Konica Minolta and AIST Develop AI-based Technology to Optimize the Conditions for Compounding and Molding Composite Plastics

On March 13, 2026, Konica Minolta, Inc. and the research group of National Institute of Advanced Industrial Science and Technology (AIST), Shun Muroga, Senior Researcher, Daisuke Kimura, Researcher and Kenji Hata, Director of the Nanocarbon Material Research Institute, today announced that they have developed an AI-based technology to optimize the conditions for mixing and molding composite plastics.

This technology was made possible by combining core technologies developed by Konica Minolta and AIST. By building an AI model that can make predictions using only a small amount of data, the technology helps ensure the consistent quality of molded plastic products.

The technology will be applied to measurement solutions that harness Konica Minolta’s sensing technology as well as process monitoring for intelligent recycled materials and biomanufacturing, which are the seeds for future growth, namely, priority themes in the medium to long term. Details of the research results will be presented at the 73rd Japan Society of Applied Physics (JSAP) Spring Meeting on March 15, 2026.

In recent years, there are high expectations for utilizing biomass-derived plastics and recycled plastics for resource circulation. However, these plastics require additional work to adjust the mixing and molding conditions compared to petroleum-derived plastics due mainly to variable quality caused by the raw materials, chemical decomposition during mixing, and molding defects.

To address this challenge for the sake of green transformation (GX), Konica Minolta and AIST have conducted research on predicting the mixing and molding conditions of composite plastics by using AI. Konica Minolta and AIST aimed to develop an AI technology suitable for composite plastics by combining their core technologies and utilizing them for materials informatics (MI) and process informatics (PI) based on measurement solutions that leverage sensing technology developed by Konica Minolta over many years, and multimodal AI† and autonomous experimentation†† technology refined by AIST.

In the latest research, Konica Minolta and AIST built multimodal AI models that can predict the optimal mixing and molding conditions for manufacturing molded plastic products with desired physical properties by determining the mixing ratio of plastic types and additives, measuring the mixing and molding quality, and performing proprietary data processing.

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