Study of the relationship between dimensional performance and manufacturing cost in fused deposition modeling. Issue 2 (12th March 2018) - Haghighi, Azadeh; Li, Lin
Abstract : Purpose: Quantifying and controlling the quality characteristics of parts produced by additive manufacturing (AM) processes has attracted significant interest in the research community. However, to increase the sustainability of AM processes, such quality characteristics need to be assessed together with life cycle performance of AM processes such as energy and material consumption and manufacturing cost. Although a few studies have been performed for several quality characteristics, i.e. surface roughness and tensile strength, the relationship between dimensional performance and manufacturing cost is still not well known for AM processes. Design/methodology/approach: In this paper, a comprehensive study of the dimensional performance and manufacturing cost of fused deposition modeling AM process is performed. Design of experiment technique is used, and the correlation of different cost components and the dimensional accuracy of parts are statistically studied. Findings: The optimum process parameters for simultaneously optimizing the dimensional performance and manufacturing cost are identified. The analysis shows that as opposed to traditional manufacturing processes, obtaining a better dimensional performance is not necessarily associated with higher cost in the AM processes. Originality/value: Almost no study and analysis for the combined dimensional performance and manufacturing cost has been performed for AM processes in the literature. It is known that within the context of traditional manufacturing processes, a natural trade-off governs the pursuit of higher dimensional performance and the manufacturing cost. However, as the AM process has a different nature compared with traditional manufacturing processes, the relationship between manufacturing cost and dimensional performance of parts has to be studied. Understanding this relationship will also help to establish a cost-optimal and sustainable tolerance allocation strategy in assemblies with AM components.