Feature-centric allocation and visualization of primary manufacturing process life cycle inventory data

Detailed machine-specific data are critical for accurate sustainability assessment and for supporting design decisions to reduce environmental impacts from manufacturing. However, obtaining, analyzing, and interpreting such fine-grained measurements can be challenging and inefficient. Existing methods for the above are time-consuming, do not fully capture process variability over time, and do not relate primary manufacturing data back to design decision-making. In this work, we propose a methodology to programmatically disaggregate process-level life cycle inventory data measurements, and relate it to both operations (i.e., activities or sub-processes) within the process and the geometric features created or affected by the process. We do this by leveraging the underlying machine code used to manufacture the part, in this case G-code, and by providing a scalable definition scheme for the corresponding operations, geometric features, and the relationship between them. Results can be used to generate targeted, actionable insights into process setup and product design improvements to address environmental impacts of manufacturing processes. • A method to relate process inventory to manufacturing activities and part geometry. • Interactive 2D and 3D visualizations are produced to aid decision-making. • Energy use in CNC milling and FDM 3D printing are analyzed. • Opportunities for product and process redesign were identified.