contributes about $3 billion annually to Canada’s GDP through employment and other impacts. In a marine ship system, safety and reliability are very important considerations. The various system elements must be properly maintained and organizations are now looking to maintenance optimization to achieve optimum safety, machinery reliability and reduced costs. Modern day maintenance optimization is a decision-making problem which need to satisfy multiple and conflicting criteria. Multi-Criteria Optimization (MCO) techniques have been used in maintenance optimization. Two main classes of maintenance MCO problems have been identified as strategy selection and interval optimization. In marine ships, maintenance strategy selection is a complex decision-making problem that has become ever more challenging to address and is accompanied by diverse constraints and economic considerations. Each maintenance strategy has its own characteristics, importance and drawbacks. The use of inappropriate maintenance strategy affects the safety of a ship, crew, machinery reliability, maintenance cost etc. MCO techniques have been used in selecting optimal maintenance strategy for ship onboard machinery.Communication présentée lors du congrès international tenu conjointement par Canadian Society for Mechanical Engineering (CSME) et Computational Fluid Dynamics Society of Canada (CFD Canada), à l’Université de Sherbrooke (Québec), du 28 au 31 mai 2023

Elements of maintenance system and tools for implementation within framework of Reliability Centred Maintenance- A review

For plant systems to remain reliable and safe they must be effectively maintained through a sound maintenance management system. The three major elements of maintenance management systems are; risk assessment, maintenance strategy selection and maintenance task interval determination. The implementation of these elements will generally determine the level of plant system safety and reliability. Reliability Centred Maintenance (RCM) is one method that can be used to optimise maintenance management systems. This paper discusses the three major elements of a maintenance system, tools utilised within the framework of RCM for performing these tasks and some of the limitations of the various tools. Each of the three elements of the maintenance management system has been considered in turn. The information will equip maintenance practitioners with basic knowledge of tools for maintenance optimisation and stimulate researchers with respect to developing alternative tools for application to plant systems for improved safety and reliability. The research findings revealed that there is a need for researchers to develop alternative tools within the framework of RCM which are efficient in terms of processing and avoid the limitations of existing methodologies in order to have a safer and more reliable plant system.

Application of a multiple attribute group decision making (MAGDM) model for selecting appropriate maintenance strategy for marine and offshore machinery operations

The process of selecting appropriate maintenance strategy to enhance the operational efficiency of marine and offshore machinery under an uncertain environment is challenging due to the many criteria that need to be considered and modelled. In addition, the design of such complex machinery on-board a vessel consists of many subjective and imprecise parameters contained in different quantitative and qualitative forms. This paper proposes a strategic multi-attribute group decision-making (MAGDM) methodology for the concise and straightforward selection of an appropriate maintenance strategy. The decision support structure allows the use of multiple decision makers to incorporate and aggregate their subjective opinions transparently. In the analysis, a Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) was employed to rank the maintenance strategies with respect to costs and benefits for their subsequent implementation. The purpose of using MAGDM in this paper is to aggregate and synthesise opinions of experts, thus, guiding them in decision making when they are planning to implement a cost effective maintenance investment. © 2019 Elsevier Lt

Integration of Fuzzy PIPRECIA and Fuzzy MOORA Methods for Maintenance Strategy Selection

In today’s competitive environment, there is a pressure on companies for reducing costs and increasing the quality by providing on time delivery. Maintenance, plays an important role in reducing cost, improving quality, reducing failures, minimizing machine downtime, increasing productivity and as a result achieving objectives of company. The aim of this paper is to select best maintenance strategy for a manufacturing company by using an integrated fuzzy MCDM (Multi-Criteria Decision Making) approach. This approach is based on fuzzy PIPRECIA (Pivot Pairwise Relative Criteria Importance Assessment) and fuzzy MOORA (Multi Objective and Optimization on the Basis of Ratio Analysis) methods. The selection of maintenance strategy is a multi-criteria decision making (MCDM) problem. As this problem includes uncertainties and difficulty in evaluating alternatives and criteria with definite expressions, fuzzy MCDM approach is proposed for selecting the best maintenance strategy. As a result of the application of the proposed integrated method in the manufacturing company, the ranking of the maintenance strategies was obtained, and predictive maintenance strategy was determined as the most appropriate maintenance strategy for the company

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

Application of Waspas In Enhancing Reliability Centered Maintenance For Ship System Maintenance

The key for achieving safe and reliable ship system operation throughout a vessel’s life cycle is the continuous use of an effective maintenance methodology for the machinery systems. A typical maintenance methodology consists of three major elements which include; risk assessment, maintenance strategy selection and maintenance scheduling. The degree of ship system safety and reliability greatly depend on the successful execution of these elements. One approach for the implementation of these elements is Reliability Centred Maintenance (RCM). However, the various tools used within the RCM approach all have one limitation or another which reduces the effectiveness of the method. This paper presents the Weighted Aggregated Product Assessment (WASPAS), a Multi-Criteria Decision Making (MCDM) tool used to enhance the RCM method in order to improve its effectiveness in marine maintenance system applications. Although the typical maintenance methodology consists of three components, this paper focuses only on two of these, namely; risk assessment and maintenance strategy selection. With respect to risk assessment, WASPAS has been combined with Failure Mode and Effects Analysis (FMEA) along with Standard Deviation (SD).  The maintenance strategy selection task has also been executed using a combination of WASPAS and SD. For both components, WASPAS is applied in the ranking of alternatives whilst SD has been used in the weighting of decision criteria. To illustrate the effectiveness of the proposed enhanced RCM methodology, a case study of the central cooling system of a marine diesel engine is presented

Under-water noise pollution sources, mitigation measures in commercial vessels: the trade-off analysis in the case of study for trans mountain project, Port of Vancouver, Canada.

Shipping is the most efficient type of transportation and plays a significant role in global trade. However, it has some negative externalities and creates environmental pollution. With the growth of shipping, the potential for low-frequency noise increases along with its negative effects such as impacts on marine species and threat to sustainable shipping, e.g. its intensity has been doubling in the North Pacific Ocean every decade for the past 60 years and it is predicted to increase by 87–102% on average by 2030. In contrast to other environmental issues, the underwater noise is not visible, so to raise awareness and show its negative impacts, a scientific approach and data collection are required. While awareness of the society in respect of the other pollutions such as oil, dangerous goods, noxious liquids substances, sewage, and air has been raised and those issues are regulated properly, society has not been familiar with under-water noise pollution and it has not been regulated properly. As such, legal gaps exist this study is a holistic approach to UWN pollution. The main sources and the ways to mitigate UWN pollution and its effect on sustainable shipping will be reviewed. Meanwhile, with reference to the previous environmental issues and present information and data collection, the general trends for the future of UWN pollution will be suggested. Moreover, in the case study (the Trans Mountain Project (TMP)), mitigation measures to reduce the negative impacts of the growth of shipping in the Haro Strait will be suggested. Furthermore, by creating four scenarios and modelling, simulations, utilizing the MCDM (MADM) algorithms, and TOPSIS techniques the trade-off between the environmental (noise and Co2 emission) and economical (fuel cost) aspects of the project will be conducted to enhance the Decision Support System (DSS). This will help the decision makers to have a multi-dimensional thinking instead of the single dimensional thinking in addressing and tackling the negative externalities of the TMP in the area. Moreover, at the end of each scenario, a sensitivity analysis will be conducted to provide a clean environment for decision makers

FAILURE MODE AND EFFECTS ANALYSIS OF SHIP SYSTEMS USING AN INTEGRATED DEMPSTER SHAFER THEORY AND ELECTRE METHOD

Failure Mode and Effects Analysis (FMEA) is a risk analysis tool which is used to define, identify, and eliminate known and/or potential failures from a system. The task is generally performed by team of experts. Each of the team of experts can express diverse opinions in rating of failure modes of systems which may be in the form of precise data and imprecise distribution ratings. However the RPN of FMEA is incapable of using these various forms of information in the prioritisation of risk of failure modes. This is one of the main limitations of FMEA. Furthermore the technique is limited to the use of three decision criteria thereby excluding other important decision criteria such as production loss in prioritising risk. To address these problems a novel FMEA tool is proposed which combines Dempster Shafer Theory with the ELECTRE method to provide a more efficient failure mode prioritisation method. With this technique the Dempster Shafer Theory is used in aggregating different failure mode ratings from experts and the ELECTRE method is applied in the ranking of failure modes. The applicability of the proposed technique is demonstrated with a case study of a marine diesel engine. Results showed that the proposed method can be applied in addressing risk prioritisation problem more efficiently than the FMEA and its variant