Construction Material Flow Intelligence (CMFI): A Project-Level Framework Integrating Material Stocks, Waste Flows, and Decision Support for Sustainable Building Delivery
建設材料フローインテリジェンス（CMFI）：持続可能な建築提供のための材料ストック、廃棄物フロー、意思決定支援を統合したプロジェクトレベル枠組み (AI 翻訳)
N. Albelwi
🤖 gxceed AI 要約
日本語
建設プロジェクトの材料廃棄物と体化炭素損失を削減するため、CMFIという意思決定支援枠組みを提案。標準的な調達・納品・設置・廃棄記録を6つの性能指標と運用シグナルに変換する。5階建て商業ビルの例では、約27.2 tCO2eの回避可能な体化炭素損失を特定。廃棄物分類、段階追跡、体化炭素統合が重要要素とされる。
English
This paper proposes CMFI, a decision-support framework for construction projects that converts routine documentation into performance indicators and operational signals to reduce material waste and embodied carbon. An illustrative case of a five-storey commercial building identifies about 27.2 tCO2e of avoidable embodied carbon loss. Sensitivity analysis highlights waste classification, stage tracking, and embodied carbon integration as key components.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本の建設業界では、建設廃棄物の削減と脱炭素が急務であり、本枠組みはプロジェクト段階での材料管理を改善し、SSBJや環境報告に対応するデータ基盤となり得る。
In the global GX context
Globally, the framework addresses the gap between aggregate material flow analysis and project-level management, offering a scalable approach to reduce embodied carbon in construction, aligning with ISSB and CSRD disclosure requirements.
👥 読者別の含意
🔬研究者:Provides a novel framework for project-level material flow analysis that can be empirically validated and extended.
🏢実務担当者:Offers a practical method to identify waste reduction and embodied carbon savings from existing project data.
🏛政策担当者:Highlights the potential for policy to encourage adoption of such frameworks to meet construction sector decarbonization targets.
📄 Abstract（原文）
Construction projects generate substantial material waste and embodied carbon losses, yet no integrating framework currently transforms routine project documentation into stage-specific decision signals during building delivery. This paper proposes Construction Material Flow Intelligence (CMFI), a project-level decision-support framework that applies mass-balance principles within a four-layer processing architecture to convert standard procurement records, delivery logs, installation data, and waste records into six performance indicators and structured operational signals. CMFI operates at the project-stage-material scale and produces three classes of output: procurement-adjustment signals, waste reduction triggers, and storage optimisation recommendations. An illustrative application to a five-storey commercial building across five material categories and three construction stages demonstrates that CMFI generates seven decision signals and identifies approximately 27.2 tCO2e of avoidable embodied carbon loss from routine project documentation, without bespoke sensing infrastructure. Component sensitivity analysis confirms that waste classification, stage-based tracking, and embodied carbon integration are each load-bearing elements of the framework. CMFI addresses the gap between aggregate material flow analysis and project-level operational management by shifting construction material monitoring from retrospective waste reporting to stage-resolved sustainability intelligence. Limitations include the use of illustrative rather than empirical data, single-period stage accounting, and uncalibrated trigger thresholds; empirical validation and digital implementation are identified as priority future directions.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/su18168262first seen 2026-08-15 05:30:22 · last seen 2026-08-16 05:42:37
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