Keşifsel Veri Analizi Kullanarak Vakum Şarj Test Süresinin Azaltılması

Year 2021, Volume: 5 Issue: 1, 187 - 196, 29.06.2021

Tuğba Demircan Süleyman Eken

Abstract

Günümüzde giderek artan rekabet koşulları ve pazarda kalıcı olabilme gibi dış faktörler firmaların sistemlerini daha verimli kullanmaya, maliyetlerini azaltmaya, yüksek kalite düzeyinde ürün üretmeye yönlendirmektedir. Firmaların yaptıkları bu çalışmalarda proses iyileştirme adımları önem taşımaktadır. Bu çalışmada üretim süreçleri keşifsel yolla analiz edilerek darboğaz oluşturan istasyon tespit edilmiştir. Keşifsel veri analizi ile kalıpları keşfetmek, anormallikleri tespit etmek, özet istatistikler ve grafik gösterimler yardımıyla varsayımları kontrol etmek için veriler üzerinde ilk araştırmaları gerçekleştirmek mümkün olmuştur. Vakum test istasyonunun katma değersiz test süresi belirlenerek proses süresi azaltılmıştır. Belirlenen yeni test süresi ile üretim kapasite artışı ve hattın daha verimli çalışması sağlanmıştır. Bu sayede günlük üretim adedi 136’dan 188’e, hat verimliliği %55’ten %77’ye artmış ve istasyonların birbirini beklemesi %35’ten %10’a düşmüştür. Aynı zamanda hattın yıllık üretim kapasitesi %27 artarak 58K dan 79K adede ulaşmıştır.

Keywords

Keşifsel Veri Analizi, Grafiksel Teknik, Tanımlayıcı İstatistik, Verimlilik, Kapasite Artışı, Plant Simulation

Thanks

BSH Ev Aletleri Sanayi ve Ticaret A.Ş.’ye çalışmanın yapılmasındaki katkılarından dolayı teşekkür ederiz.

Reducing Vacuum Charge Test Time Using Exploratory Data Analysis

Abstract

Nowadays, external factors such as increasing levels of competition and having a permanent place in the market are directing companies to use their systems more efficiently, to reduce their costs, and to produce higher quality products. Process improvement steps are important in studies of these companies. In this study, the vacuum test station that created a bottleneck was determined by analyzing the production process in an exploratory way. Through exploratory data analysis, it was possible to perform an initial data investigation to discover patterns, spot anomalies, test hypothesis, and check assumptions with the help of summary statistics and graphic representations. By determining the value-added test time of the vacuum test station, the process time was reduced. Using the new test period, production capacity increased and a more efficient operation of the line was achieved. The number of daily production increased from 136 to 188, line efficiency increased from 55% to 77%, and the stations waiting for each other decreased from 35% to 10%. At the same time, the annual production capacity of the line increased by 27%, reaching from 58K to 79K.

Keywords

Exploratory Data Analysis, Graphical Technique, Descriptive Statistics, Productivity, Capacity Increase, Plant Simulation

References

• Chen, L., Ding, Z., & Sun, F. (2010). Performance analysis of a vacuum thermionic refrigerator with external heat transfer. Journal of applied physics, 107(10), 104507.
• Chiarini, A., Belvedere, V., & Grando, A. (2020). Industry 4.0 strategies and technological developments. An exploratory research from Italian manufacturing companies. Production Planning & Control, 31(16), 1385-1398.
• Cleff, T. (2014). Exploratory data analysis in business and economics. Exploratory Data Analysis in Business and Economics. https://doi. org /10.1007/978-3-319- 01517- 0.
• Eken, S. (2020a). An exploratory teaching program in big data analysis for undergraduate students. Journal of Ambient Intelligence and Humanized Computing, 11(10), 4285-4304.
• Eken, S. (2020b). Büyük Verinin İnteraktif Görselleştirilmesi: Tableau Üzerine Öğrenci Deneyimleri. Avrupa Bilim ve Teknoloji Dergisi, (18), 262-271.
• Gang, L., & Xianping, Z. (2005). Research on vacuum thermal isolation plate applied to refrigerator for isolation. Cryogenics and Superconductivity, 4.
• Misra, S., Zhou, B. B., Drozdov, I. K., Seo, J., Urban, L., Gyenis, A., ... & Yazdani, A. (2013). Design and performance of an ultra-high vacuum scanning tunneling microscope operating at dilution refrigerator temperatures and high magnetic fields. Review of Scientific Instruments, 84(10), 103903.
• Martinez, W. L., Martinez, A. R., & Solka, J. (2017). Exploratory data analysis with MATLAB. Florida, FL:Crc Press.
• Ozturk, H. M., Ozturk, H. K., & Kocar, G. (2011). Comparison of vacuum cooling with conventional cooling for purslane. International Journal of Food Engineering, 7(6), 1-18.
• Rennie, T. J., Raghavan, G. S. V., & Vigneault, C. (2000). Determination of the product refrigeration load in vacuum cooling of lettuce. Applied Engineering in Agriculture, 16(5), 459.
• Sahoo, K., Samal, A. K., Pramanik, J., & Pani, S. K. (2019). Exploratory data analysis using Python. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 8(12), 2019.
• Sukumar, R. S., Gopichand, A., Janardhana, U., Kumar, V. S., & Chanti, B. V. Design and Fabrication of Water Refrigeration System by Creating Vacuum. International Journal of Innovative Research in Science, Engineering and Technology, 4(4), 2428-2434.
• Tao, W. H., Huang, C. M., Hsu, C. L., & Lin, J. Y. (2004). Performance study of an energy-efficient display case refrigerator. Chemical Engineering Communications, 191(4), 550-565.
• Thiessen, S., Knabben, F. T., & Melo, C. (2016). An Experimental Study on the Use of Vaccum Insulation Panels in Household Refrigerators. Proceedings of International Refrigeration and Air Conditioning Conference (pp. 1–8). West Lafayette, IN: Purdue University.
• Tummers, J., Catal, C., Tobi, H., Tekinerdogan, B., & Leusink, G. (2020). Coronaviruses and people with intellectual disability: an exploratory data analysis. Journal of Intellectual Disability Research, 64(7), 475-481.
• Velleman, P. F., & Hoaglin, D. C. (1981). Applications, basics, and computing of exploratory data analysis. London, Duxbury Press.
• Zhao, R., Qiao, L., Gao, Z., & Huang, D. (2020). Effect of Vacuum Insulation Panels on Energy Consumption and Thermal Load Transfer between Compartments in a Three-Temperature Frost-Free Refrigerator. Energies, 13(7), 1559.