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Research on human health and safety impacts of wire arc additive manufacturing is often overshadowed by the need for weld quality and mechanical strength improvements. To address this gap, a review of research literature is conducted focusing on the influence of welding process parameters, welding fumes, and fume exposure on worker health. The review uses a causal graph to classify research literature into two domains: manufacturing technology and public health. The graph serves as a precursor to development of a Bayesian network model, whose expected benefits, steps for implementation, and likely challenges that would be encountered during implementation are discussed. publishedVersion

Additive manufacturing is rapidly emerging as an alternative to conventional manufacturing, including subtractive processes, often attributed to its claim for sustainable product development, e.g., reduced cost, reduced energy and material use, and the distributed production of tailored consumer products. However, many of these benefits remain unsubstantiated for large-scale production. The aim of the research herein is to identify the systemic contributors to environmental impacts for additive manufacturing using exergy analysis and life cycle impact assessment. These methods have been previously applied to evaluate the environmental performance of conventional and non-conventional manufacturing processes. Thus, they offer a validated approach to evaluate the environmental impacts of additive manufacturing with respect to systemic material and energy losses. In this study, the environmental impacts of direct metal laser sintering (DMLS) of iron metal powder is characterized by performing a thermodynamic analysis of the resources and energy utilized and lost from cradle-to-gate. It is found that only 6% of total process inputs in DMLS contribute to material processing, while 94% is lost as bulk waste, heat, and work. Life cycle impact assessments are performed to characterize the environmental impacts of these losses using single issue indicator (Global Warming Potential, GWP) and aggregate indicator (ReCiPe 2008) methods. The results show that electricity consumption is a key contributor to the focal process and its related upstream processes. The systemic GWP impact for DMLS was found to be 7.2 kg CO 2 equivalent. ReCiPe 2008 indicates damage to human health outweighs damage to ecosystem quality (E=84%, H=58%, I=51%) and resource availability (E=74%, H=29%, I=19%) for the DMLS process.

Key performance indicators (KPIs) are used to monitor and improve production cost, quality, and time. A plethora of manufacturing KPIs are currently in use, with others continually being developed to meet organizational needs. However, obtaining the optimum KPI values at different organizational levels is challenging due to the complex interactions between manufacturing decisions, variables, and the desired targets. A Bayesian network is developed to characterize the interrelationships between manufacturing decisions and variables, selected KPI, and total production cost. For an additive manufacturing case, the approach enables appropriate KPI value estimation for achieving desired production cost targets in a manufacturing enterprise. publishedVersion

Implementation of additive manufacturing into product manufacturing suffers from the challenge of part defects prediction. Due to interdependencies of design variables and manufacturing parameters in achieving suitable part quality, modelling methods are necessary to provide simulation capabilities for part quality analysis at early stages of product development. A systematic methodology is proposed to extract cause-effect relationships among variables and to transform this causal model into a Bayesian network. The Bayesian network is then used to predict the effect of specific design and manufacturing parameters on part defects and to estimate the needed input parameters backwards, based on acceptable output values. publishedVersion