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

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

Decision Support Model in the Strategic Management of the Portuguese Air Force Alpha Jet Fleet

Based on exploration criteria, the Phase-Out of an asset comprises the operation end of that asset. However, given the high cost of some assets, decision makers are faced by the dilemma of developing policies that allow them to extend the exploration period or find alternative scenarios for their use. With the aim of creating value, in terms of maintenance planning, this paper proposes a decision support model based on a multi-criteria approach, with the objective of selecting the best alternative. The proposed model analyzes the exploration extension scenario of an asset, identifying the actions necessary to guarantee its operational availability in relation to other alternative scenarios. The model developed was applied to the Alpha Jet fleet of the Portuguese Air Force, which is in Phase-Out period and will cease to operate in January 2018, and there is no definite decision for its use

Maintenance policy selection for ships : finding the most important criteria and considerations

Maintenance of technical capital assets is gaining increasing attention, as maintenance is an important contributor to reach the intended life-time of these expensive assets. This paper focusses on maintenance policy selection (MPS) for ships using the Analytic Hierarchy Process. It builds on earlier research where we have investigated MPS specifically for naval ships. Here, we aim to generalize our findings on naval ships towards ships in general, and to elicit the most important criteria for ship MPS. We propose an improved hierarchy of criteria that we use during six workshops at six different companies to investigate MPS. We conclude that it is possible to obtain meaningful outcomes using a single hierarchy of criteria at multiple companies considering various ship types. The workshops reveal that crew safety is the most important criterion when selecting a aintenance policy, followed by reliability and availability—surprisingly, costs minimization is only moderately important. Furthermore, the workshops reveal that softer criteria, such as experience with maintenance and planability, must be included in the MPS process. Finally, we see that, for ship MPS, failure-based maintenance is never preferred, and that there is no clear preference for either time/use-based maintenance or condition-based maintenance

Investigating ship system performance degradation and failure criticality using FMECA and artificial neural networks

The goal of all maintenance methods is to eliminate failures or reduce their occurrence. Ex-tended downtime on key ships systems such as power generation plants can lead to undesirable consequences beyond economic and operational losses, especially considering naval vessels. One solution to overcome this challenge is through a system-specific analysis that identifies the most critical component and possible causes of delays be it technical or logistics. In this regard, this paper presents a methodology using FMECA approach that adopts the risk priority number differently to identify Mission Critical Components. This was supported with ANN classification using unsupervised learning to identify patterns in the data that signifies the onset of performance degradation and potential failures onboard an OPV. The study has identified some critical components and failure patterns that contribute to extended downtime based on survey and machinery maintenance reports. Recommendations were provided on preventing/mitigating the failures and how to prioritize existing ship systems maintenance