Designing a System Architecture for Automated Product Carbon Footprint Calculation in Production Lines
生産ラインにおける製品カーボンフットプリント自動計算のためのシステムアーキテクチャ設計 (AI 翻訳)
Steffen Wurm, Adrian Kasner, Oliver Petrović, Werner Herfs
🤖 gxceed AI 要約
日本語
本論文は、製造現場での製品カーボンフットプリント（PCF）自動計算のためのモジュール型システムアーキテクチャを提案する。アセット管理シェル（AAS）をデジタルツインとして活用し、データ収集から統合、PCFアプリケーションまでの4層構造を設計。シミュレーションと実地検証により、中小企業でも導入可能なスケーラブルな参照アーキテクチャを示した。
English
This paper proposes a modular system architecture for automated Product Carbon Footprint (PCF) calculation in manufacturing, using the Asset Administration Shell (AAS) as a digital twin. It defines four functional layers (Sources, Network, Data Integration, PCF Applications) and validates via simulation and an application-oriented study in discrete manufacturing, offering a scalable reference for transparent and sustainable production.
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
日本ではSSBJ開示やサプライチェーン排出量算定が進む中、中小企業のPCF算定負担が課題。本アーキテクチャはAASを活用した自動化で、日本企業のScope 3対応や効率的なデータ収集に貢献し得る。
In the global GX context
Globally, this addresses the challenge of PCF data integration for SMEs under regulatory pressure (e.g., CSRD, EU CBAM). The AAS-based digital twin approach aligns with Industry 4.0 and interoperability standards, offering a scalable reference for transparent emissions reporting.
👥 読者別の含意
🔬研究者:Provides a reference architecture for automated PCF calculation, useful for researchers in carbon accounting and digital twin integration.
🏢実務担当者:Offers a practical blueprint for manufacturing firms, especially SMEs, to automate PCF data collection and reporting.
🏛政策担当者:Highlights the need for interoperability standards and digital infrastructure to support SME compliance with emissions reporting.
📄 Abstract（原文）
This paper presents a system architecture for the automated calculation of Product Carbon Footprints (PCF) in industrial production environments. The motivation arises from the need for sustainability, reinforced by regulatory pressure and the growing demand for transparent, data-based reporting of product-related emissions. While Life Cycle Assessments (LCA) provide a methodological basis for PCF analysis, many companies, particularly small and medium sized enterprises (SMEs), struggle to access and integrate PCF relevant data from heterogeneous systems. To address this, we propose a modular architecture for continuous acquisition, integration, and processing of operational data. At its core, the Asset Administration Shell (AAS) serves as the digital twin of the product, enabling dynamic assignment and aggregation of emissions. The architecture consists of four functional layers: Sources, Network, Data Integration, and PCF Applications. Validation comprised a simulation and an application oriented study in discrete manufacturing. The simulation focused on testing real time data acquisition and processing through industrial communication protocols and the AAS model, while the application oriented validation examined the feasibility of deploying the architecture in practice. The study provides a scalable reference architecture for automated PCF determination and underlines how digital twins and interoperability standards enable transparent and sustainable manufacturing.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.procir.2026.05.021first seen 2026-08-02 17:20:32
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