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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.

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The additive manufacturing (AM) technology provides a unique opportunity to realize as-built assemblies, i.e., assemblies which can be fabricated as a whole in one build cycle. Some of the introduced challenges, however, are the design issues of these assembly structures and understanding the dimensional performance of the AM process to ensure proper mobility. While process improvement techniques have been proposed for dealing with individual additive components, it is also necessary to study the dimensional behavior of as-built assemblies compared to individual additive components. This paper studies and compares the dimensional performance of as-built assemblies with ordinary assemblies in which the components are fabricated individually and then assembled together. A design of experiment approach is applied to study the effect of assembly type and orientation on the final clearances. The results suggest that in addition to orientation factor, the type of assembly can also play an important role in the final clearance values. In addition, a different dimensional behavior exists in the as-built assembly structures compared to ordinary assemblies, i.e., clearances in as-built assembly tend to be smaller and also more uniform along the clearance profile.

Additive manufacturing has drawn significant attention in both academia and industry due to its capabilities and promising potential in various sectors. However, the adoption of this technology in large-scale construction is still limited due to the numerous existing challenges. In this work, a comprehensive review of large-scale automated additive construction, its challenges, and emerging advances with a focus on robotic solutions and environmental sustainability is presented. The potential interrelations of the two topics are also discussed. A new classification scheme of available and emerging robotic solutions in automated additive construction is presented. Moreover, the vision of environmental sustainability is explored through three lenses: process, material, and printed large-scale structures/buildings. Finally, the current challenges and potential future directions are highlighted. The provided state of the art and challenges can be used as a guideline for future research on large-scale automated additive construction.

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