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2024 April 2   13:41

Wall-mounted robot for ship inspection and maintenance receives ClassNK innovation approval

Mitsui O.S.K. Lines, Ltd. (MOL), Sumitomo Heavy Industries, Ltd. (SHI), and MOL Ship Management Co., Ltd. (MOLSHIP) today announced that their jointly developed wall climbing robot for steel structures—intended to support ship inspection and maintenance work—has completed a demonstration test and earned the Nippon Kaiji Kyokai (ClassNK) "Innovation Endorsement Certification," as a framework to support innovative initiatives.

The Innovation Endorsement is ClassNK's third-party certification program. It certifies and supports initiatives that contribute to the sustainable evolution of maritime and offshore businesses. 

This robot is characterized by its high traversability not only on vertical walls but also on curved surfaces and unevenness. It can move to high places that were previously difficult to access by humans or robots, and can take clear photographs and inspections of the relevant parts. Moreover, it is capable of measuring the thickness of steel plates by remote operation by the operator, and its measurement accuracy is as high as 0.01mm. This not only avoids the dangers of working at heights, but also eliminates the need for scaffolding, reducing labor costs and scaffolding costs. Furthermore, it can also work in confined spaces, eliminating the risk of oxygen deficiency for the crew. 

This innovative robot performance and technology, as well as its innovative functions for ship inspection, have been recognized, and it has obtained the Innovation Endorsement certification from ClassNK in the "Product & Solution" category, which targets products and systems that apply advanced initiatives.

Following the success of this demonstration test, MOL and MOLSHIP aim to further develop their ship operation and management technology, as well as SHIs' robot development and manufacturing technology. They also aim to enhance the performance and functionality of robots and pursue digital transformation using detailed data obtained from robots.

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