CMC Research to Publish Report on Next-Generation Digital Twins and 30 Key Vendors and Research Institutions on May 18, 2026

CMC Research will publish “Implementation of Next-Generation Digital Twins and 30 Key Players: The Ecosystem Bridging Manufacturing, Energy, and Physical AI” on May 18, 2026. The report covers the integration of physical models and AI, practical implementation of PINNs, autonomous CPS optimization, digital twins for manufacturing processes, materials informatics, and energy optimization. The report argues that Japan’s manufacturing, materials, and device industries are facing structural risks as skilled expertise and process know-how, traditionally treated as sources of competitiveness, become increasingly difficult to sustain. As a solution, it presents next-generation digital twins that convert tacit knowledge into reproducible, computable digital assets by structuring multilayer data such as material properties, process conditions, equipment behavior, and energy consumption. From a technical perspective, digital twins are evolving from visualization tools into decision-making engines. Conventional data-driven AI and surrogate models are effective at learning correlations from observed data, but they have inherent limits in extrapolation areas and physics-constrained problems. Hybrid modeling that combines physical models with AI, particularly Physics-Informed Neural Networks (PINNs), embeds physical laws as constraints and enables physically consistent predictions even in data-scarce domains. This reduces dependence on experiments and prototypes while enabling optimal conditions to be derived in advance. The report highlights applications in complex, multiscale, and highly nonlinear processes such as battery electrode coating and drying, semiconductor atomic layer deposition, and continuous-flow chemical synthesis. Hybrid models can reduce the effective dimensionality of parameter spaces, improve sensitivity analysis, lower uncertainty during scale-up, and accelerate vertical ramp-up from laboratory conditions to mass production lines. The competitive focus is also expanding from manufacturing optimization alone to integrated optimization that includes energy systems. With regulatory developments such as Europe’s Digital Product Passport and Carbon Border Adjustment Mechanism, product-level environmental impact management is becoming mandatory. Energy-linked digital twins that integrate manufacturing processes and energy consumption are expected to become standard, requiring dynamic optimization across factories, data centers, and battery systems. For data centers, liquid cooling control, load balancing, and PUE improvement are positioned as practical priorities for optimizing total cost of ownership and reducing levelized cost of storage. The report is A4 format, paperback, 123 pages, priced at JPY 99,000 including tax. A book and PDF CD set is priced at JPY 165,000 including tax. ISBN: 978-4-910581-88-0. Edited and published by CMC Research. Major sections cover the digital assetization of tacit knowledge and Japan’s structural industrial risks, data quality and data silo mitigation, linkage between materials informatics and manufacturing, sensing and data acquisition, PINNs construction and implementation, autonomous CPS optimization, analysis of 30 major companies and research institutions, autonomous digital twins for batteries, semiconductors, and chemical processes, and energy-linked optimization for factories and data centers.