An Integrated Fuzzy Analytical Hierarchical Process and Fuzzy Grey Relational Analytical Model with Vikor for Maintenance System Appraisal

Sunday Ayoola Oke

Abstract


The motivation for this research lies in the understanding that the evaluation of a maintenance department for a manufacturing organization strongly depends on a wide range of uncertainties and vague parameters. Consequently, utilising intuition may not be technically correct and downplays on the supposed results for the right management decisions on maintenance. The need for a new method to correct this anomaly is very much pressing to enhance the performance of maintenance systems. In this paper, the fusion of fuzzy analytical hierarchy process with fuzzy grey relational analysis as well as VIKOR is presented. A measuring instrument, questionnaire, for evaluating the performance of maintenance systems was developed and administered in four companies. Using the pair-wise comparisons of criteria relevant to systems reliability, profitability, lead-time, system safety, production cost and manufacturing goals, the crisp values for the major components were generated. Computation of the grey relational grade, best and moist values, utility regret measure and VIKOR index, and finally the ranking of the maintenance system were made. The approach is feasible in maintenance system evaluation. The unique and innovative approach that established a link between maintenance system’s goals and variables when dealing with maintenance system appraisal is the main novelty of the work. An additional novelty not reported earlier in literature is the consideration of human attributes and environments in an integrated manner. This study contributes a significant approach for correctly evaluating the technical aspects of the maintenance system.

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References


Ahren T. and Parida A. 2009. Maintenance performance indicators (MPI) for benchmarking the railway infrastructure. A case study, Benchmarking: An International Journal, 16(2), pp. 247-258.

Baluch N., Abdullah C.S.B. and Mohtar S.B. (2010). Maintenance management performance: An overview towards evaluating Malaysian palm oil mill. The Asian Journal of Technology Management, 3(1), pp. 1-4.

Chang D.Y. (1996). Application of extend analysis method on fuzzy AHP. European Journal of Operational Research, 96, pp. 343-350.

De Groote P. 1995. Maintenance performance analysis: A practical approach, Journal of Quality in Maintenance Engineering, 1(2), pp. 4-24.

Elangovan K., Selladurai V., Devadasan S.R., Goyal S.K., Muthu S., 2007. Quality and productivity improvement of executive decisions in maintenance engineering: An ESS-based approach, International Journal of Productivity and Quality Management, 2(1), pp. 112-139.

Girubha R.J. and Vinodh S. (2012). Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component. Materials and Design, 37, pp. 478-486.

Hasani H., Tabatabaei S.A. and Amiri G. (2012). Grey relational analysis to determine the optimum process parameters for open-end spinning yarns. Journal of Engineered Fibers and Fabrics, 7(2), pp. 81-86.

Khan M.R.R, Darrab I.A. 2010. Development of analytical relation between maintenance, quality and productivity, Journal of Quality in Maintenance Engineering, 16(4), pp. 341-353.

Kumar U. and Parida A. 2006. Maintenance performance measurement: The need of the hour for the mechanized mining industry, Proceedings of the 1st Asian Mining Congress, 16-18 Jan 2006, Kolkatha, India.

Maletic D., Maletic M., Al-Najjar B., Gomiscek B., 2014. The role of maintenance in improving company’s competitiveness and profitability: A case study in a textile company, Journal of Manufacturing Technology Management, 25(4), and pp.441-456.

Muchiri P., Pintelon L., Gelders L. and Martin H. (2011). Development of maintenance function performance measurement framework and indicators. International Journal of Production Economics, 131(1), pp. 295-302.

Oke S.A. 2005. An analytical model for the optimization of maintenance profitability, International Journal of Productivity and Performance Management, 54(2), pp.113-136.

Oke S.A. Oyedokun O.I, Akanbi O.G, Oyawale F.A. 2008. An inflation-based maintenance profitability model, International Journal of Productivity and Quality Management, 3(3), pp. 325-339.

Opricovic S. and Tzeng G.H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operations Research, 156, pp. 445-455.

Parida A. and Kumar U. 2004. Managing information is key to maintenance effectiveness, e-Proceedings of the Intelligent Maintenance System’s (IMS), July 15-17, Arles, France.

Parida A., Chattopadhyay G. and Kumar U. 2005. Multi-criteria maintenance performance measurement: A conceptual model. Proceedings of the 18th International Congress of Condition Monitoring and Diagnostic Engineering Management, 31 August – 2 September, Cranfield, UK, pp. 349-356.

Parida A. and Kumar U. 2006. Maintenance performance measurement (MPM): Issues and challenges, Journal of Quality in Maintenance Engineering, 12(3), pp. 239-251.

Parida A. 2007. Study and analysis of maintenance performance indicators (MPIs) for LKAB: A case study, Journal of Quality in Maintenance Engineering, 13(4), pp. 325-327.

Parida A and Uday K. 2009. Maintenance performance measurement: methods, tools and application, MaintWorld, 1(1), pp. 50-53.

Raouf A, 1994. Improving capital productivity through maintenance, International Journal of Operations & Production Management, 14(7), pp. 44-52.

Wang C-H. and Pang C-T. (2011). Using VIKOR Method for Evaluating Service Quality of Online Auction under Fuzzy Environment. International Journal of Computer Science Engineering and Technology, 1(6), pp. 307-314.

PlantWeb (2003).White paper: Reducing operations and maintenance costs. www.EmersonProcess.com (Accessed June 20, 2016).

Saaty T.L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48, pp. 9-26.

Simoes, J.M., Gomes, C.F. and Yasin M.M. (2011). A literature review of maintenance performance measurement: A conceptual framework and directions for future research, Journal of Quality in Maintenance Engineering, 17(2), pp.116-137.

Sondalini M (2016). Useful key performance indicators for maintenance. www.lifetime-reliability.com (Accessed June 20, 2016).

Wu H-Y., Chen J-K. and Chen I-S. (2012). Performance evaluation of aircraft maintenance staff using a fuzzy MCDM approach. International Journal of Innovative Computing, Information and Control, 8(6), pp. 3919- 3937.




DOI: http://dx.doi.org/10.2022/jmet.v9i1.951

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