Metal Sektöründe üretim sürelerine etki eden faktörlerin veri madenciliği yöntemleriyle tespit edilmesi

Year 2021, Volume: 36 Issue: 4, 1949 - 1962, 02.09.2021

Kübra Işık Selda Kapan Ulusoy

https://doi.org/10.17341/gazimmfd.736659

Cited By: 3

Abstract

Günümüzün küresel rekabet koşullarında hayatta kalabilmek için işletmeler üretimlerinde düşük teslim zamanı, düşük maliyet, yüksek kalite ve yüksek esnekliği hedeflemek zorundadırlar. Proje bazlı üretim yapan firmaların bu hedeflere ulaşabilmesi için siparişe dayalı üretim yöntemini tercih etmeleri gerekmektedir. Siparişe dayalı üretimde ürünün teslim tarihinde hazır olması büyük önem taşımaktadır. Teslim tarihlerinin azaltılması için üretim süresini etkileyen faktörlerin tespit edilmesi gerekmektedir. Üretim süresine etki eden faktörlerin tespit edilmesi, bu faktörler üzerinde yapılabilecek iyileştirmeleri öngörmeyi sağlayacaktır. Bu çalışmada üretim süresine etki eden faktörlerin veri madenciliği yöntemleri ile belirlenebileceği metal sektöründe üretim yapan bir firmaya uygulanarak gösterilmiştir. Bu faktörler araştırılırken veri madenciliğinden çeşitli sınıflandırma algoritmaları kullanılmıştır. Uygulama sonucunda en iyi sonuçlar random tree algoritması ile elde edilmiştir. Üretim süresine etki eden faktörler parça adı, makine adı, üretim ayı, ortalama sıcaklık, operatör adı, tezgâh boyutu, ürün miktarı olarak bulunmuştur. Uygulama sonucunda üretilen bilgiler ile işletmeye üretim süreçleri için iyileştirme tavsiyeleri verilmiştir. Ham veri kümesi ek dosyada verilmiştir.

Keywords

Veri madenciliği, üretim süresine etki eden faktörler, kural tabanlı sınıflandırma, karar ağacı tabanlı sınıflandırma, nitelik seçimi

Thanks

Güven Mühendislik Makine Ltd. Şti. ’ye çalışmada kullanılan verilere ulaşmada sağladıkları destekten dolayı teşekkür ederiz.

Determining the factors that affect the production time in the metal industry utilizing data mining methods

Abstract

In order to survive in today's global competitive environment, companies must aim for low delivery time, low cost, high quality, and high flexibility in their production. Companies engaged in project-based production should prefer the order-based production method to achieve these goals. For order-based production method, it is very important that the product is ready at the delivery date. To reduce delivery dates, factors affecting production time should be determined. Determining the factors affecting the production time enables companies to plan the improvements that can be made on these factors. On an application, it is shown that data mining can be used to identify the factors affecting production times in metal industry. While investigating these factors, various classification algorithms were used. In the result best evaluation metrics were obtained with random tree algorithm. The features that best express the model used are part name, machine name, month of production, average temperature, operator name, machine size and product quantity. With the information produced, improvement recommendations that can be applied to the production processes are given to the company. The raw data set can be accessed as a supplementary file.

Keywords

Data mining, factors affecting production time, rule based classification, decision tree based classification, feature selection

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