Parametric LCA model for Ti6Al4V powder production

The production of titanium (Ti6Al4V) powder is critical for aerospace, biomedical, and additive manufacturing but poses environmental challenges due to its energy intensity. Existing assessments often rely on static LCAs, offering limited optimization, or employ fragmented parametric models that do not capture full system interdependencies. This study introduces a novel, comprehensive parametric Life Cycle Assessment (LCA) framework for Ti6Al4V powder production, addressing these limitations. Its core methodological innovation lies in the integration of the entire production chain (from mining to sieving) and the simultaneous optimization of technically crucial, interdependent operational parameters, specifically, TiO₂ content in slag (typically 0.78–0.90), atomization electrode diameter (0.04–0.10 m), and argon pressure (often ≈5.5 MPa), rather than just parameterizing mass/energy flows as often seen in prior models. This is achieved by linking upstream process quality (e.g., slag composition impacting chlorination energy) to downstream performance and environmental impacts (e.g., atomization energy and waste generation) through empirically-derived relationships based on extensive literature data. The model minimizes environmental impact under user-defined control conditions (target powder diameter, region, impact category). Numerical investigation demonstrates significant impact reduction potential. Crucially, the model quantifies environmental trade-offs between conflicting objectives and reveals critical hotspots, with atomization and chlorination consistently accounting for >70 % of impacts even post-optimization. Energy consumption sensitivity is high, varying over five-fold for key steps based on parameter adjustments. This holistic, multi-variable optimization approach provides unprecedented, actionable insights by identifying optimal operational settings, not just sensitivities, for enhancing the sustainability of Ti6Al4V powder production, overcoming limitations of prior static or phase-specific parametric models.