Additive manufacturing in green supply chains: A parametric model for life cycle assessment and cost

The use of additive manufacturing (AM) can improve the green performance of supply chains. However, adopting a centralized or a decentralized supply chain remains an open issue. A decision support model, that integrates Life Cycle Cost (LCC) and Life Cycle Assessment (LCA) methodologies, is proposed in this paper. The lifecycle of a printed product is parametrized depending on strategic decisions that impact economic and environmental sus-tainability at once, i.e., the production strategy, the degree of outsourcing and production decentralization. Cap-ital and variable costs have been modelled by adopting the process-based cost modelling (PBCM) approach. The monetary valuation of life cycle assessment (MLCA) has been used to aggregate different environmental impact categories. The green-ability of compared production scenarios is measured through a dimensionless-aggregated metric that, besides the scenario performance, also consider the weights the decision maker(s) should assign to the sustainability dimensions. A numerical application is carried out by comparing three different scenarios (i.e., centralized, decentralized, and mixed). Regarding the used data, results show that fully decentralizing printed product production by renting production capacity and outsourcing post-processing activities is the greenest solution regardless of the weights given to the economic and environmental dimensions.(c) 2023 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.

Automated summary

The use of additive manufacturing (AM) can enhance the environmental performance of supply chains by implementing a decision support model that integrates Life Cycle Cost (LCC) and Life Cycle Assessment (LCA) methodologies. The model takes into account strategic decisions related to production strategy, degree of outsourcing, and production decentralization. Based on the adoption of the process-based cost modeling approach, the model includes parametrized lifecycle of printed products considering both economic and environmental sustainability. A numerical application comparing centralized, decentralized, and mixed scenarios shows that fully decentralizing printed product production is the most environmentally sustainable solution, regardless of the weights assigned to the economic and environmental dimensions.