NTT DATA, along with NTT COMWARE Corporation, ITOCHU Techno-Solutions Corporation (CTC), and Mitsubishi Chemical Group Corporation (MCG) have collaborated to reduce the workload of, and improve the conditions for, workers inspecting factory facilities.
The experiment spanned 120 kilometers between Odaiba and Gotanda, Tokyo, demonstrating the feasibility of remote anomaly detection using an AI analysis. Hidehiko Tanaka, Head of Technology and Innovation at NTT DATA, noted that the convergence of robotics and AI will “greatly contribute to reducing human workload in all industries.”
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IOWN APN for Smart Maintenance
The project leveraged the IOWN All-Photonics Network (APN) and AI technologies to enable smart maintenance using remote-controlled robots and AI-powered video analysis. “ITOCHU Techno-Solutions is dedicated to contributing to developing a new and unprecedented society through the IOWN concept," emphasized Mitsuo Nishimoto, General Manager, Telecommunication Division No.1, ITOCHU Techno-Solutions.
The robots successfully detected cracks in pipes and analyzed pipe vibrations in real time, meeting high latency and image quality standards. "We aim to further implement other technologies such as remote predictive detection for cracks," added Wataru Imazato, Executive Vice President, Senior Vice President of Network and Cloud Division, NTT COMWARE. Using this data and insight, the entities aim to create a system that provides accurate and real-time information about factory environments. Multiple robots and devices will gather environmental data like video and sound and will conduct multimodal AI analyses.
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Regular inspections are crucial for maintaining factories, however, they can be time-consuming and risky for workers, especially in large facilities or at significant heights. To address this, the project utilized the IOWN APN to ensure high-speed, low-latency communication, enabling the robots to patrol remotely and detect anomalies in pipes using real-time video.
"Reducing the burden on on-site workers tasked with inspecting factory facilities is a problem faced not only by chemical manufacturers, but by all manufacturers. This result is the first step toward a new way of ‘monozukuri’ based on the IOWN APN,” highlighted Toshiya Katsuragi, Senior Vice President, Chief Technology Officer, Mitsubishi Chemical Group.
Moving forward, the companies plan to enhance remote robot control, data analysis, and video transmission capabilities. They aim to create a world where remote sites can be assessed accurately and in real time, reducing the workload of inspection personnel and improving safety during high-risk tasks. Discussions will continue through the IOWN Global Forum, with plans to establish a communication environment at a Mitsubishi Chemical Group manufacturing site for further verification experiments on anomaly detection using robots and AI analysis.
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