Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi 2149-3871 Nevşehir Hacı Bektaş Veli Üniversitesi 10.30783/nevsosbilen.1196320 RELIABILITY ANALYSIS OF A CIRCULAR KNITTING MACHINE BİR YUVARLAK ÖRME MAKİNESİNİN GÜVENİLİRLİK ANALİZİ https://orcid.org/0000-0001-7063-148X Gülbahar Sümeyra ERCİYES ÜNİVERSİTESİ https://orcid.org/0000-0001-5604-0448 Kapan Ulusoy Selda ERCİYES ÜNİVERSİTESİ https://orcid.org/0000-0001-9459-146X Zeydan Mithat İSTANBUL MEDENİYET ÜNİVERSİTESİ 03 31 2023 13 1 291 308 10 29 2022 01 30 2023 Copyright © 2011, Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi 2011 Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi

One of the main factors affecting the quality of the product in production systems is the quality of the manufacturing process that produces the product. Failure of production equipment can increase the rate of faulty products and reduce the production time due to the time spent in repair. In order to minimize the failures, the reliability of the machines should be modeled and the machine maintenance plan should be determined in line with the predictions obtained from the model. The aim of this study is to model the mechanical failures that may occur during fabric production in a circular knitting machine in a company in the bedding fabric sector in Turkey by using counting processes. In the study, firstly, the production and failure records of the past days were examined and the mechanical failures in production were determined and arranged. As a result of trend analyzes using graphical methods and hypothesis tests, it has been determined that the appropriate model for the failure behavior of the machine is the Nonhomogeneous Poisson Process (HOPS). The failure density function of HOPS is expressed by the Power Law model. The adequacy of the model was demonstrated by the goodness-of-fit test based on R2. Reliability measures estimated from the model revealed that the machine was failing more and more frequently. This showed the necessity of overhauling the machine in order to minimize production time loss and quality loss. This study example demonstrates the importance of reliability analysis in maintenance planning.

Üretim sistemlerinde ürünün kalitesini etkileyen ana faktörlerden biri ürünü üreten imalat sürecinin kalitesidir. Üretim ekipmanlarının arızalanması hatalı ürün oranını artırabilmekte ve tamirde geçen süre nedeni ile üretim süresini azaltmaktadır. Arızaları en aza indirmek için makinelerin güvenilirliğinin modellenerek, modelden elde edilen tahminler doğrultusunda makine bakım planının belirlenmesi gerekmektedir. Bu çalışmada, Türkiye’de yatak kumaşı sektöründe faaliyet gösteren bir firmada, yuvarlak örme makinesinde kumaş üretimi esnasında meydana gelebilecek mekanik arızalar sayma süreçleri kullanılarak modellenmiştir. Çalışmada öncelikle geçmiş günlere ait üretim ve arıza kayıtları incelenerek üretimde gerçekleşen mekanik arızalar tespit edilmiş ve düzenlenmiştir. Grafiksel yöntemler ve hipotez testleri kullanılarak yapılan trend analizleri sonucunda makinenin arızalanma davranışı için uygun modelin Homojen Olmayan Poisson Süreci (HOPS) olduğu belirlenmiştir. HOPS’un arıza yoğunluk fonksiyonu Kuvvet Yasası modeli ile ifade edilmiştir. Modelin yeterliliği R2’ye dayalı uyum iyiliği testi ile gösterilmiştir. Modelden tahmin edilen güvenilirlik ölçütleri makinenin gittikçe daha sık arızalandığını ortaya çıkarmıştır. Bu durum üretim zamanı kaybı ve kalite kaybını en aza indirmek için makineye revizyon yapılması gerekliliğini göstermiştir. Bu çalışma örneğinde bakım planlanmasında güvenilirlik analizinin önemi görülmüştür.

 Güvenilirlik Homojen Olmayan Poisson Süreci Kuvvet Yasası Modeli Duruş Tahmini Stokastik Süreçler Reliability Nonhomogeneous Poisson Process Power Law Model Stoppage Estimation Stochastic Processes Akpınar, A. (2020). Homojen olmayan poisson süreci ile bir bankaya ait atm makinasının güvenilirliğinin test edilmesi. [Yüksek Lisans Tezi, Fırat Üniversitesi, Elazığ]. Ulusal Tez Merkezi. Ascher, H., & Feingold, H. (1984). Repairable systems modelling, inferences, misconceptions and their causes. Marcel Decker. Block, J., Ahmadi, A., Tyrberg, T., & Kumar, U. (2014). Fleet-level reliability of multiple repairable units: a parametric approach using the power law process. International Journal of Performability Engineering, 10(3), 239-250. http://www.ijpe-online.com/EN/10.23940/ijpe.14.3.p239.mag Buğatekin, A. T. (2017). Homojen olmayan poisson süreci ile bir makinenin güvenilirliğinin test edilmesi. Fırat Üniversitesi Mühendislik Bilimleri Dergisi, 29(1), 207-211. https://dergipark.org.tr/tr/pub/fumbd/issue/29393/314657 Chen, Z. (2004). Bayesian and emprical bayes approaches to power law process and microarray. [University of South Florida Ph. D. Thesis, United States of America]. Cirrone, G. A. P., Donadio, S., Guatelli, S., Mantero, A., Mascialino, B., Parlati, S., ...& Viarengo, P. (2004). A goodness-of-fit statistical toolkit. IEEE Transactions on Nuclear Science, 51(5), 2056-2063. https://doi.org/10.1109/TNS.2004.836124 Crowder, M. J., Kimber, A. C., Sweeting, T. J., & Smith, R. L. (1991). Statistical analysis of reliability data. Routledge. Çolak, M., Çetin, T., & Atılgan, A. (2017). Mobilya endüstrisinde tamir bakımın önemi ve bir uygulama. Akademia Mühendislik ve Fen Bilimleri Dergisi, 2(3), 60-70. Demirdöğen, O., & Küçük, O. (2013). Üretim işlemler yönetimi. Detay Yayıncılık. Du, J. (2008). Evaluation of equipment reliability, availability and maintainability in an oil sands processing plant. [University of British Columbia Doctoral dissertation, Kanada]. Garmabaki, A. H. S., Ahmadi, A., Block, J., Pham, H., & Kumar, U. (2016). A reliability decision framework for multiple repairable units. Reliability Engineering & System Safety, 150, 78-88. https://doi.org/10.1016/j.ress.2016.01.020 Gaudoin, O., Yang, B., & Xie, M. (2003). A simple goodness-of-fit test for the power-law process, based on the Duane plot. IEEE Transactions on Reliability, 52(1), 69-74. https://doi.org/10.1109/TR.2002.805784 Gonzalez, C. A., Torres, A., & Rios, M. A. (2014, 10-13 September). Reliability assessment of distribution power repairable systems using HOPS. In 2014 IEEE PES Transmission & Distribution Conference and Exposition, Latin America (PES T&D-LA). Hartler, G. (1989). The nonhomogeneous Poisson process-a model for the reliability of complex repairable systems. Microelectronics Reliability, 29(3), 381-386. https://doi.org/10.1016/0026-2714(89)90624-0 Jones, R. B. (1995). Risk based management: a reliability centered approach. Gulf Professional Publishing. Kendall, M. G. (1970). Rank correlation methods. Griffin. Köle, C., & Gökpınar, F. (2014). Üstel dağılıma uygunluk için bazı uyum iyiliği testlerinin 1. tip hata ve güçleri bakımından kıyaslanmaları. Süleyman Demirel Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 16(3), 318-326. https://dergipark.org.tr/tr/pub/sdufenbed/issue/20799/222088 Kumar, U., & Klefsjö, B. (1992). Reliability analysis of hydraulic systems of LHD machines using the power law process model. Reliability Engineering & System Safety, 35(3), 217-224. https://doi.org/10.1016/0951-8320(92)90080-5 Kuo, W., & Zuo, M. J. (2003). Optimal reliability modelling, principles and applications. John Wiley and Sons, Inc. Kvaloy, J. T., & Lindqvist, B. H. (1998). TTT-based tests for trend in repairable systems data. Reliability Engineering & System Safety, 60(1), 13-28. https://doi.org/10.1016/S0951-8320(97)00099-9 Lewis, P. A., & Robinson, D. W. (1974). Testing for a monotone trend in a modulated renewal process. In:ProschanF,Serfling RJ,editors. Reliability and Biometry.Philadelphia: SIAM. Louit, D. M., Pascual, R., & Jardine, A. K. (2009). A practical procedure for the selection of time-to-failure models based on the assessment of trends in maintenance data. Reliability Engineering & System Safety, 94(10), 1618-1628. https://doi.org/10.1016/j.ress.2009.04.001 Lutfiah İsmail, A. T. (2014). Testing the performance of the power law process model considering the use of regression approach. International Journal of Software Engineering and Applications, 5(5), 35-46. https://doi.org/10.5121/ijsea.2014.5503 Mann, H. (1945). Nonparametric tests against trend. Econometrica: Journal of the econometric society, 13(3), 245–259. https://doi.org/10.2307/1907187 Meeker, W.Q., & Escobar, L.A. (1998). Statistical methods for reliability data. John Wiley and Sons, Inc. Montgomery, D. C. (2013). Applied statistics and probability for engineers. John Wiley and Sons, Inc. Nelson, W. B. (2003). Recurrent events data analysis for product repairs, disease recurrences, and other applications. Society for Industrial and Applied Mathematics. Rausand, M., & Høyland, A. (2004). System reliability theory: models, statistical methods, and applications. John Wiley and Sons, Inc. Rigdon, S. E., & Basu, A. P. (2000). Statistical methods for the reliability of repairable systems. John Wiley and Sons, Inc. Rigdon, S. E., & Basu, A. P. (1989). The power law process: a model for the reliability of repairable systems. Journal of Quality Technology, 21(4), 251-260. https://doi.org/10.1080/00224065.1989.11979183 Ross, S. M. (1996). Stochastic processes. John Wiley and Sons, Inc. Ryan, K. J. (2003). Some flexible families of ıntensities for non-homogeneous poisson process models and their bayes ınference. Qual. Reliab. Engng. Int, 19, 171–181. https://doi.org/10.1002/qre.520 Saldanha, P. L. C., De Simone, E. A., & E Melo, P. F. F. (2001). An application of non-homogeneous poisson point processes to the reliability analysis of service water pumps. Nuclear engineering and design, 210(1-3), 125-133. https://doi.org/10.1016/S0029-5493(01)00412-5 Tobias, P. (2022). Statistical Methods Group, SEMATECH. https://www.itl.nist.gov/div898/handbook/apr/section2/apr223.htm Tsarouhas, P. H., & Arvanitoyannis, I. S. (2010). Assessment of operation management for beer packaging line based on field failure data: a case study. Journal of Food Engineering, 98(1): 51-59. https://doi.org/10.1016/j.jfoodeng.2009.12.007 Tsarouhas, P. (2012a). Reliability, availability and maintainability analysis in food production lines: a review. International Journal of Food Science & Technology, 47(11), 2243-2251. https://doi.org/10.1111/j.1365-2621.2012.03073.x Uzgören, N., & Elevli, S. (2010). Homojen olmayan poisson süreci: bir maden makinesinin güvenilirlik analizi. Journal of the Faculty of Engineering & Architecture of Gazi University, 25(4), 827-837. https://dergipark.org.tr/tr/pub/gazimmfd/issue/6686/88607 Van Dyck, J., & Verdonck, T. (2014). Precision of power-law HOPS estimates for multiple systems with known failure rate scaling. Reliability Engineering & System Safety, 126, 143-152. https://doi.org/10.1016/j.ress.2014.01.019 Yıldırım, N. (2013). Normal dağılım için uyum iyiliği testleri ve bir simülasyon çalışması. [Yüksek Lisans Tezi, Gazi Üniversitesi, Ankara]. Ulusal Tez Merkezi. Zhang, D., Zhang, Y., Yu, M., & Chen, Y. (2014). Reliability defects identification of serial production systems: application to a piston production line. Arabian Journal for Science and Engineering, 39(12), 9113-9125. https://doi.org/10.1007/s13369-014-1426-7 Wang, P., & Coit, D. W. (2005, 24-27 January). Repairable systems reliability trend tests and evaluation. In Annual Reliability and Maintainability Symposium, Proceedings.