JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING, v.10, no.3, pp.1126 - 1142
Abstract
There is a combinatorial explosion of alternative variants of an assembly design owing to the design freedom provided by additive manufacturing (AM). 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 two-dimensional table is assembled, and the data are used to confirm the independence of non-functional 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 non-functional 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.