A mathematical model proposal for maintenance strategies optimization of the most critical electrical equipment groups of hydroelectric power plants

Öz

Maintenance is a process that makes a high-level contribution to the sustainability goal of the manufacturing facilities defined as uninterrupted, high-quality level, economic, efficient, reliable and environmentally friendly production. The foremost stage of this important process is the maintenance planning and the first and indispensable phase of this stage is the maintenance strategy selection. When considering the maintenance processes which cause the significant costs due to production downtime, material, time and labor requirements, assignment of the suitable maintenance strategies especially for the critical equipment has great importance in terms of avoiding the unnecessary costs for the generation facility. Furthermore, maintenance strategy optimization directly effects the goal of sustainable production in the manufacturing facilities by providing to increase the faultless operating time of equipment and contribute to realize the reliable and high-quality manufacturing. In addition to these, this problem becomes more and more important in the electricity generation plants which are in the group of continuous production facilities, when the effects of energy on the society are considered. In this context in this study, among the electrical equipment which are the most problematic group, the most critical ones in terms of the power plant are determined by the AHP-TOPSIS combination in one of the big-scale hydroelectric power plants realize the 20% of Turkey’s electricity generation. Then, the most appropriate strategy combination from corrective, periodic, predictive and revision maintenance strategies is obtained by using the proposed integer programming model for these equipment groups. The use of this combination has resulted in an 80% improvement in generation downtimes and associated costs.

Anahtar Kelimeler

• Maintenance strategy optimization,Hydroelectric power plants,Integer programming,AHP,TOPSIS

Hidroelektrik santralların en kritik elektriksel ekipman gruplarının bakım stratejilerinin optimizasyonu için matematiksel bir model önerisi

Öz

Bakım, üretim tesislerinin kesintisiz, kalite düzeyi yüksek, ekonomik, verimli, güvenilir ve çevreye duyarlı üretim yapması olarak tanımlanan sürdürülebilirlik hedefine üst düzeyde katkı sağlayan bir prosestir. Bu önemli prosesin en önemli aşamalarının başında bakım planlaması gelmektedir ve bu fazın ilk ve vazgeçilmez aşaması ise bakım strateji seçimidir. Bakım proseslerinin üretim duruşu, malzeme, zaman ve iş gücü gereksinimi nedeniyle önemli maliyetler doğurması düşünüldüğünde, özellikle kritik ekipmanlara uygun bakım stratejilerinin atanması, üretim tesisinin gereksiz maliyetlerden kaçınması açısından büyük önem arz etmektedir.  Ayrıca, ekipmanın arızasız çalışma süresinin artırılması ile güvenilir ve kalite düzeyi yüksek üretimin gerçekleştirilmesine sağladığı katkı ile de bakım strateji optimizasyonu, üretim tesislerinde sürdürülebilir üretim hedefine direkt olarak etki etmektedir. Bunların yanı sıra, sürekli üretim tesisleri grubunda yer alan elektrik üretim santrallarında, enerjinin toplum üzerindeki etkileri de düşünüldüğünde bu problem çok daha önemli bir hal almaktadır. Bu bağlamda bu çalışmada, Türkiye enerji üretiminin %20’sini gerçekleştiren hidroelektrik santrallardan büyük ölçekli bir tanesinde, en problemli ekipman grubu olan elektriksel ekipmanlar arasından santral açısından en kritik olanlar AHP-TOPSIS kombinasyonu ile belirlenmiştir. Ardından, bu ekipman grupları için tamir, periyodik, kestirimci ve revizyon bakım stratejilerinden en uygun kombinasyon önerilen tam sayılı programlama modeli ile elde edilmiştir. Bu kombinasyonun kullanımı ile üretim duruşları ve bunların beraberinde getirdiği maliyetlerde %80 oranında bir iyileşme sağlanmıştır.

Anahtar Kelimeler

• Bakım strateji optimizasyonu,Hidroelektrik santrallar,Tam sayılı programlama,AHP,TOPSIS

Kaynakça

1. Bevilacqua M, Braglia M. “The analytic hierarchy process applied to maintenance strategy selection”. Reliability Engineering & System Safety, 70(1), 71-83, 2000.
2. Shafiee, M. “Maintenance strategy selection problem: an MCDM overview”. Journal of Quality in Maintenance Engineering, 21(4), 378-402, 2015.
3. Mobley RK. An Introduction to Predictive Maintenance. Butterworth-Heinemann, 2002.
4. Yıldız C, Şekkeli M. “Türkiye gün öncesi elektrik piyasasında rüzgar enerjisi ve pompaj depolamalı hidroelektrik santral için optimum teklif oluşturulması”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 22(5), 361-366, 2016.
5. Uyan M. “Güneş enerjisi santrali kurulabilecek alanların AHP yöntemi kullanılarak CBS destekli haritalanması”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23(4), 343-351, 2017.
6. T.C. Enerji ve Tabii Kaynaklar Bakanlığı. http://www.enerji.gov.tr/tr-TR/Sayfalar/Elektrik (13.11.2018).
7. Enerji Atlası. http://www.enerjiatlasi.com/elektrik-uretimi/ (13.11.2018).
8. Özcan EC. Bakım Yönetim Sistemi: Kurulum ve İşletme Esasları. Ankara, Türkiye, Elektrik Üretim AŞ. Yayınları, 2016.

9. Ding SH, Kamaruddin S. “Maintenance policy optimization-literature review and directions”. The International Journal of Advanced Manufacturing Technology, 76(5-8), 1263-1283, 2015.
10. Bertolini M, Bevilacqua M. “A combined goal programming-AHP approach to maintenance selection problem”. Reliability Engineering & System Safety, 91(7), 839-848, 2006.
11. Özcan EC, Ünlüsoy S, Eren T. “A combined goal programming–AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants”. Renewable and Sustainable Energy Reviews, 78, 1410-1423, 2017.
12. Nguyen TAT, Chou SY. “Maintenance strategy selection for improving cost-effectiveness of offshore wind systems”. Energy Conversion and Management, 157, 86-95, 2018.
13. 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.
14. Kirubakaran B, Ilangkumaran M. “Selection of optimum maintenance strategy based on FAHP integrated with GRA–TOPSIS”. Annals of Operations Research, 245(1-2), 285-313, 2016.
15. Seiti H, Tagipour R, Hafezalkotob A, Asgari F. “Maintenance strategy selection with risky evaluations using RAHP”. Journal of Multi‐Criteria Decision Analysis, 24(5-6), 257-274, 2017.
16. Carnero MC, Gómez A. “Maintenance strategy selection in electric power distribution systems”. Energy, 129, 255-272, 2017.
17. Panchal D, Chatterjee P, Shukla RK, Choudhury T, Tamosaitiene J. “Integrated fuzzy AHP-CODAS framework for maintenance decision in urea fertilizer industry”. Economic Computation & Economic Cybernetics Studies & Research, 51(3), 179-196, 2017.
18. Nazeri A, Naderikia R. “A new fuzzy approach to identify the critical risk factors in maintenance management.” The International Journal of Advanced Manufacturing Technology, 92(9-12), 3749-3783,2017.
19. George-Williams H, Patelli E. “Maintenance strategy optimization for complex power systems susceptible to maintenance delays and operational dynamics”. IEEE Transactions on Reliability, 66(4), 1309-1330, 2017.
20. Krishnasamy L, Khan F, Haddara M. “Development of a risk-based maintenance (RBM) strategy for a power-generating plant”. Journal of Loss Prevention in the Process Industries, 18(2), 69-81, 2005.
21. Shagluf A, Parkinson S, Longstaff AP, Fletcher S. “Adaptive decision support for suggesting a machine tool maintenance strategy: from reactive to preventative”. Journal of Quality in Maintenance Engineering, 24(3), 376-399,2018.
22. Heo JH, Park GP, Yoon YT, Park JK, Lee SS. “Optimal maintenance strategies for transmission systems using the genetic algorithm”. Transmission and Distribution Conference Proceedings, New Orleans, USA, 19-22 April 2010.
23. Labib AW. “A decision analysis model for maintenance policy selection using a CMMS”. Journal of Quality in Maintenance Engineering, 10(3), 191-202, 2004.
24. Baidya R, Dey PK, Ghosh SK, Petridis K. “Strategic maintenance technique selection using combined quality function deployment, the analytic hierarchy process and the benefit of doubt approach”. The International Journal of Advanced Manufacturing Technology, 94(1-4), 31-44, 2018.
25. Dedopoulos IT, Shah N. “Preventive maintenance policy optimization for multipurpose plant equipment”. Computers & Chemical Engineering, 19, 693-698, 1995.
26. Goel HD, Grievink J, Weijnen MP. “Integrated optimal reliable design, production, and maintenance planning for multipurpose process plants”. Computers & Chemical Engineering, 27(11), 1543-1555, 2003.
27. Löfsten H. “Management of industrial maintenance–economic evaluation of maintenance policies”. International Journal of Operations & Production Management, 19(7), 716-737, 1999.
28. Shahin A, Pourjavad E, Shirouyehzad H. “Selecting optimum maintenance strategy by analytic network process with a case study in the mining industry”. International Journal of Productivity and Quality Management, 10(4), 464-483, 2012.
29. Görener A. “Maintenance strategy selection by using WSA and TOPSIS methods under fuzzy decision environment”. Sigma Journal of Engineering and Natural Sciences, 31(2), 159-177, 2013.
30. Vahdani B, Hadipour H, Sadaghiani JS, Amiri M. “Extension of VIKOR method based on interval-valued fuzzy sets”. The International Journal of Advanced Manufacturing Technology, 47(9-12), 1231-1239, 2010.
31. Thor J, Ding SH, Kamaruddin S. “Comparison of multi criteria decision making methods from the maintenance alternative selection perspective”. The International Journal of Engineering and Science, 2(6), 27-34, 2013.
32. Sankpal P, Andrew A, Kumanan S. “Maintenance strategies selection using fuzzy FMEA and integer programming”. In Proceedings of the International Conference on Advances in Production and Industrial Engineering, 503-509, 23-24 January 2015.
33. Emovon I, Norman RA, Murphy AJ. “Hybrid MCDM based methodology for selecting the optimum maintenance strategy for ship machinery systems”. Journal of Intelligent Manufacturing, 29(3), 519-531, 2018.
34. Shyjith K, Ilangkumaran M, Kumanan S. “Multi-criteria decision-making approach to evaluate optimum maintenance strategy in textile industry”. Journal of Quality in Maintenance Engineering, 14(4), 375-386, 2008.
35. Ilangkumaran M, Kumanan S. “Selection of maintenance policy for textile industry using hybrid multi-criteria decision making approach”. Journal of Manufacturing Technology Management, 20(7), 1009-1022, 2009.
36. Ioannis D, Nikitas N. “Application of Analytic Hierarchy Process & TOPSIS methodology on ships’ maintenance strategies”. In Journal of Polish Safety and Reliability Association, Summer Safety and Reliability Seminars, 4(1), 21-28, 2013.
37. Wang JJ, Jing YY, Zhang CF, Zhao JH. “Review on multi-criteria decision analysis aid in sustainable energy decision-making”. Renewable and Sustainable Energy Reviews, 13(9), 2263-2278, 2009.
38. Kubler S, Robert J, Derigent W, Voisin A, Le Traon Y. “A state-of the-art survey & testbed of fuzzy AHP (FAHP) applications”. Expert Systems with Applications, 65, 398-422, 2016.
39. Vaidya OS, Kumar S. “Analytic hierarchy process: An overview of applications”. European Journal of Operational Research, 169(1), 1-29, 2006.
40. Kumar A, Sah B, Singh AR, Deng Y, He X, Kumar P, Bansal RC. “A review of multi criteria decision making (MCDM) towards sustainable renewable energy development”. Renewable and Sustainable Energy Reviews, 69, 596-609, 2017.
41. Velasquez M, Hester PT. “An analysis of multi-criteria decision making methods”. International Journal of Operation Research,10(2), 56–66, 2013.
42. Saaty T. The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. USA, McGraw-Hill, 1980.
43. Behzadian M, Otaghsara SK, Yazdani M, Ignatius J. “A state-of the-art survey of TOPSIS applications”. Expert Systems with Applications, 39(17), 13051-13069, 2012.
44. Hwang CL, Yoon K. Multiple Attribute Decision Making: Methods and Applications. Berlin, Springer-Verlag, 1981.
45. Zyoud SH, Fuchs-Hanusch D. “A bibliometric-based survey on AHP and TOPSIS techniques”. Expert Systems with Applications, 78, 158-181,2017.
46. Arıbaş M, Özcan U. “Akademik araştırma projelerinin AHP ve TOPSIS yöntemleri kullanılarak değerlendirilmesi. Politeknik Dergisi, 19(2), 163-173, 2016.
47. Jünger M, Liebling TM, Naddef D, Nemhauser GL, Pulleyblank WR, Reinelt G, Wolsey LA. 50 Years of Integer Programming 1958-2008: From the Early Years to the State-of-the-Art. Berlin, Springer Science & Business Media, 2009.
48. Taha HA. Integer Programming: Theory, Applications and Computations. USA, Academic Press, 2014.
49. Yatırımlar Dergisi. http://www.yatirimlar.com/haber-2018_Yilinda_Turkiye_Ortalama_Elektrik_Toptan_Satis_Fiyati_171_KrskWh_olarak_belirlendi-241241.htm (13.11.2018).