A Modular Smart Vision System for Industrial Inspection and Control of Conformity
Marwan El Heloua b, Khaled Benfrihac d, Abdulrahman M. Al-Ahmarie f, Peter Wardleg h, Esma Talhii j, Stéphane Loubèrek l, Chawki El Zantc d, Quentin Charrierc d
- aArts & Métiers Institute of Technology, Product Design and Innovation Laboratory, HESAM University 1 , 151 Bd de l’Hôpital, 75013 Paris
- bArts & Métiers Institute of Technology, Product Design and Innovation Laboratory, HESAM University 1 , 151 Bd de l’Hôpital, 75013Paris, France (Corresponding author), e-mail: marwan.el_helou@ensam.eu , ORCID link for author moved to before name tags https://orcid.org/0000-0002-0019-7371
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Abstract
ABSTRACT In manufacturing systems, there are several essential tasks to perform before and after the production process. In traditional systems, these tasks were done manually, which can lead to more resource consumption and the risk of human error; however, advanced manufacturing systems and Industry 4.0 tend toward a more autonomous manner. To ensure the compliance of the machining process and the safety of the personnel as well as the machines at the shop floor, the inspection of the overall factory prior to any machining process and the control of conformity of the manufactured parts are necessary in order to know the status of the manufacturing line. This paper proposes a novel modular smart vision system for machine inspection and conformity control of machined parts. Our system uses smart vision technologies embedded in industrial robots and enhanced with image processing and analysis capabilities. The solution also integrates a user interface for human–machine interactions that has been developed with a modular approach, and is designed, launched, and controlled by the manufacturing execution system, allowing agile and customized configuration. By this new approach, the robot inspects all the machines in the factory to check the status before launching the production plan. After the machining process, the system interprets the in situ dimensional analysis for the machined parts and makes decisions about whether the parts are acceptable or require additional machining.

