Anhui Keye Intelligent Technology Co., Ltd

PET Preform AI Visual Inspection System conducts visual defect detection on water, beverage, oil and other preforms via a systematic workflow: image capture, intelligent image processing, automated annotation, advanced AI algorithm modeling, and software coordination. It instantly rejects non-conforming products, automatically counts qualified units, and supports batch box division for streamlined production.     What product can be inspected? PET Preform - water preform, beverage preform, oil preform, etc. Defects Detection   11 Cameras Solution (customizable)   7 cameras solution: 1 for top mouth, 1 for bottom, 1 for supporting ring, 4 for body sidewall. 11 cameras solution: 1 for top mouth, 1 for bottom, 1 for supporting ring, 1 for injection gate, 4 for neck thread, 4 for body sidewall. More customized solution available. Required Information Before Quotation 1.Integration method: offline/in-line inspection 口 Offline inspection: The inspection is separated from production line (preform feeder + inspection machine). Please advise production capacity. 口 In-line inspection: the preforms feeder connects to your production line, then enter inspection machine. Please advise line speed. 2. Preforms Size Info: diameter, height, weight for each. 3. Inspection speed: determined by your production capacity/line speed. Inspection Theory Inspection process of Keye Tech vision inspection system to detect appearance defects: Feeding device: Products transfer to a workstation via feeding devices, entering the inspection machine orderly one by one. Image acquisition: High-pixel images are captured by customized system of self-developed industrial cameras and LED light sources. Image processing: Captured images upload to our self-developed KVIS COULD AI Platform for few image annotation and model training(within 1h). AI algorithm models: AI algorithms analyze the processed images, sort products into "NG" (defective) and "OK" (qualified), and trigger inline rejection of defective products via pneumatic devices. Software scheduling: The software provides sample comparison standards, allowing customers to select the most suitable criteria to balance accuracy and defect rates. Counting and box division: Defective products are instantly rejected into a separate box. Good products are counted for box division.

Machine Vision Inspection is a technology based on image processing that is used to automate inspection processes in production lines in various manufacturing industries. Basically, it allows a computer to inspect and evaluate product quality using industrial cameras, lights, and computer vision software.   Machine vision automates specific industrial tasks like defect detection, assembly guidance, and barcode scanning, making processes faster and more cost-effective. 2. Computer vision uses AI to analyze visual data, supporting applications like facial recognition, healthcare diagnostics, and customer behavior analysis.   When computer scientists working in computer science disciplines that involve images, such as computer graphics, image processing, and computer vision, noticed that their methods and applications increasingly overlapped, they began using the term "visual computing" to describe these fields collectively.

Overview. The visual inspection machines capture high-definition images of semiconductor products and transparent objects such as glass and perform the measurements for scratches, particulates and debris, chipping, color unevenness, dimensions of devices and so forth through the image processing technology.   These systems use optic lenses, sensors, and artificial intelligence technology to detect flaws, defects, and irregularities in your products. Essentially, vision inspection systems compare manufactured products to images of what the product should look like, identifying discrepancies between the two.   The purpose of an inspection is to identify whether work equipment can be operated, adjusted and maintained safely, with any deterioration detected and remedied before it results in a health and safety risk.   Principles of Visual Inspection. The fundamental principle of visual inspection is based on the detection of surface anomalies through direct observation. Inspectors clean the surface of the material or asset they're going to inspect to remove any contaminants such as dirt, grease, or paint that could obscure defects.