Optimizing Industry 4.0 by Implementation of an Advanced Bottle Filling Plant with RFID, and CNN Technology

Industry 4.0 is an essential concept that has been demonstrated to increase factory production efficiencies. Industry 4.0's primary component is the digitalization of the production process, which makes use of increasingly sophisticated technologies like cloud computing, the Internet of things, industrial Internet of things, and many more. It describes the implementation of a benchmark Industry 4.0 facility that simulates a bottle filling plant and uses all of the cutting-edge technology required for an Industry 4.0 plant. The RFID tag and OTP verification are used for the authentication of the user at the entrance of the Bottle filling plants. It detects the height of the bottle, and the liquid presence using color segmentation. The YOLOv4 and ArUco markers detect the object and height of the bottle. The CNN model is used to categorize the caps in three categories which are intact, damaged and missing. This study is novel because it combines Industry 4.0 technologies like RFID tags, YOLOv4, and ArUco markers with CNN-based defect classification to provide an all-encompassing, automated quality control system for bottle filling factories. This technique ensures strong authentication and security while improving the precision of flaw detection, revolutionizing industrial processes. With sensitivity at 1.0000 and specificity at 0.7500, the system successfully identifies, detects, and classifies bottle cap faults, achieving an accuracy of 83.33% for the CNN model. The study offers possibilities for additional advancements in efficiency, safety, and fault discovery by proving that this technology can be implemented in actual industrial settings.