Abstract
Abstract
A metropolitan area's water supply is imperative to the city's development. One of the main goals of the water supply utilities is to ensure the availability of water, as a lack of water would cause many social, political, or health problems. Therefore, water supply facilities must be in good condition, efficient preventive maintenance plans must be implemented, and the performance of the maintenance team monitored. In this paper, efficiency indices of Tehran water utility maintenance teams are investigated using different Data Envelopment Analysis (DEA) models. The final scores were then used as inputs to a Fuzzy Inference System (FIS) to assess the efficiency of these maintenance units. Two performance indicators based on DEA, "Availability efficiency" and "Repair time efficiency" are introduced for performance assessment. The Mean Time Between Failure (MTBF) and the Ready To Operate (RTO) are two desirable outputs that are considered in addition to one undesirable output: the Mean Time To Repair (MTTR). In addition, we suggest a new index named MRRW by combining the DEA efficiency with the RRW index. We introduce a novel approach based on DEA combined with FIS methods and the new factors for evaluating water supply maintenance systems, while most previous studies on measuring the efficiency of maintenance teams consider only limited aspects of performance measurement. Based on the results of our study, it became clear that the MRRW measures efficiency better than the traditional RRW measures. We present future improvement strategies based on the output of the FIS.
Funder
FHNW University of Applied Sciences and Arts Northwestern Switzerland
Publisher
Springer Science and Business Media LLC
Subject
Management of Technology and Innovation,Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management
Reference67 articles.
1. Abdulgader FS, Eid R, Daneshvar Rouyendegh B (2018) Development of decision support model for selecting a maintenance plan using a fuzzy MCDM approach: a theoretical framework. Appl Comput Intell Soft Comput Article ID 9346945:2018
2. Akbari N, Jones D, Treloar R (2020) A cross-European efficiency assessment of offshore wind farms: A DEA approach. Renew Energy 151:1186–1195
3. Arabameri A, Rezaei K, Cerdà A, Conoscenti C, Kalantari Z (2019) A comparison of statistical methods and multi-criteria decision making to map flood hazard susceptibility in Northern Iran. Sci Total Environ 660:443–458
4. Assaf SA, Hadidi LA, Hassanain MA, Rezq MF (2015) Performance evaluation and benchmarking for maintenance decision making units at petrochemical corporation using a DEA model. Int J Adv Manuf Technol 76(9):1957–1967
5. Banda EM, Mwale FD (2018) Utility performance in supplying water to informal settlements: a case study from Malawi. Util Policy 55:151–157