Latest version of 2022! A comprehensive disclosure of know-how that reduces the time for data-driven material development processes by 55%, which is being increasingly utilized in universities and aerospace research institutions.
The wave of digital transformation (DX) is finally beginning to impact the upstream research and development in the manufacturing industry value chain. How will AI change the research and development in manufacturing, where it is said that 70% of designs rely on the intuition and experience of veteran researchers? This report explains the background of data-driven material development, which is also being utilized in universities and aerospace research institutions, and provides hints on how to reduce process time in design and material selection by 55%. *For more details, please download the catalog for confirmation. *The 55% reduction in material development process time is based on estimates.
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■Contents - The Reality of Unrestricted DX and Research and Development Sites - Why is AI Utilization in Manufacturing Not Advancing? - Research and Development Transformed by Informatics - Innovations in the Field of Machine Manufacturing Driven by Informatics Technology - The Future of Mechanical Informatics
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Applications/Examples of results
- Aerospace Research Institutions Lightweight and strong carbon fiber composite materials are expanding their use in the aerospace sector. Analysis techniques utilizing machine learning technology are employed to understand their complex failure mechanisms. - Universities Fuel cell vehicles (FCVs) are gaining attention as next-generation mobility, but high-pressure hydrogen containers for storing hydrogen are very expensive. Optimal design techniques using neural network technology are utilized. - Metal Hose Manufacturers Fuel cell vehicles (FCVs) are gaining attention as next-generation mobility. Optimal design techniques using machine learning and inverse analysis technology are employed for flexible hoses used to fill hydrogen.
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Company information
SUPWAT provides services for research and development professionals in the manufacturing industry. Based on insights from mechanical engineering, we assess what could become a characteristic value, what to learn, and what outputs can be expected, all from a perspective that anticipates development and manufacturing, allowing us to propose machine learning solutions. We have many excellent members not only in mechanical engineering but also in machine learning, enabling us to consider suitable proposals for your company from various perspectives.
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