Application of Waspas in Ehancing 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.

[1]  Silvia Carpitella,et al.  A combined multi-criteria approach to support FMECA analyses: A real-world case , 2018, Reliab. Eng. Syst. Saf..

[2]  Dragisa Stanujkic,et al.  An Approach to Personnel Selection in the Tourism Industry Based on the SWARA and the WASPAS Methods , 2017 .

[3]  Ikuobase Emovon,et al.  An integrated multicriteria decision making methodology using compromise solution methods for prioritising risk of marine machinery systems , 2015 .

[4]  Richard Kirkham,et al.  Performance Measurement of Marine Vessel Maintenance Operations; A Case Study of Kuwait Shipping Companies , 2010 .

[5]  Jin Wang,et al.  Modified failure mode and effects analysis using approximate reasoning , 2003, Reliab. Eng. Syst. Saf..

[6]  Joseph I. Achebo,et al.  Optimization of Gas Metal Arc Welding Process Parameters Using Standard Deviation (SDV) and Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) , 2015 .

[7]  Morteza Yazdani,et al.  Sensitivity Analysis in MADM Methods: Application of Material Selection , 2016 .

[8]  Metin Celik,et al.  Application of failure modes and effects analysis to main engine crankcase explosion failure on-board ship , 2013 .

[9]  Ikuobase Emovon,et al.  Ship System Maintenance Strategy Selection Based on DELPHI-AHP-TOPSIS Methodology , 2016 .

[10]  Marcello Braglia,et al.  The analytic hierarchy process applied to maintenance strategy selection , 2000, Reliab. Eng. Syst. Saf..

[11]  Liliane Pintelon,et al.  Maintenance concept development: A case study , 2004 .

[12]  Ikuobase Emovon,et al.  Multi-criteria decision making support tools for maintenance of marine machinery systems , 2016 .

[13]  Shankar Chakraborty,et al.  Applications of WASPAS Method in Manufacturing Decision Making , 2014, Informatica.

[14]  Rob J. I. Basten,et al.  Exploring maintenance policy selection using the Analytic Hierarchy Process; An application for naval ships , 2015, Reliab. Eng. Syst. Saf..

[15]  Chung-Hsing Yeh,et al.  Inter-company comparison using modified TOPSIS with objective weights , 2000, Comput. Oper. Res..

[16]  Anthony M. Smith,et al.  Reliability-Centered Maintenance , 1992 .

[17]  Anish Sachdeva,et al.  Maintenance criticality analysis using TOPSIS , 2009, 2009 IEEE International Conference on Industrial Engineering and Engineering Management.

[18]  Dong‐Shang Chang,et al.  Applying DEA to enhance assessment capability of FMEA , 2009 .

[19]  Francesco Zammori,et al.  ANP/RPN: a multi criteria evaluation of the Risk Priority Number , 2012, Qual. Reliab. Eng. Int..

[20]  Bijan Sarkar,et al.  THE MAINTENANCE STRATEGY SELECTION OF A GAS TURBINE POWER PLANT SYSTEM , 2011 .

[21]  Ying Luo,et al.  Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making , 2010, Math. Comput. Model..

[22]  Hu-Chen Liu,et al.  Failure mode and effects analysis using fuzzy evidential reasoning approach and grey theory , 2011, Expert Syst. Appl..

[23]  Iraklis Lazakis,et al.  Determination of the optimum ship maintenance strategy through multi attribute decision making , 2012 .

[24]  Joseph A. C. Delaney Sensitivity analysis , 2018, The African Continental Free Trade Area: Economic and Distributional Effects.

[25]  Gionata Carmignani,et al.  An integrated structural framework to cost-based FMECA: The priority-cost FMECA , 2009, Reliab. Eng. Syst. Saf..

[26]  Robert M. Conachey,et al.  Development of machinery survey requirements based on reliability-centered maintenance. Discussion , 2005 .

[27]  Shun-Peng Zhu,et al.  Risk evaluation in failure mode and effects analysis of aircraft turbine rotor blades using Dempster–Shafer evidence theory under uncertainty , 2011 .