Cloud manufacturing integrates cloud computing technologies with traditional manufacturing processes, improving operational efficiency and flexibility. However, it also increases the demand for energy, especially in data centres, which exacerbates the environmental impact. To address this issue, this research work presents a framework suitable for identifying, characterising, and managing energy inefficiencies in digital infrastructures. The framework includes energy data collection, inefficiency characterisation, root cause analysis and implementation of a targeted solution. By focusing on key factors such as server utilisation, data management and resource allocation, the proposed methodology aims to contribute reducing energy consumption, operational costs and CO₂ emissions. The iterative approach proposed in the framework could enable continuous improvement and adaptation, promoting sustainable cloud manufacturing in digital infrastructure environments.

Energy efficiency in digital infrastructures: a framework towards a sustainable cloud manufacturing / Simeone, Alessandro; Caggiano, Alessandra; Melone, Maria; Muraro, Simone; Priarone, Paolo C.; Settineri, Luca. - 138:(2026), pp. 921-926. ( 18th CIRP International Conference on Intelligent Computation in Manufacturing Engineering, CIRP ICME 2024 Italia 2024) [10.1016/j.procir.2026.01.159].

Energy efficiency in digital infrastructures: a framework towards a sustainable cloud manufacturing

Simeone, Alessandro;Muraro, Simone;Priarone, Paolo C.;Settineri, Luca
2026

Abstract

Cloud manufacturing integrates cloud computing technologies with traditional manufacturing processes, improving operational efficiency and flexibility. However, it also increases the demand for energy, especially in data centres, which exacerbates the environmental impact. To address this issue, this research work presents a framework suitable for identifying, characterising, and managing energy inefficiencies in digital infrastructures. The framework includes energy data collection, inefficiency characterisation, root cause analysis and implementation of a targeted solution. By focusing on key factors such as server utilisation, data management and resource allocation, the proposed methodology aims to contribute reducing energy consumption, operational costs and CO₂ emissions. The iterative approach proposed in the framework could enable continuous improvement and adaptation, promoting sustainable cloud manufacturing in digital infrastructure environments.
2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3008532