Life cycle assessment of CNC machining for freeform mirrors

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Authors: Hanif Auwal Ibrahim, Noel Harrison, Tomás Flanagan, A. R. Jennings, Stephen Mundy, George Willis, Sinéad Mitchell
Cited by: 1
References: 13

Abstract

Freeform mirrors, with their non-symmetric geometries, enable advanced optical performance for aerospace, photonics, and imaging applications. However, their manufacturing involves resource-intensive processes with largely unexplored environmental impacts. This study presents a cradle-to-gate life cycle assessment (LCA) of computer numerical control (CNC) machining for AlSi freeform mirrors, following ISO 14040/44 standards. The analysis quantifies carbon footprint and energy demand, establishing a baseline for sustainable manufacturing. Results reveal that mirror machining and subsequent coating and metrology phases dominate environmental impacts, contributing approximately 80% of the total carbon footprint (35.85 out of 45 kg CO₂-eq). The coating phase accounts for nearly half of the impacts (22 kg CO₂-eq), while raw material production (17.6%) and transport (2.6%) are secondary contributors. Toxicity impacts are significant, driven by chemical inputs and waste streams, underscoring the need for improved material handling and waste treatment. Key improvement opportunities include renewable energy adoption, scrap recycling, machining optimisation, cutting fluid reduction, and coating efficiency enhancements. Future work will compare these findings with alternative manufacturing routes such as additive manufacturing (AM) and replication methods, which may offer lower life-cycle impacts for complex geometries. By identifying environmental hotspots, this study informs eco-design strategies and process innovations within the FreeForm Optix project and beyond, enabling the optical industry to reduce the carbon footprint and resource intensity of high-precision components.

Fields of Study & Subjects

Engineering Technology and Methodologies Energy Efficiency and Management Advanced machining processes and optimization

Publication details

Journal / source
Procedia CIRP
Publisher
Elsevier BV
Volume
140
Pages
108–113
Publication date
1 January 2026
Language
EN