Mystkowski A.Karbay V.K.Mystkowska J.2024-03-132024-03-1320141507-2711https://hdl.handle.net/20.500.12662/3210This paper presents a method for improving the labelling process and a robust monitoring model for oving the labelling process and a robust monitoring model for the labelling machine with the purpose of reducing waste of labeombination of Matlab®-designed and hardware-in-the-loop (HIL) simulationas well as Arena Simulation. The method solves problems with the application of labels during the labelling stage and provides a robust monitoring algorithm that recognizes defective labels before they are stuck onto bottles. The Grafcet optimal algorithm for recognizing defective labels is executed. The Matlab®Stateflow model for monitoring and recognizing defective labels is applied. The proposed algorithms are complete, and optimized solutions are ready for implementation in the existing PLC supervisory control system. Based on HIL simulations, the proposed method ensures an increase of the total production quantity. Statistical data was collected directly from the field, classified using Statfit software, and used in Arena Simulation software to present the difference and benefits before and after using the PLC-based robust monitoring model for the labelling machine automation process.eninfo:eu-repo/semantics/closedAccessHIL simulationLabel defects detectionLabellingPLCRobust monitoring stateflow® modelArticle2-s2.0-849039879873903Q138316