THE DIGITAL TWIN MODEL OF CNC MACHINES TO ESTIMATE OPERATION COMPLETION TIMES

Year 2023, Volume: 7 Issue: 2, 303 - 321, 31.08.2023

Elif Cesur , Raşit Cesur , Beyza Nur Aydoğan

https://doi.org/10.46519/ij3dptdi.1215353

Cited By: 1

Abstract

As digital transformation takes hold in the industry, studies are exploring how modeling physical systems in digital environments can boost production efficiency. The objective is to tackle more complex issues than traditional methods and achieve more cost-effective and higher-quality production. The integration of artificial intelligence and machine learning into industrial processes is a very important step in digitalization studies. Integrating artificial intelligence and machine learning using the Internet of Things (IoT) has shown great potential, as data collection, processing, and extraction can be done through a single platform. One of the areas where these technologies are being used is in the Digital Twin (DT) applications. Digital transformation enables real-time control of systems by creating a virtual environment that mirrors the real world. The most effective targets for applying DT technology in industrial control are 3D printers, robots, and CNC benches. In this study, the main objective is to develop a DT model for manufacturing systems. In the second phase of the study, the execution time of linear motion commands on machines of flexible manufacturing systems was estimated using the developed DT model. In the estimation phase, different machine learning algorithms were used and their performances were compared.

Keywords

Digital Twin, İntelligent Manufacturing Systems, CNC Workbenches

CNC TEZGAHLARININ DİJİTAL İKİZ MODELİ İLE KOMUT TAMAMLANMA SÜRELERİNİN TAHMİN EDİLMESİ

Abstract

Endüstride dijital dönüşümün başlamasıyla fiziksel sistemlerin dijital ortamda modellenerek üretim verimliliğinin artması için çok sayıda çalışma yapılmıştır. Bu çalışamalar mevcut yöntemlere kıyasla daha karmaşık sorunları çözmek, maliyet ve kalite açısından daha etkin üretim yapmak amacıyla gerçekleştirilmektedir. Dijitalleşme çalışmalarında yapay zekâ ve makine öğreniminin endüstriyel operasyonlara dahil edilmesi oldukça önemli bir adım olmuştur. IoT ile entegre yapay zekâ ve makine öğrenimi, veri toplama, işleme ve bilgi çıkarımın tek bir yerde yapılmasına izin verdiği için büyük bir potansiyele sahip olduğu görülmüştür. Bu teknolojilerin kullanıldığı alanlardan biri ise Dijital İkiz (Dİ) uygulamalarıdır. Dİ ile, gerçek dünyanın sanal ortamda birebir modeli oluşturularak sistemlerin gerçek zamanlı kontrolü sağlanmaktadır. Endüstriyel kontrolde Dİ teknolojisinin uygulanabileceği en etkin bileşenler ise 3 boyutlu yazıcılar, robotlar ve CNC tezgâhlarıdır. Bu çalışmada, öncelikle üretim sistemlerinin Dİ modelinin geliştirilmesi hedeflenmiştir. Çalışmanın ikinci aşamasında ise geliştirilen Dİ modeli ile esnek imalat sistemi tezgahlarında doğrusal hareket komutlarının tamamlanma süresi tahmin edilmiştir. Tahmin aşamasında birden çok makine öğrenmesi algoritmaları kullanılmış ve performansları karşılaştırılmıştır. 0.995745 R2ve 0.991615 doğruluk değerleri ile Yapay sinir ağları modeli en iyi yöntem olduğu görülmektedir.

Keywords

Dijital İkiz, Zeki İmalat Sistemleri, CNC tezgâhları

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