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Quality control in industry involves trained operators to manipulate and inspect metallic surfaces in order to identify, and eventually correct, manufacturing defects. These tasks are manually performed, and a poor performance ( e.g. , missing defects) leads to an increase of the costs and prolongation of the manufacturing time cycle. In this work, we propose a multi-agent robotic platform to autonomously perform Industry 4.0 quality control processes of metallic surfaces. The platform consists of three anthropomorphic robots with custom-made end-effectors designed to manipulate, inspect, and eventually correct a metallic frame of a motorcycle. The description of a novel multi-agent platform is followed by the presentation of the developed inspection procedure, in which a linear laser scanner is used to reconstruct the three-dimensional metallic surface of a motorcycle with a resolution of ~0.1 mm. In order to validate the platform, we perform a set of experiments to assess the performance of the robotic platform in a real Industry 4.0 scenario. Results confirmed that such a system guarantees a sub-millimetric precision to identify defects on complex-shaped metallic surfaces and effectively correct them. The proposed robotic platform can be adopted for overcoming the drawbacks of a traditional procedure that relies on visual-tactile manual defects correction ( e.g. , low-repeatability, high-subjectivity) and is scalable to different industrial applications. The proposed approach aims to elevate the role of operators to expert supervisors of the process, limiting the interactions with potentially-dangerous tools/procedures and thus improving the working conditions in an industrial 4.0 scenario. Note to Practitioners —This work was motivated by a crucial need in industry, i.e. to automatize the manufacturing quality control, translating the commonly-used visual-based manual approach performed by operators to an objective robotic one that relies on defect detection by using a linear laser scanner. A novel multi-agent robotic platform, developed by the authors, showed its effectiveness in automatizing complex tasks, in which huge workspace and different tools are required. The aim of the paper was to develop a fully automatized application that covers the entire quality control process, while focusing on one specific phase, i.e. automatic inspection. The integrated software and the infrastructural communication protocols of the entire robotic platform were designed to be flexible in order to realize a new reference for industrial applications, where a multi-agent approach is demanded. The experimental validation focused on a specific use case (a motorcycle frame selected due to its complex structure, i.e. multiple curvatures with variable radii, and large volumes), but the proposed platform and the implemented methodology have to be intended as a general purpose approach, adaptable to any industrial process and mechanical component. The authors, starting by a laboratory development with extensive tests, applied and demonstrated the feasibility of the proposed approach in a real Industry 4.0 scenario.
Czimmermann et al. (Tue,) studied this question.