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A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants

Year 2021, Volume: 24 Issue: 1, 75 - 86, 01.03.2021
https://doi.org/10.2339/politeknik.626171

Abstract

The main goal of power plants is to generate the electricity in sustainability perspective consisting of the principles of environmental awareness, reliability, efficiency, economy and uninterruptedness. Complying with the operational directives and maintenance are twin pillars for achieving this comprehensive goal. Within this scope, this study handles the maintenance strategy selection problem which is the first step of the effective maintenance management for one of the most important equipment groups among thousands of equipment in one of the large-scale hydroelectric power plants which have great importance for Turkey energy mix with approximately a fifth share in the total generation. So as to determine the most critical equipment group AHP-TOPSIS combination is used. For the selected equipment group, the most appropriate of all applicable 4 maintenance strategies are determined via PROMETHEE, which has been limited used for the maintenance strategy selection problem in the literature despite its advantages. As a result of this study which is the first in the literature with its method configuration and its application in hydroelectric power plants, a 1-year observation is conducted to confirm the proposed approach, and a 100% improvement is achieved in the unit shutdowns resulting from the selected equipment.

References

  • [1] Albayrak B. Budget presentation for 2018. Republic of Turkey Minister of Energy and Natural Resources. Turkish; November 2017.
  • [2] Özcan E.C., Erol S., “A multi-objective mixed integer linear programming model for energy resource allocation problem: The case of Turkey”, Gazi Journal of Science, 27(4):1157-1168, (2014).
  • [3] Renewables 2018 global status report. Renewable Energy Policy Network for the 21st Century (REN 21); 2018. ISBN: 978-3-9818911-3-3
  • [4] Enerji Atlası [cited 2018 December 06]. Hydroelectric power generation rate. Available from: http://www.enerjiatlasi.com/elektrik-uretimi/; Turkish. 2018.
  • [5] Madu C.N., “Competing through maintenance strategies”, International Journal of Quality & Reliability Management,17(9):937–948, (2000).
  • [6] Mobley R.K. “An introduction to predictive maintenance”, Woburn: Buttherworth-Heinemann; 2002.
  • [7] Ding S.H., Kamaruddin S., “Maintenance policy optimization—literature review and directions”, International Journal of Advanced Manufacturing Technologies, 76:1263–1283, (2015).
  • [8] Bevilacqua M., Braglia M., “The analytic hierarchy process applied to maintenance strategy selection”, Reliability Engineering & System Safety,70(1):71-83, (2000).
  • [9] Hajej Z., Turki S., Rezg N., “Modelling and analysis for sequentially optimising production, maintenance and delivery activities taking into account product returns”, International Journal of Production Research, 53(15): 4694-4719, (2015).
  • [10] Guiras Z., Turki S., Rezg N., Dolgui A., “Optimal maintenance plan for two-level assembly system and risk study of machine failure”, International Journal of Production Research, 1-18, (2018).
  • [11] Bouslikhane S., Hajej Z., Rezg N., “An optimal integrated maintenance to production with carbon emission for a closed-loop system”, 5th International Conference on Control, Decision and Information Technologies,2018 (CoDIT), 177-182, (2018).
  • [12] Hafidi N., El Barkany A., Mahmoudi M., “Optimizing subcontracting choice in the context of integrated maintenance into production”, International Colloquium on Logistics and Supply Chain Management, 2018 (LOGISTIQUA), 206-210, (2018).
  • [13] Shafiee M., “Maintenance strategy selection problem: an MCDM overview”, Journal of Quality in Maintenance Engineering, 21(4):378-402, (2015).
  • [14] Özdağoğlu A., “The effects of different normalization methods to decision making process in TOPSIS”, Ege Academic Review, 13(2), 245-257, (2013).
  • [15] Wang H., “A survey of maintenance policies of deteriorating systems”, European Journal of Operational Research, 139(3): 469-489, (2002).
  • [16] Garg A., Deshmukh S.G., “Maintenance management: literature review and directions”, Journal of Quality in Maintenance Engineering, 12(3): 205-238, (2006).
  • [17] Velmurugan R.S., Dhingra T., “Maintenance strategy selection and its impact in maintenance function: a conceptual framework”, International Journal of Operations & Production Management, 35(12):1622-1661, (2015).
  • [18] Rocha P., Rodrigues R.C., “Bibliometric review of improvements in building maintenance”, Journal of Quality in Maintenance Engineering, 23(4):437-456, (2017).
  • [19] Andrawus J.A., Watson J., Kishk M., Adam A., “The selection of a suitable maintenance strategy for wind turbines”, Wind Engineering, 30(6): 471-486, (2006).
  • [20] Nilsson J., Bertling L., “Maintenance management of wind power systems using condition monitoring systems—life cycle cost analysis for two case studies”, IEEE Transactions on Energy Conversion, 22(1): 223-229, (2007).
  • [21] Wang L., Chu J., Wu J., “Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process”, International Journal of Production Economics, 107(1): 151-163, (2007).
  • [22] Srivastava P., Khanduja D., Agrawal V.P., “A framework of fuzzy integrated MADM and GMA for maintenance strategy selection based on agile enabler attributes”, Mathematics-in-Industry Case Studies, 8(1): 5, (2017).
  • [23] Shayesteh E., Yu J, Hilber P., “Maintenance optimization of power systems with renewable energy sources integrated”, Energy, 149: 577-586, (2018).
  • [24] Sharma R.K., Kumar D., Kumar P., “FLM to select suitable maintenance strategy in process industries using MISO model”, Journal of Quality in Maintenance Engineering, 11(4): 359-374, (2005).
  • [25] Braglia M., Castellano D., Frosolini M., “An integer linear programming approach to maintenance strategies selection”, International Journal of Quality & Reliability Management, 30(9): 991-1016, (2013).
  • [26] Muinde P.M., “Maintenance strategy selection using analytic hierarchy process: a case study”, Journal of Sustainable Research in Engineering, 1(4): 21-29, (2015).
  • [27] Saassouh B., Dieulle L., Grall A., “Online maintenance policy for a deteriorating system with random change of mode”, Reliability Engineering & System Safety, 92(12): 1677-1685, (2007).
  • [28] Sadeghi A., Manesh R.A., “The application of fuzzy group analytic network process to selection of best maintenance strategy-a case study in mobarakeh steel company”, Iran. Procedia-Social and Behavioral Sciences, 62: 1378-1383, (2012).
  • [29] Ilangkumaran M., Kumanan S., “Application of hybrid VIKOR model in selection of maintenance strategy”, International Journal of Information Systems and Supply Chain Management, 5(2): 59-81, (2012).
  • [30] Siew-Hong D., Kamaruddin S., “Selection of optimal maintenance policy by using fuzzy multi criteria decision making method”, International Conference on Industrial Engineering and Operations Management, 3-6, (2012).
  • [31] Odeyale S.O., Alamu O.J., Odeyale E.O., „The analytical hierarchy process concept for maintenance strategy selection in manufacturing industries”, The Pacific Journal of Science and Technology, 14(1): 223-233, (2013).
  • [32] Goossens A.J., Basten R.J., Exploring maintenance policy selection using the Analytic Hierarchy Process; an application for naval ships”, Reliability Engineering & System Safety, 142:31-41, (2015).
  • [33] Mollaverdi N., Abdollahi H., “Selecting optimal maintenance strategy using qualitative-quantitative model and multi-criteria decision-making approach”, International Conference on Industrial Engineering and Operations Management, 99-103, (2015).
  • [34] Baidya R., Dey P.K., Ghosh S.K., Petridis K., “Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach”, International Journal of Advanced Manufacturing Technologies, 94(1-4): 31-44, (2018).
  • [35] Borjalilu N., Ghambari M., “Optimal maintenance strategy selection based on a fuzzy analytical network process: A case study on a 5-MW powerhouse”, International Journal of Engineering Business Management, 10: 1-10, (2018).
  • [36] Joshua J., Mathew S.G., Harikrishnan A.R., “Selection of an optimum maintenance strategy for improving the production efficiency in a casting unit”, Journal of Engineering Science and Technology, 3(2): 138-141, (2016).
  • [37] Zhao J., Yang L.A., “Bi-objective model for vessel emergency maintenance under a condition-based maintenance strategy”, Simulation, 94(7): 609-624, (2018).
  • [38] Emovon I., Norman R.A., Murphy A.J., “Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems”, Journal of Intelligent Manufacturing, 29(3): 519-531, (2018).
  • [39] Mechefske C.K., Wang Z., “Using fuzzy linguistics to select optimum maintenance and condition monitoring strategies”, Mechanical Systems and Signal Processing, 15(6): 1129-1140, (2001).
  • [40] Jafari A., Jafarian M., Zareei A., Zaerpour F., “Using fuzzy Delphi method in maintenance strategy selection problem”, Journal of Uncertain Systems, 2(4): 289-298, (2008).
  • [41] Bashiri M., Badri H., Hejazi T.H., “Selecting optimum maintenance strategy by fuzzy interactive linear assignment method”, Applied Mathematical Modelling, 35(1): 152-164, (2011).
  • [42] Seiti H., Hafezalkotob A., Fattahi R., “Extending a pessimistic–optimistic fuzzy information axiom-based approach considering acceptable risk: Application in the selection of maintenance strategy”, Applied Soft Computing, 67: 895-909, (2018).
  • [43] Nguyen T.A.T., Chou S.Y., “Maintenance strategy selection for improving cost-effectiveness of offshore wind systems”, Energy Conversion and Management, 157: 86-95, (2018).
  • [44] Tu J., Sun C., Zhang X., Pan H., Cheng R., “Maintenance strategy decision for avionics system based on cognitive uncertainty information processing”, Eksploatacjai Niezawodność, 17(2): 297-305, (2015).
  • [45] Ibraheem A.T., Atia N.S., “Applying decision making with analytic hierarchy process (AHP) for maintenance strategy selection of flexible pavement”, The Global Journal of Researches in Engineering, 16(5): 25-34, (2016).
  • [46] Azadeh A., Gharibdousti M.S., Firoozi M., Baseri M., Alishahi M., Salehi V., “Selection of optimum maintenance policy using an integrated multi-criteria Taguchi modeling approach by considering resilience engineering”, International Journal of Advanced Manufacturing Technologies, 84(5-8): 1067-1079, (2016).
  • [47] Carnero M.C., Gómez A., “Maintenance strategy selection in electric power distribution systems”, Energy, 129: 255-272, (2017).
  • [48] Pun K.P., Tsang Y.P., Choy K.L., Tang V., Lam H.Y., “A fuzzy-AHP-Based decision support system for maintenance strategy selection in facility management”, 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 1-7, (2017).
  • [49] Faghihinia E., Mollaverdi N., “Building a maintenance policy through a multi-criterion decision-making model”, Journal of Industrial Engineering International, 8(14):1-15, (2012).
  • [50] Cavalcante C.A.V., Ferreira R.J.P., De Almeida A.T., “A preventive maintenance decision model based on multicriteria method PROMETHEE II integrated with Bayesian approach”, IMA Journal of Management Mathematics, 21:333–348, (2010).
  • [51] Almeida-Filho A., Ferreira R.J.P., Almeida A., “A DSS based on multiple criteria decision making for maintenance planning in an electrical power distributor”, Evolutionary Multi-Criterion Optimization (EMO), 787-95, (2013).
  • [52] Chareonsuk C., Nagarur N., Tabucanon M.T., “A multicriteria approach to the selection of preventive maintenance intervals”, International Journal of Production Economics, 49(1):55-64, (1997).
  • [53] Lin J., Meng F., Chen R., Zhang Q., “Preference attitude-based method for ranking intuitionistic fuzzy numbers and its application in renewable energy selection”, Complexity, 2018: 1-14, (2018).
  • [54] Maghsoodi A.I., Maghsoodi A.I., Mosavi A., Rabczuk T., Zavadskas E.K., “Renewable energy technology selection problem using integrated H-SWARA-MULTIMOORA approach”, Sustainability, 10(12): 1-18, (2018).
  • [55] Karunathilake H., Hewage K., Mérida W., Sadiq R., “Renewable energy selection for net-zero energy communities: Life cycle-based decision making under uncertainty”, Renewable Energy, 130: 558-573, (2019).
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  • [57] Özcan E.C., Ünlüsoy S., Eren T., “A combined goal programming – AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants”, Renewable & Sustainable Energy Review, 78:1410-1423, (2017).
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A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants

Year 2021, Volume: 24 Issue: 1, 75 - 86, 01.03.2021
https://doi.org/10.2339/politeknik.626171

Abstract

The main goal of power plants is to generate the electricity in sustainability perspective consisting of the principles of environmental awareness, reliability, efficiency, economy and uninterruptedness. Complying with the operational directives and maintenance are twin pillars for achieving this comprehensive goal. Within this scope, this study handles the maintenance strategy selection problem which is the first step of the effective maintenance management for one of the most important equipment groups among thousands of equipment in one of the large-scale hydroelectric power plants which have great importance for Turkey energy mix with approximately a fifth share in the total generation. So as to determine the most critical equipment group AHP-TOPSIS combination is used. For the selected equipment group, the most appropriate of all applicable 4 maintenance strategies are determined via PROMETHEE, which has been limited used for the maintenance strategy selection problem in the literature despite its advantages. As a result of this study which is the first in the literature with its method configuration and its application in hydroelectric power plants, a 1-year observation is conducted to confirm the proposed approach, and a 100% improvement is achieved in the unit shutdowns resulting from the selected equipment.

References

  • [1] Albayrak B. Budget presentation for 2018. Republic of Turkey Minister of Energy and Natural Resources. Turkish; November 2017.
  • [2] Özcan E.C., Erol S., “A multi-objective mixed integer linear programming model for energy resource allocation problem: The case of Turkey”, Gazi Journal of Science, 27(4):1157-1168, (2014).
  • [3] Renewables 2018 global status report. Renewable Energy Policy Network for the 21st Century (REN 21); 2018. ISBN: 978-3-9818911-3-3
  • [4] Enerji Atlası [cited 2018 December 06]. Hydroelectric power generation rate. Available from: http://www.enerjiatlasi.com/elektrik-uretimi/; Turkish. 2018.
  • [5] Madu C.N., “Competing through maintenance strategies”, International Journal of Quality & Reliability Management,17(9):937–948, (2000).
  • [6] Mobley R.K. “An introduction to predictive maintenance”, Woburn: Buttherworth-Heinemann; 2002.
  • [7] Ding S.H., Kamaruddin S., “Maintenance policy optimization—literature review and directions”, International Journal of Advanced Manufacturing Technologies, 76:1263–1283, (2015).
  • [8] Bevilacqua M., Braglia M., “The analytic hierarchy process applied to maintenance strategy selection”, Reliability Engineering & System Safety,70(1):71-83, (2000).
  • [9] Hajej Z., Turki S., Rezg N., “Modelling and analysis for sequentially optimising production, maintenance and delivery activities taking into account product returns”, International Journal of Production Research, 53(15): 4694-4719, (2015).
  • [10] Guiras Z., Turki S., Rezg N., Dolgui A., “Optimal maintenance plan for two-level assembly system and risk study of machine failure”, International Journal of Production Research, 1-18, (2018).
  • [11] Bouslikhane S., Hajej Z., Rezg N., “An optimal integrated maintenance to production with carbon emission for a closed-loop system”, 5th International Conference on Control, Decision and Information Technologies,2018 (CoDIT), 177-182, (2018).
  • [12] Hafidi N., El Barkany A., Mahmoudi M., “Optimizing subcontracting choice in the context of integrated maintenance into production”, International Colloquium on Logistics and Supply Chain Management, 2018 (LOGISTIQUA), 206-210, (2018).
  • [13] Shafiee M., “Maintenance strategy selection problem: an MCDM overview”, Journal of Quality in Maintenance Engineering, 21(4):378-402, (2015).
  • [14] Özdağoğlu A., “The effects of different normalization methods to decision making process in TOPSIS”, Ege Academic Review, 13(2), 245-257, (2013).
  • [15] Wang H., “A survey of maintenance policies of deteriorating systems”, European Journal of Operational Research, 139(3): 469-489, (2002).
  • [16] Garg A., Deshmukh S.G., “Maintenance management: literature review and directions”, Journal of Quality in Maintenance Engineering, 12(3): 205-238, (2006).
  • [17] Velmurugan R.S., Dhingra T., “Maintenance strategy selection and its impact in maintenance function: a conceptual framework”, International Journal of Operations & Production Management, 35(12):1622-1661, (2015).
  • [18] Rocha P., Rodrigues R.C., “Bibliometric review of improvements in building maintenance”, Journal of Quality in Maintenance Engineering, 23(4):437-456, (2017).
  • [19] Andrawus J.A., Watson J., Kishk M., Adam A., “The selection of a suitable maintenance strategy for wind turbines”, Wind Engineering, 30(6): 471-486, (2006).
  • [20] Nilsson J., Bertling L., “Maintenance management of wind power systems using condition monitoring systems—life cycle cost analysis for two case studies”, IEEE Transactions on Energy Conversion, 22(1): 223-229, (2007).
  • [21] Wang L., Chu J., Wu J., “Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process”, International Journal of Production Economics, 107(1): 151-163, (2007).
  • [22] Srivastava P., Khanduja D., Agrawal V.P., “A framework of fuzzy integrated MADM and GMA for maintenance strategy selection based on agile enabler attributes”, Mathematics-in-Industry Case Studies, 8(1): 5, (2017).
  • [23] Shayesteh E., Yu J, Hilber P., “Maintenance optimization of power systems with renewable energy sources integrated”, Energy, 149: 577-586, (2018).
  • [24] Sharma R.K., Kumar D., Kumar P., “FLM to select suitable maintenance strategy in process industries using MISO model”, Journal of Quality in Maintenance Engineering, 11(4): 359-374, (2005).
  • [25] Braglia M., Castellano D., Frosolini M., “An integer linear programming approach to maintenance strategies selection”, International Journal of Quality & Reliability Management, 30(9): 991-1016, (2013).
  • [26] Muinde P.M., “Maintenance strategy selection using analytic hierarchy process: a case study”, Journal of Sustainable Research in Engineering, 1(4): 21-29, (2015).
  • [27] Saassouh B., Dieulle L., Grall A., “Online maintenance policy for a deteriorating system with random change of mode”, Reliability Engineering & System Safety, 92(12): 1677-1685, (2007).
  • [28] Sadeghi A., Manesh R.A., “The application of fuzzy group analytic network process to selection of best maintenance strategy-a case study in mobarakeh steel company”, Iran. Procedia-Social and Behavioral Sciences, 62: 1378-1383, (2012).
  • [29] Ilangkumaran M., Kumanan S., “Application of hybrid VIKOR model in selection of maintenance strategy”, International Journal of Information Systems and Supply Chain Management, 5(2): 59-81, (2012).
  • [30] Siew-Hong D., Kamaruddin S., “Selection of optimal maintenance policy by using fuzzy multi criteria decision making method”, International Conference on Industrial Engineering and Operations Management, 3-6, (2012).
  • [31] Odeyale S.O., Alamu O.J., Odeyale E.O., „The analytical hierarchy process concept for maintenance strategy selection in manufacturing industries”, The Pacific Journal of Science and Technology, 14(1): 223-233, (2013).
  • [32] Goossens A.J., Basten R.J., Exploring maintenance policy selection using the Analytic Hierarchy Process; an application for naval ships”, Reliability Engineering & System Safety, 142:31-41, (2015).
  • [33] Mollaverdi N., Abdollahi H., “Selecting optimal maintenance strategy using qualitative-quantitative model and multi-criteria decision-making approach”, International Conference on Industrial Engineering and Operations Management, 99-103, (2015).
  • [34] Baidya R., Dey P.K., Ghosh S.K., Petridis K., “Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach”, International Journal of Advanced Manufacturing Technologies, 94(1-4): 31-44, (2018).
  • [35] Borjalilu N., Ghambari M., “Optimal maintenance strategy selection based on a fuzzy analytical network process: A case study on a 5-MW powerhouse”, International Journal of Engineering Business Management, 10: 1-10, (2018).
  • [36] Joshua J., Mathew S.G., Harikrishnan A.R., “Selection of an optimum maintenance strategy for improving the production efficiency in a casting unit”, Journal of Engineering Science and Technology, 3(2): 138-141, (2016).
  • [37] Zhao J., Yang L.A., “Bi-objective model for vessel emergency maintenance under a condition-based maintenance strategy”, Simulation, 94(7): 609-624, (2018).
  • [38] Emovon I., Norman R.A., Murphy A.J., “Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems”, Journal of Intelligent Manufacturing, 29(3): 519-531, (2018).
  • [39] Mechefske C.K., Wang Z., “Using fuzzy linguistics to select optimum maintenance and condition monitoring strategies”, Mechanical Systems and Signal Processing, 15(6): 1129-1140, (2001).
  • [40] Jafari A., Jafarian M., Zareei A., Zaerpour F., “Using fuzzy Delphi method in maintenance strategy selection problem”, Journal of Uncertain Systems, 2(4): 289-298, (2008).
  • [41] Bashiri M., Badri H., Hejazi T.H., “Selecting optimum maintenance strategy by fuzzy interactive linear assignment method”, Applied Mathematical Modelling, 35(1): 152-164, (2011).
  • [42] Seiti H., Hafezalkotob A., Fattahi R., “Extending a pessimistic–optimistic fuzzy information axiom-based approach considering acceptable risk: Application in the selection of maintenance strategy”, Applied Soft Computing, 67: 895-909, (2018).
  • [43] Nguyen T.A.T., Chou S.Y., “Maintenance strategy selection for improving cost-effectiveness of offshore wind systems”, Energy Conversion and Management, 157: 86-95, (2018).
  • [44] Tu J., Sun C., Zhang X., Pan H., Cheng R., “Maintenance strategy decision for avionics system based on cognitive uncertainty information processing”, Eksploatacjai Niezawodność, 17(2): 297-305, (2015).
  • [45] Ibraheem A.T., Atia N.S., “Applying decision making with analytic hierarchy process (AHP) for maintenance strategy selection of flexible pavement”, The Global Journal of Researches in Engineering, 16(5): 25-34, (2016).
  • [46] Azadeh A., Gharibdousti M.S., Firoozi M., Baseri M., Alishahi M., Salehi V., “Selection of optimum maintenance policy using an integrated multi-criteria Taguchi modeling approach by considering resilience engineering”, International Journal of Advanced Manufacturing Technologies, 84(5-8): 1067-1079, (2016).
  • [47] Carnero M.C., Gómez A., “Maintenance strategy selection in electric power distribution systems”, Energy, 129: 255-272, (2017).
  • [48] Pun K.P., Tsang Y.P., Choy K.L., Tang V., Lam H.Y., “A fuzzy-AHP-Based decision support system for maintenance strategy selection in facility management”, 2017 Portland International Conference on Management of Engineering and Technology (PICMET), 1-7, (2017).
  • [49] Faghihinia E., Mollaverdi N., “Building a maintenance policy through a multi-criterion decision-making model”, Journal of Industrial Engineering International, 8(14):1-15, (2012).
  • [50] Cavalcante C.A.V., Ferreira R.J.P., De Almeida A.T., “A preventive maintenance decision model based on multicriteria method PROMETHEE II integrated with Bayesian approach”, IMA Journal of Management Mathematics, 21:333–348, (2010).
  • [51] Almeida-Filho A., Ferreira R.J.P., Almeida A., “A DSS based on multiple criteria decision making for maintenance planning in an electrical power distributor”, Evolutionary Multi-Criterion Optimization (EMO), 787-95, (2013).
  • [52] Chareonsuk C., Nagarur N., Tabucanon M.T., “A multicriteria approach to the selection of preventive maintenance intervals”, International Journal of Production Economics, 49(1):55-64, (1997).
  • [53] Lin J., Meng F., Chen R., Zhang Q., “Preference attitude-based method for ranking intuitionistic fuzzy numbers and its application in renewable energy selection”, Complexity, 2018: 1-14, (2018).
  • [54] Maghsoodi A.I., Maghsoodi A.I., Mosavi A., Rabczuk T., Zavadskas E.K., “Renewable energy technology selection problem using integrated H-SWARA-MULTIMOORA approach”, Sustainability, 10(12): 1-18, (2018).
  • [55] Karunathilake H., Hewage K., Mérida W., Sadiq R., “Renewable energy selection for net-zero energy communities: Life cycle-based decision making under uncertainty”, Renewable Energy, 130: 558-573, (2019).
  • [56] Özcan E.C., “Maintenance management system: fundamentals of installation and operation”, Electricity Generation Co, (2016)
  • [57] Özcan E.C., Ünlüsoy S., Eren T., “A combined goal programming – AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants”, Renewable & Sustainable Energy Review, 78:1410-1423, (2017).
  • [58] Geyik O., Tosun M., Ünlüsoy S., Hamurcu M., Eren T., “Using AHP and TOPSIS methods for selecting of publishing house”, International Journal of Social and Educational Sciences, 3(6): 106-126, (2016).
  • [59] Alver V., Çetin S., Eren T., Bedir N., “The solution of the assignment problem of paid teachers to primary and secondary schools with the AHP and mathematical programming model: A case in Kırıkkale, Turkey”, International Journal of Lean Thinking, 9(1): 13-32, (2018).
  • [60] Taş M., Özlemiş Ş.N., Hamurcu M., Eren T., “Determination of monorail line type in Ankara with AHP and PROMETHEE approach”, Journal of Economics, Business, Politics and International Relations, 3(1): 64-89, (2017).
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There are 72 citations in total.

Details

Primary Language English
Subjects Engineering
Journal Section Research Article
Authors

Evrencan Özcan 0000-0002-3662-6190

Şeyda Gür 0000-0002-4639-9657

Tamer Eren 0000-0001-5282-3138

Publication Date March 1, 2021
Submission Date September 27, 2019
Published in Issue Year 2021 Volume: 24 Issue: 1

Cite

APA Özcan, E., Gür, Ş., & Eren, T. (2021). A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants. Politeknik Dergisi, 24(1), 75-86. https://doi.org/10.2339/politeknik.626171
AMA Özcan E, Gür Ş, Eren T. A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants. Politeknik Dergisi. March 2021;24(1):75-86. doi:10.2339/politeknik.626171
Chicago Özcan, Evrencan, Şeyda Gür, and Tamer Eren. “A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants”. Politeknik Dergisi 24, no. 1 (March 2021): 75-86. https://doi.org/10.2339/politeknik.626171.
EndNote Özcan E, Gür Ş, Eren T (March 1, 2021) A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants. Politeknik Dergisi 24 1 75–86.
IEEE E. Özcan, Ş. Gür, and T. Eren, “A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants”, Politeknik Dergisi, vol. 24, no. 1, pp. 75–86, 2021, doi: 10.2339/politeknik.626171.
ISNAD Özcan, Evrencan et al. “A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants”. Politeknik Dergisi 24/1 (March 2021), 75-86. https://doi.org/10.2339/politeknik.626171.
JAMA Özcan E, Gür Ş, Eren T. A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants. Politeknik Dergisi. 2021;24:75–86.
MLA Özcan, Evrencan et al. “A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants”. Politeknik Dergisi, vol. 24, no. 1, 2021, pp. 75-86, doi:10.2339/politeknik.626171.
Vancouver Özcan E, Gür Ş, Eren T. A Hybrid Model to Optimize the Maintenance Policies in the Hydroelectric Power Plants. Politeknik Dergisi. 2021;24(1):75-86.

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