Process Improvement Study in a Tire Factory

Yıl 2023, Cilt: 9 Sayı: 2, 111 - 122, 30.06.2023

Seher Arslankaya , Asude Demir

https://doi.org/10.22399/ijcesen.1289121

Öz

Today, motorsports is one of the sports branches with the world's largest audience and fan base. The production techniques of the tires used in these organizations are an indispensable factor in order to be the pioneer of the sector. In this study, SWOT Analysis and Failure Modes and Effects Analysis were performed for two different production lines, and the superiority of the lines against each other was evaluated. The process to be improved on the excellent line was determined as a result of brainstorming by an expert team. After the changed parameters, the effects on the final product and the process were evaluated. The study was concluded by determining that all the changes made do not constitute an obstacle to the continuity of the process and the quality of the final product. Time analysis was made by video recording the process whose cycle time changed. As a result of the calculations made after the time analysis, the annual tire gain was calculated as 7299.

Anahtar Kelimeler

Cycle time, SWOT analysis, Failure modes and effects analysis, Time analysis, Brainstorming, Process improvement

Kaynakça

• [1] Krajewski, L. J., Rıtzman L. P. and Malhotra M. K. (2014). Üretim yönetimi süreçler ve tedarik zincirleri (9. Ed), (S. Birgün, Trans.), Nobel publications, Ankara. https://books.google.com.tr/books/about/%C3%9Cretim_y%C3%B6netimi.html?id=G5JqngEACAAJ&redir_esc=y
• [2] Kirkham, L., Garza-Reyes, J. A., Kumar, V. and Antony J. (2014). Prioritisation of operations ımprovement projects in the europan manufacturing ındustry. International Journal of Production Research, 52(18); 5323-5345. Doi: 10.1080/00207543.2014.903345
• [3] Patel N., Chauhan N. and Trivedi P. (2015). Benefits of value stream mapping as a lean tool ımplementation manufacturing ındustries: a review. International Journal for Innovative Research in Science & Technology, 1(8); 53-57. http://www.ijirst.org/articles/IJIRSTV1I8017.pdf
• [4] Türkan, T. and Görener, A. (2017). Süreç iyileştirme: vasıflı çelik üretim sektöründe bir uygulama, Optimum Ekonomi ve Yönetim Bilimleri Dergisi, 4(2); 23-40. Doi: https://doi.org/10.17541/optimum.282050
• [5]Gupta, A., Singh, R.K. and Suri P.K. (2018). Sustainable service quality management by logistics service providers: an ındian perspective, Global Business Review, 19(3); 130-150. Doi: https://doi.org/10.1177/0972150918758098
• [6] Avunduk, H. (2019). Yalın altı sigma: bir pet şişirme makinesinde süreç iyileştirme uygulaması, Elektronik Sosyal Bilimler Dergisi, 18(70); 633-653. Doi: https://doi.org/10.17755/esosder.428802
• [7] Sevgili, A. and Antmen, Z. F. (2019). Yalın üretim tekniklerinden değer akış haritalandırmanın bir metal işleme fabrikasında süreç iyileştirme amacıyla uygulanması, Avrupa Bilim ve Teknoloji Dergisi, 16, 219-228. Doi: https://doi.org/10.31590/ejosat.555940
• [8] Apilioğulları, L. (2020). Yalın altı sigma ve endüstri 4.0 entegrasyonu ile kalite iyileştirme vaka çalışması, Anemon Muş Alparslan Üniversitesi Sosyal Bilimler Dergisi, 8(5); 1497-150. https://dergipark.org.tr/tr/pub/anemon/issue/57135/640553
• [9] Sarı, İ., Sergi, D. and Özuduruk, S. F. (2020). Müşteri hizmetleri bölümünde süreç analizi ve stratejik planlama lastik sektöründe bir uygulama, Eskişehir Teknik Üniversitesi Bilim Ve Teknoloji Dergisi, 8(2); 191-211. Doi: https://doi.org/10.20290/estubtdb.604569
• [10] Berber, G. and Deste, M. (2018). Süreç iyileştirme uygulamaları üzerine bir literatür araştırması, Uluslararası Ekonomi, İşletme ve Politika Dergisi, 2(2); 213-230. Doi: https://doi.org/10.29216/ueip.462265
• [11] Özan, M. (2021). Süreç yönetimi ve süreç iyileştirmenin işletme performansına etkilerinin analizi. İşletme Araştırmaları Dergisi, 13(2), 1144-1161. Doi:https://doi.org/10.20491/isarder.2021.1189
• [12] Çelik, H. (2020). Süreç iyileştirmede kaizen ve kaikaku uygulamasi. Avrasya Sosyal ve Ekonomi Araştırmaları Dergisi, 7(4), 245-259. https://dergipark.org.tr/en/pub/asead/issue/54055/708375#article_cite
• [13] Oskaloğlu, E. (2019). Üretim işletmelerinde süreç iyileştirme tekniklerinin kullanılabilirliği üzerine bir araştırma (Master's thesis, İnönü Üniversitesi Sosyal Bilimleri Enstitüsü). http://abakus.inonu.edu.tr/xmlui/handle/11616/15071
• [14] Sütçü, A., Karşıyaka, O. & Burhan, M. E. (2019). Bir mobilya üretim tesisinde iş analizi ve benzetim uygulaması ile süreç verimliliğinin artırılması. Avrupa Bilim ve Teknoloji Dergisi, (17). 45-57. DOI: 10.31590/ejosat.609563
• [15] Uluskan, M. (2019). Süreç yeterlilik analizinin genişletilmiş kaizen yöntemine entegrasyonu: otomotiv sektöründe bir uygulama. Eskişehir Osmangazi Üniversitesi Mühendislik ve Mimarlık Fakültesi Dergisi, 27(3), 165-183. DOI: 10.31796/ogummf.581278
• [16] Yildiz, B., & Sayin, B. (2019). Süreç Yönetiminin Ürün İnovasyon Performansı Üzerindeki Etkisinde Rekabet Yoğunluğunun Düzenleyici Rolü. Business and Economics Research Journal, 10(2), 575-586. https://www.ceeol.com/search/article-detail?id=762619
• [17] Selimoğlu, S. K., Yeşilçelebi, G., & Altunel, M. (2021). İç denetim süreçlerini iyileştirme ve risk yönetimi araçları: Yalın altı sigma ve FMEA. Muhasebe ve Finansman Dergisi, 201-218. Doi: https://doi.org/10.25095/mufad.950760
• [18] Akkurt, I Basyigit C., Kilincarslan S., Beycioglu, A. 2010. Prediction of photon attenuation coefficients of heavy concrete by fuzzy logic. Journal of the Franklın Instıtute-Engıneerıng and Applıed Mathematıcs. 347(9);1589-1597. DOI: 10.1016/j.jfranklin.2010.06.002
• [19] Arslankaya, S. and Çelik, M. T. (2021). Prediction of Heart Attack Using Fuzzy Logic Method and Determination of Factors Affecting Heart Attacks. International Journal of Computational and Experimental Science and Engineering, 7(1); 1-8. https://doi.org/10.22399/ijcesen.837731
• [20] Basyigit, C, Akkurt I, Kilincarslan S. and Beycioglu A. (2010). Prediction of compressive strength of heavyweight concrete by ANN and FL models. Neural Computıng & Applıcatıons 19(4);507-513 DOI: 10.1007/s00521-009-0292-9
• [21] Caymaz, T., Çalışkan, S. and Botsalı, A.R. (2022). Evaluation of Ergonomic Conditions using Fuzzy Logic in a Metal Processing Plant. International Journal of Computational and Experimental Science and Engineering, 8(1); 9-24 https://doi.org/10.22399/ijcesen.932994
• [22] Çilli, A., Beken, M. and Kurt, N. 2022. Determination of Theoretical Fracture Criteria of Layered Elastic Composite Material by ANFIS Method from Artificial Intelligence. International Journal of Computational and Experimental Science and Engineering, 8(2); 32-39. https://doi.org/10.22399/ijcesen.1077328
• [23] Akkurt, İ. Boodaghi Malidarreh P. and Boodaghi Malidarre R.,., (2021): Simulation and Prediction the Attenuation Behavior of the KNN-LMN Based Lead Free Ceramics by FLUKA Code and Artificial Neural Network (ANN) - Based Algorithm, Environmental Technology, DOI: 10.1080/09593330.2021.2008017
• [24] Boodaghi Malidarre R., Akkurt İ, Boodaghi Malidarreh P. and Arslankaya S. (2022). Investigation and ANN-based prediction of the radiation shielding, structural and mechanical properties of the Hydroxyapatite (HAP) bio-composite as artificial bone. Radiation Physics and Chemistry. 197;110208. https://doi.org/10.1016/j.radphyschem.2022.110208
• [25] Ural, A. and Kilimci, Z. H. (2021). The Prediction of Chiral Metamaterial Resonance using Convolutional Neural Networks and Conventional Machine Learning Algorithms. International Journal of Computational and Experimental Science and Engineering, 7 (3); 156-163 . https://doi.org/10.22399/ijcesen.973726
• [26] Ecer, B. , Aktas, A. , Kabak, M. and Dağdeviren, M. (2020). Determining the Best Maternity Hospital by Using a Fuzzy Decision Making Model. International Journal of Computational and Experimental Science and Engineering, 6(1); 7-12. https://doi.org/10.22399/ijcesen.646157
• [27] Kırelli, Y., Arslankaya, S., Alcan, P. (2022). MRI Image Analysis with Deep Learning Methods in Brain Tumor Diagnosis. In: Sen, Z., Oztemel, E., Erden, C. (eds) Recent Advances in Intelligent Manufacturing and Service Systems. Lecture Notes in Mechanical Engineering. Springer, Singapore. Print ISBN 978-981-16-7163-0Online ISBN 978-981-16-7164-7 https://doi.org/10.1007/978-981-16-7164-7_4
• [28] Çelik M.T. and Arslankaya S. (2023). Analysis of Quality Control Criteria in An Business With The Fuzzy Dematel Method: Glass Business Example. Journal of Engineering Research. 11(2);100039, https://doi.org/10.1016/j.jer.2023.100039
• [29] Boodaghi Malidarre R., Arslankaya S., Nar M., Kırelli Y., Erdamar I.Y.D., Karpuz N., Ozhan Dogan S. and Boodaghi Malidarre P. (2022). Deep learning prediction of gamma-ray-attenuation behavior of KNN–LMN ceramics. Emerging Materials Research 11(2);276-282 https://doi.org/10.1680/jemmr.22.00012
• [30] Imamoglu, M.Y., Akkurt, I., Arslankaya, S. et al. (2022). Prediction of radiation shielding properties for concrete by artificial neural networks. Eur. Phys. J. Plus 137;865 https://doi.org/10.1140/epjp/s13360-022-02815-3
• [31] Teke Ç., Akkurt İ., Arslankaya S., Ekmekci, İ and Gunoglu K. (2023). Prediction of gamma ray spectrum for 22Na source by feed forward back propagation ANN model. Radiation Physics and Chemistry, 202;110558, https://doi.org/10.1016/j.radphyschem.2022.110558
• [32] A. Bakeer, I. S. Mohamed, P. Boodaghi Malidarreh, I. Hattabi and L. Liu, (2022). An Artificial Neural Network-Based Model Predictive Control for Three-Phase Flying Capacitor Multilevel Inverter. in IEEE 10;70305-70316, 2022, doi: 10.1109/ACCESS.2022.3187996.
• [33] Kırelli Y. and Arslankaya S. (2020). Sentiment Analysis of Shared Tweets on Global Warming on Twitter with Data Mining Methods: A Case Study on Turkish Language. Computational Intelligence and Neuroscience 2020;1904172 https://doi.org/10.1155/2020/1904172
• [34] Erol, Y. (2019). Stratejik yönetimde swot analizi ve bir işletmede uygulanması, Master’s thesis, İstanbul Kultur University. https://acikerisim.iku.edu.tr/entities/publication/30df3ecb-6b5f-4544-9046-ed9e30d74a75
• [35] Turan, M. and Ocaktan, D. (2019). Transformatör üreten bir firmada risk analizinde bulanık htea kullanımı ve uygulama yazılımı geliştirme, Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 21(1); 474-487. Doi: https://doi.org/10.25092/baunfbed.549171
• [36] Berber, G. and Deste, M. (2021). Bir gıda işletmesinde süreç iyileştirme uygulaması: dondurma fabrikasi örneği, Anadolu Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(3); 53-72. Doi: https://doi.org/10.53443/anadoluibfd.959147
• [37] Kaya, D.Ş. (2017). Root cause analysıs: examples of scenarıo, Gümüşhane University Journal Of Health Sciences, 6(4); 247-251. https://search.trdizin.gov.tr/tr/yayin/detay/285749/root-cause-analysis-examples-of-scenario