We are currently offering a case study on the efficiency improvement of the product development process using AI predictions!
Cloud-based materials informatics platform "Polymerize"
Introducing a case study of successful efficiency and shortening in the development of high-performance elastomer seals using AI predictions, with a focus on minimizing the processes necessary to achieve development goals.
The cloud-based materials informatics platform "Polymerize" is equipped with unique data processing capabilities, allowing it to import spreadsheet data in any format, making it easy to implement. It features centralized data management and predictive capabilities powered by proprietary AI algorithms, enabling users to obtain suggestions, analyses, and insights related to experiments to achieve development goals. 【Features】 ■ Project management ■ Analysis of past experimental data ■ Data management ■ Experimental design ■ Result prediction using AI engines *For more details, please download the PDF (case study materials) or feel free to contact us.
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basic information
【Main Achievements】 ■Reduced man-hours by 50% compared to the trial-and-error development process ■Discovered insights on suitable material combinations and formulations that can be utilized for future product development ■Significantly improved functionality of the final product *For more details, please refer to the PDF document or feel free to contact us.
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For more details, please refer to the PDF document or feel free to contact us.
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Our company provides a materials informatics platform, PolymerizeLabs, and consulting services for the chemical and materials industries. PolymerizeLabs reflects the unique R&D processes and expertise specific to materials development, enabling seamless data management and AI utilization without the need for programming knowledge. It is the only all-in-one materials informatics platform in the industry that ensures AI prediction accuracy even with limited or sparse data. Based on a data management infrastructure specialized in organizing various materials development data and a highly flexible AI engine equipped with a diverse range of machine learning algorithms, we offer data-driven development processes across various materials fields. We contribute to addressing resource shortages, high cost structures, compliance with environmental regulations, alleviating supply chain bottlenecks, and responding quickly to market changes faced by all R&D departments, thereby enhancing corporate competitiveness and establishing a new standard for R&D processes in the AI era.
