Özlem ÖRNEK, Eyyüp GÜLBANDILAR, Ahmet YAZICI

AKILLI FABRİKALARDAKİ OTONOM TAŞIYICILAR İÇİN BULANIK MANTIK TABANLI ANOMALİ TESPİTİ

Dijital dönüşüm sanayideki birçok sürecin veri odaklı yeni yaklaşımlarla ele alınmasını gerekli kılmaktadır. Bu bağlamda Endüstri 4.0 ile beraber akıllı fabrikalarda da önemli dijital dönüşümün olması beklenmektedir. Akıllı fabrikalardaki dijital dönüşüme katkı sağlayacak en önemli teknolojilerden bir tanesi de otonom taşıyıcı araç (OTA)’lardır. OTA’ların fabrika içerisindeki görevlerini verimli bir şeklide gerçekleştirmeleri ve beklenmedik bir problem veya aksama olduğunda insan müdahalesi olmadan bu durumun veri üzerinden tespiti önemlidir. Bu çalışmada, Bulanık mantık ile OTA’ların fabrika içerisindeki trafik ağında oluşabilecek beklenmedik durma, yavaşlama vb. kaynaklı anormal durumlar tespit edilmektedir. Yapılan testlerde önerilen yöntemin %84,62 başarıyla sonuç verdiği gözlenmiştir.

Anahtar Kelimeler:

Anomali Tespiti, Bulanık Mantık, Akıllı Fabrika, Otonom Araç

FUZZY LOGIC BASED ANOMALY DETECTION FOR AUTONOMOUS TRANSPORT VEHICLES IN SMART FACTORIES

Digital transformation requires new data-oriented approaches in industry. In this context, it is expected that there will be significant digital transformation in the smart factories with Industry 4.0. One of the most important technologies that will contribute to digital transformation in smart factories is the autonomous transport vehicle (ATV). ATVs are expected to perform their tasks in the factory in an efficient manner. And it is also expected to detect an unexpected problem or any failure via the data without human intervention. This study aimed determining abnormal conditions of traffic network such as unexpected stop and deceleration by using fuzzy logic in the factory. The performed tests show that the proposed method results success (84.62%).

Keywords:

Anomaly Detection, Fuzzy Logic, Smart Factories, Autonomous Vehicle,

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