Enhancing Low-Carbon Routing Through Additive Manufacturing of Reconfigurable Products: An Exploratory Study

The reduction and neutrality of carbon emissions have emerged as major concerns spanning various stages of product life cycles. Additive manufacturing (AM), with its process efficiency and decentralized production characteristics, has been seen as an enabler for more sustainable practices in both product production and distribution. Recent advancements in AM of shape memory materials offer promising prospects for the production of smart products that can re-configure and re-shape in response to external stimuli, such as heat and electricity. This new manufacturing paradigm holds the potential to enable green product logistics by facilitating easier transportation and storage of compact or coalesced products, which can later revert to their desired shapes. Nonetheless, it should be noted that these benefits are accompanied by trade-offs stemming from the additional carbon emissions generated during the stimuli-triggered reshaping. In this research, an integrated vehicle assignment and routing approach is demonstrated for logistics distribution networks that involve reconfigurable products made by AM, considering stochastic travel and customer demand. Case studies were performed on the distribution networks of reconfigurable lamp shades, and the results indicate the effectiveness of the demonstrated method in determining the best product-to-vehicle assignments and sequence of trips with minimized carbon emissions.