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Utilizing the Industrial Metaverse for Manufacturing’s Digital Transformation

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インダストリアルメタバースが切り開く未来―デジタルトランスフォーメーションによる次世代工場の実現

In reference to digital manufacturing, Mr. Naoki Okuyama from Ricoh’s Digital Strategy Department stated, “We have discovered that the future production sites will fall into two main categories: ‘automation’ or ‘human-robot collaboration.’ For instance, mass production like smartphone manufacturing in China leans towards automation and ‘unmanned’ operations, which are cost-effective. On the other hand, Ricoh’s production in Japan involves small-run, multi-variety production that demands flexibility in processes. However, equipment offering this flexibility is complex to operate and maintain, often not meeting ROI expectations. Despite the need for human workers at domestic sites for production flexibility, concerns arise about human errors, declining birth rates, and an aging population. This has led us to create a more worker-friendly production environment with collaborative robots.”

Data infrastructure:

Digital twins work alongside real-time data to create a framework for data collection, processing, storage, and security. Information from physical devices is gathered, processed using sensors and AI, and converted into useful data. Governance structures are in place for data maintenance, access control, and security to build reliable digital twins for simulations and analyses. Mr. Taiki Saito from Ricoh Industries Co., Ltd.’s Printer Production Division highlighted the importance of collecting human-related data naturally to maintain workflow integrity.

Technical skills and training:

The success of digital twins relies on personnel with specialized technical skills including data analysis, modeling, programming, and other specific technologies. Training is crucial to maximize employee potential. Ricoh Industry Co., Ltd. has implemented a unique training initiative involving virtual recreation of workspaces for employees to better understand processes. This immersive experience has improved work efficiency and accelerated skill acquisition, ultimately enhancing overall work efficiency.

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