Reduced man-hours associated with research and development experiments by 55%! Revealing the secrets of data-driven material development.
The chemical industry is increasingly focusing on Materials Informatics (MI), and the number of companies and researchers incorporating MI into their development processes is gradually rising. MI refers to the attempt to utilize digital technologies in product design within process-based manufacturing industries like the chemical sector. Advances in digital technologies such as big data, AI, and machine learning make it possible to analyze vast amounts of experiments and papers to predict material formulations, thereby improving the efficiency of material development. This report discusses the latest trends in the further utilization of AI beyond the realms of Materials Informatics (MI) and product formulation. It also includes case studies from major companies that have already begun initiatives in MI, such as Asahi Kasei, Sumitomo Chemical, Toray, and Yokohama Rubber. *The 55% reduction in man-hours associated with experiments is based on estimates.
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■Publication Content 01. Visualization of Urgently Needed Research Know-How 02. Attention on MI 03. Another AI Learning Approach Beyond the MI Domain 04. Introduction of the AI Machine Learning SaaS Platform "WALL"
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<Initiatives of Major Companies in MI - Excerpts> - Asahi Kasei In its mid-term management plan announced in 2019, the company stated its intention to strengthen MI as part of its "Digital Transformation." An "Informatics Promotion Center" was established within the Research and Development Headquarters. By the end of fiscal year 2021, the organization was strengthened to include over 150 digital professionals. MI is utilized in almost all material development, and efforts are being made to permeate not only research and development but also the field level, including sales. - Toray The company is promoting the efficiency of research and development through simulations and MI, utilizing theoretical calculations and data science, under the theme of "Advanced Materials Research through Digital Manufacturing."
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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.