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There is a combinatorial explosion of alternative variants of an assembly design owing to the design freedom provided by Additive Manufacturing. In this regard, a novel Virtual Reality-based decision-support framework is presented herein for extracting the superior assembly design to be fabricated by AM route. It specifically addresses the intersection between human assembly and AM hence combining Design for Assembly, and Design for Additive Manufacturing using Axiomatic Design theory. Several Virtual Reality experiments were carried out to achieve this with human subjects assembling parts. At first, a 2D table is assembled, and the data are used to confirm the independence of nonfunctional requirements such as assembly time and assembly displacement error according to Independence Axiom. Then this approach is demonstrated on an industrial lifeboat hook with three assembly design variations. The data from these experiments are utilized to evaluate the possible combinations of the assembly in terms of probability density based on the Information Axiom. The technique effectively identifies the assembly design most likely to fulfill the nonfunctional requirements. To the authors’ best knowledge, this is the first study that numerically extracts the human aspect of design at an early design stage in the decision process and considers the selection of the superior assembly design in a detailed design stage. Finally, this process is automated using a graphical user interface, which embraces the practicality of the currently integrated framework and enables manufacturers to choose the best assembly design.

The design freedom provided by Additive Manufacturing (AM) enables the part consolidation (PC) of sophisticated mechanical assemblies. However, PC has been mainly performed for static components in assemblies with nonmoving parts. In this regard, a new approach to assembly-level Design for Additive Manufacturing (A-DfAM) considering an industrial lifeboat hook assembly with a functionally dynamic system is proposed. The methodology comprises steps starting from inputting the Computer-Aided Design (CAD) files for the 3D printing of the final assembly and evaluation. Throughout the design stages, opportunistic and restrictive natures of DfAM within our methodology direct engineers and designers to manufacture optimized products. In addition, a comparative assessment of the original and final assemblies is also illustrated. Consequently, a significant part-count reduction after PC was achieved, and the prototype of the lifeboat hook components was printed via laser-powder bed fusion (L-PBF). This shows that by incorporating the suggested A-DfAM framework, it can serve as a potential guide to whoever intends to manufacture dynamic assemblies.

To overcome the limited feasibility of various refractory high-entropy alloys (HEAs) due to the presence of (i) very dense elements (W and Ta), (ii) costly elements (Hf and Ta), and (iii) oxidation prone elements (V) in them, AlxCryMozNbTiZr HEAs were prepared via arc-melting. Considering the critical nature of oxidation resistance in high-temperature applications, HEAs were characterized to form a combinatorial library of microstructural and oxidation behavior. AlxCryMozNbTiZr HEAs revealed multiphase microstructures consisting of intermetallic phases along with BCC matrices. Mass loss and porous microstructures were obtained in Mo-rich HEAs after oxidation at 1000 °C for 1 h. The presence of Al enhanced the oxidation resistance and developed a protective oxide layer on the HEAs. Al30Cr10-NTZ exhibited promising potential for use in high temperature applications, as it showed an oxidation time exponent of ∼0.5 and a dense and continuous oxide layer.