Abstract

Additive manufacturing (AM) is a recent emerging technology that is being adopted in various industry sectors and supply chains. Life cycle assessment (LCA) and life cycle costing (LCC) are powerful methods that can be used for assessing the environmental and economic performance of emerging manufacturing technologies. This study aims to evaluate the life cycle environmental impacts and cost of computerized numerical control-based (CNC) manufacturing and direct metal laser sintering technology (DMLS) through a cradle-to-gate life cycle analysis. This research has four main novel elements: (i) conducting a recent comprehensive review of metal AM and conventional manufacturing (CM) processes using a systematic method and meta-analysis (ii) comparing the conventional process “CNC machining” and the additive technology “direct metal laser sintering” from the environmental (LCA) and economic (LCC) perspectives, (iii) investigating the influence of geometry complexity and shape size factors on the environmental and cost performance of both manufacturing methods, and (iv) conducting a Monte Carlo simulation-based sensitivity analysis to tackle uncertainty in LCC input parameters. The midpoints and endpoints impact for CNC and AM processes were estimated using the Ecoinvent v3.8 database and ReCiPe (E) impact assessment method. The review revealed that global warming potential is one of the most widely studied environmental indicators; however, only 6% of the studies have investigated the life cycle economic impacts of AM technologies using sensitivity and uncertainty analysis. The results have shown that in terms of ReCiPe endpoints, DMLS has the highest environmental impact on human health while CM has more impact on the eco-system quality. Electricity consumption is the main contributor to environmental impact categories in both manufacturing technologies. This is due to the high electricity utilization for casting and milling conventionally manufactured parts and printing the AM parts. LCC net present values revealed that manufacturing all parts with AM costs 91% more compared to CNC. The LCC analysis has shown that AM is more suitable and cost-effective for parts with highly complex geometries. Whereas CNC machining was found to be economically feasible for large-sized and low-complexity parts. The Monte Carlo sensitivity analysis demonstrated that for the case of AM, the most significant parameter is the processing cost followed by material cost, which highlighted the importance of energy-efficient AM and dematerialization through design for circularity.

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