Design and Implementation of a Fault Inspection System for the Festo Modular Production System (MPS)

The rapid development of automation systems and the increased demand for efficient fault detection in manufacturing processes have led to the need for advanced fault detection systems. In this study, we present a novel fault detection system for the Festo MPS 500 system that provides an easier appro...

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Bibliographic Details
Published in:International Conference on Control, Automation and Systems (Online) pp. 706 - 711
Main Authors: Sagynbay, Alisultan, Balapan, Azat, Alizadeh, Tohid
Format: Conference Proceeding
Language:English
Published: ICROS 17.10.2023
Subjects:
Automation
communication
Fault detection
Fault diagnosis
Festo MPS 500
human-machine interface
image processing
Manufacturing
OpenCV
Pipelines
Process control
Production systems
Python algorithms
Siemens PLC
Snap7
ISSN:2642-3901
Online Access:Get full text
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Summary:The rapid development of automation systems and the increased demand for efficient fault detection in manufacturing processes have led to the need for advanced fault detection systems. In this study, we present a novel fault detection system for the Festo MPS 500 system that provides an easier approach of communication. The system implements a camera and Python algorithms for accurate and reliable detection of misaligned parts. An image processing pipeline is developed that includes ROI selection, rectangle detection, fixed point selection, distance calculation, and digital signal communication with PLCs. The system achieved a high level of accuracy in detecting misaligned parts, while establishing a seamless data exchange between PLCs using Python's Snap7 library. Moreover, the system utilizes a human-machine interface to display errors and monitor the production process. The results indicate that the proposed fault detection system offers a reliable and efficient solution to improve communication between PLCs and enhance manufacturing performance, by introducing the usage of a high level programming language.
ISSN:2642-3901
DOI:10.23919/ICCAS59377.2023.10316847