While sustainability is set as a goal by a broad range of international organizations, its definition varies, and there is still a lack of practical criteria for product designers to evaluate the degree of (un)sustainability in the design phase. Life cycle assessment (LCA) can allow quantification of the environmental impacts of a product but is often carried out post-design, when the manufacturing process is already settled. Finally, while significant advances have been made towards standardizing LCA calculations by providing product category rules, large uncertainties remain in the calculation results due to a lack of transparency regarding the choices of databases, system boundaries, allocation, cut-off rules, and level of data granularity. A practical way to improve in those areas is to share with the semiconductor community a parametrizable life cycle inventory (LCI) model based on a target device to (1) identify knowledge gaps in LCA methods for such products, (2) identify the main process variables, and (3) provide a starting point for LCA calculations by the designers themselves. With this aim, a parametrizable cradle-to-gate manufacturing LCI model was developed based on the peer-reviewed process flow of a trench field-stop silicon insulated gate bipolar transistor (IGBT) semiconductor power device. The model allows computation of the environmental impacts of the IGBT manufacturing process based on different tunable parameters such as die size, wafer diameter, manufacturing yield, abatement efficiency, wafer fab throughput, wafer fab location, and associated electricity mix. Embedding a high level of data granularity, it helps identify, at elementary process levels, key environmental hotspots and associated technical levers for their reduction. Analysis of the IGBT manufacturing process tends to demonstrate the importance of an impact assessment approach considering multiple environmental categories, going beyond the sole focus on greenhouse gas emissions and accounting for potential transfers of impact. With an open-source mindset and in a continuous improvement prospective, the manufacturing inventory model and its associated tools are freely available from a public GitHub repository and open for comments and consolidation from users.
Guillemet et al. (Mon,) studied this question.