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Energy-based key performance indicator for energy-intensive manufacturing processes: Application to steel casting

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  • Kim, Sung-il
  • Joo, Younghwan

Abstract

To enhance the energy efficiency of manufacturing processes, a quantitative assessment of inefficiency is essential. Key performance indicators (KPIs) serve as a crucial tool for this purpose. However, many existing indicators predominantly focus on macroscopic performance evaluation, limiting their use at the granular level of workplaces. In this study, an energy-related KPI is introduced that is designed to quantitatively assess specific inefficiency factors in manufacturing processes, integrating overall process and facility energy conversion efficiency perspectives. This approach compares the total energy consumption across different manufacturing states and analyzes the statistical distribution of energy consumption and time required for each event to identify patterns that diminish overall process energy efficiency. The proposed KPI theory, which was validated using data from a steel casting process, reveals that mitigating energy losses due to process delays and idle times can lead to a potential 7.2 % enhancement in facility energy efficiency. This technique offers insights, effectively bridging the gap between theoretical energy efficiency evaluation and its practical implementation, underscoring the importance of optimizing idle time management for substantial efficiency improvements.

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  • Kim, Sung-il & Joo, Younghwan, 2025. "Energy-based key performance indicator for energy-intensive manufacturing processes: Application to steel casting," Energy, Elsevier, vol. 317(C).
    • Handle: RePEc:eee:energy:v:317:y:2025:i:c:s0360544225001859
    DOI: 10.1016/j.energy.2025.134543
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    1. Crescenzo Pepe & Giorgia Farella & Giovanni Bartucci & Silvia Maria Zanoli, 2025. "Recent Innovations in Computer and Automation Engineering for Performance Improvement in the Steel Industry Production Chain: A Review," Energies, MDPI, vol. 18(8), pages 1-41, April.

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