Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Jurnal Teknik Indonesia (JU-TI)
Udu Chukwudi Emeka
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Carbon Accounting at the Shop-Floor: The Integration of Real-Time Energy Monitoring, Process Modeling and LCA for Net-Zero Targets Chukwumuanya Emmanuel Okechukwu; Okpala Charles Chikwendu; Udu Chukwudi Emeka
Jurnal Teknik Indonesia Vol. 4 No. 01 (2025): Jurnal Teknik Indonesia (JU-TI) 2025
Publisher : SEAN Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Achieving net-zero emissions in manufacturing requires operational-level methods that are capable of capturing energy use and carbon intensity with high resolution. Traditional carbon accounting and Life Cycle Assessment (LCA) approaches often lack the temporal granularity required to guide shop-floor decisions. This study introduces a framework that integrates real-time energy monitoring, process modeling, and dynamic LCA to support decarbonization strategies in production environments. The framework was applied to three case studies: CNC machining, injection molding, and additive manufacturing. Results showed that non-productive energy accounted for 18–35% of total consumption, but targeted optimization reduced energy use by 12–23% and emissions by 10–23%. Dynamic LCA improved accuracy, lowering uncertainty by 14–16% compared to static methods. These findings demonstrate that shop-floor-focused carbon accounting can directly contribute to net-zero targets by linking real-time data with sustainability outcomes. The framework not only provides immediate efficiency gains, but also advances Industry 4.0 by embedding carbon intelligence into digital manufacturing systems. Future research should extend validation to energy-intensive sectors and explore integration with digital twins for comprehensive decision support
Co-Authors Chukwumuanya Emmanuel Okechukwu Okpala Charles Chikwendu