製造業におけるカーボンフットプリント評価：方法論、限界、そしてMBD活用型デジタル枠組みの将来像

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:製造業CFP算定の方法論的限界とMBD連携という新たな研究アジェンダを整理する基礎文献として有用。

🏢実務担当者:製品CFP算定のばらつき要因を理解し、CAD/MBDデータとLCAを連携させた設計段階からの排出量把握の方向性を検討できる。

🏛政策担当者:製品単位炭素開示の比較可能性確保に向け、データ標準・相互運用性・検証要件の整備を検討する際の論点を提供する。

Manufacturing remains one of the largest contributors to global greenhouse gas (GHG) emissions, making accurate and comparable carbon-footprint (CFP) assessments essential for achieving net-zero and circular-economy goals. Over the past two decades, process-based Life Cycle Assessment (LCA), input-output analysis (IOA), hybrid approaches, and international standards such as ISO 14067:2018 and PAS 2050:2011 have shaped the field. Although each approach provides valuable insights, differences in data quality, system-boundary definitions, and allocation rules often produce inconsistent results, limiting their usefulness for policy and industrial decision-making. This structured scoping review synthesizes the current state of CFP methodologies in manufacturing, highlighting their strengths, limitations, and emerging developments, including dynamic and spatially resolved models. Relevant literature was identified through structured searches of Scopus, Web of Science Core Collection, Engineering Village/Compendex, and IEEE Xplore for publications issued between January 2000 and December 2025. Overall, the reviewed methodologies involve different trade-offs among product-level detail, supply chain coverage, data requirements, and temporal or spatial representativeness, and no single approach is suitable for all manufacturing applications. However, existing reviews have not sufficiently explained how recurring methodological limitations in manufacturing CFP assessment, particularly inconsistent system boundaries, allocation choices, data quality, uncertainty treatment, and fragmented product information, can be translated into specific digital information requirements for design-integrated assessment. Unlike previous reviews that examine CFP methodologies and digital-engineering technologies separately, this review connects the methodological requirements of manufacturing CFP assessment with the information structures provided by Model-Based Definition (MBD). On this basis, the review develops a future-oriented framework in which machine-readable product data, external environmental databases, and traceable assessment parameters could support partially automated and design-integrated CFP evaluation. Practical implementation nevertheless remains constrained by semantic misalignment between CAD/MBD and LCA data structures, reliance on proprietary environmental databases, limited interoperability among commercial tools, and data quality and version control requirements. AI-assisted EF estimation may help address data gaps but requires transparent validation and expert oversight. MBD is therefore positioned not as a replacement for established LCA methods, but as an enabling information structure whose implementation and industrial validation remain areas for future research.

• openalex https://doi.org/10.1016/j.clet.2026.101325first seen 2026-09-24 04:45:08