System Approach to Investigate Environmental Footprint and Cost Tradeoffs in Additive Manufacturing

Abstract

As additive manufacturing (AM) continues to grow and show potential for efficient resource utilization and product lifecycle, it represents a promising technology for the green industrial transformation needed to achieve Net Zero Emissions by 2050. However, the environmental impact of AM remains unclear, given its diverse applications and the historical emphasis on cost and quality as primary adoption drivers. Pressured by climate change, AM manufacturers lack quantitative tools to balance the technology’s complexity, environmental impact, and economic value.

This thesis demonstrates the use of system modeling methodologies to help AM manufacturers navigate these tradeoffs and make data-driven decisions to scale their service. After exploring the policy landscape impacting manufacturing and reviewing the latest developments in AM cost modeling and environmental impact assessment, a case study on an AM service unit in the sporting goods industry is used to illustrate the methodologies. A tradespace analysis compares the value of HP’s MultiJet Fusion technology to injection molding (IM) across various product characteristics and lifecycle decisions, and a flexible design analysis evaluates various investment decisions, considering uncertainties from the market and technology.

For the case studied (and assumptions used), the tradespace analysis reveals a 75% lower environmental footprint (EF) per part using AM compared to IM, while IM yields a 97% unit cost saving. Maximizing build capacity with small, uniform parts in locations with low-footprint energy increases AM’s economic and environmental value, suggesting that opposite product attributes and lifecycle decisions constitute development areas. The flexible design analysis, conducted for the specific AM service unit, shows that transitioning with added capacity to a larger rental facility with solar panels yields a 37% lower EF than maintaining current operations, and waiting to move to the larger facility until the demand aligns with added capacity generate a 96-137% increased NPV. These trends lead to the recommendation to transition the existing capacity to a larger rental facility with solar panels and wait for increased demand to invest in additional capacity.

These insights affirm the effectiveness of system modeling methodologies in guiding AM service providers by balancing financial and environmental factors. By introducing the application of these techniques in the AM context, this study establishes a baseline and identifies gaps to bridge for improved model accuracy. The approach developed in this work can be applied to different cases to quantitatively explore strategic options for technology investment and scaling to meet financial and environmental sustainability goals.