AI Summary & Key Takeaways
AI InsightTotally it was tried by 150 times for 50 pieces of leather in 5 different templates and these pieces felt into the required basket correctly by discriminating for faulty/faultiness ones by 149 times (99,33% success ratio).
📌 3 Key Takeaways
Abstract
At present, the audits about the cutting error of textile products (leather, fabric, etc.) are made by the human by the eye via the template. Making these audits that necessitate accurate measurement by eye both takes so much time and enhance the risk occurrence risk. In this article, the image processing based industrial quality control system that determines the cutting errors of textile products automatically and discriminates between faulty and faultless products is explained. The system minimizes the faults based upon the human auditing and increases the number of pieces that are controlled by the unit of time. The performed system is composed of Panel PC, line scan camera, system of conveyor, basket control unit, image processing software and control user interface. The textile pieces (cuts) to be inspected come into the part by the conveyor where the camera and illumination unit are available, and the image is captured. This captured image is sent to the Panel PC and controlled whether there is a cutting error via image processing software. According to the result of the audit, the basket system at the end of the conveyor (conveyor belt) moves back and forth on wheel rail, and the textile pieces are provided to fall into the required basket. The performed system was tested on the leather pieces that were taken from a company in the leather sector. Totally it was tried by 150 times for 50 pieces of leather in 5 different templates and these pieces felt into the required basket correctly by discriminating for faulty/faultiness ones by 149 times (99,33% success ratio).
Özet
Günümüzde tekstil (deri, kuma ş vb.) ürünleri kesim hatalar ı ile ilgili denetimler ş ablon vas ı tas ı yla insan taraf ı ndan gözle yap ı lmaktad ı r. Hassas ölçüm gerektiren bu denetimlerin gözle yap ı lmas ı , hem çok uzun zaman almakta hem de hata olu ş ma riskini art ı rmaktad ı r. Bu makalede tekstil parçalar ı n ı n kesim hatalar ı n ı otomatik olarak tespit eden ve hatal ı /hatas ı z parça ayr ı m ı yapabilen görüntü i ş leme tabanl ı endüstriyel kalite kontrol sistemi anlat ı lm ı ş t ı r. Sistem insan denetiminden kaynaklanan hatay ı en aza indirmekte ve birim zamanda kontrol edilen parça say ı s ı n ı art ı rmaktad ı r. Gerçekle ş tirilen sistem, Panel PC, çizgi tarama kameras ı , yürüyen bant sistemi, sepet kontrol ünitesi, görüntü i ş leme yaz ı l ı m ı ve kullan ı c ı kontrol ara yüzünden olu ş maktad ı r. Denetimi yap ı lacak kesilmi ş tekstil parçalar ı yürüyen bant üzerinde kamera ve ayd ı nlatma ünitesinin bulundu ğ u k ı sma gelir ve görüntü yakalan ı r. Yakalanan görüntü Panel PC’ye gönderilir ve görüntü i ş leme yaz ı l ı m ı vas ı tas ı yla kesim hatas ı olup olmad ı ğ ı denetlenir. Denetim sonucuna göre yürüyen band ı n sonunda yer alan sepet sistemi, pnömatik olarak ileri/geri hareket ettirilerek parçan ı n istenen sepete dü ş mesi sa ğ lan ı r. 5 farkl ı ş ablona sahip 50 adet deri parças ı için yap ı lan 150 denemeden 149 unda (%99.33 ba ş ar ı oran ı ) do ğ ru olarak hatal ı /hatas ı z ayr ı m ı yap ı larak belirlenen sepete otomatik olarak dü ş ürüldü ğ ü görülmü ş tür.