Emerging manufacturing technologies such as Filament Deposition Modelling (FDM) printing have the ability to democratise manufacturing by enabling the low-cost production of goods in homes and communities. In addition to changing the way we manufacture, FDM and other Additive Manufacturing (AM) technologies are also able to revolutionise the way in which we design, as they permit the creation of structures not permissible by traditional subtractive processes. This flexibility also however creates a large and complex solution space yielding the generation of optimal designs incredibly difficult. A design methodology is proposed that accounts for the large and complex solution space afforded by the FDM process. It combines an empirically-derived capability profile of the FDM manufacturing process and a fusion of activities from both virtual and physical design processes. Capability profiles coupled with classical analysis techniques are used to predict part behaviours’ and, when coupled with appropriate solution space navigation, enable the auto-generation of manufacturing parameters & geometries that can satisfy the functional requirements of an object. This paper presents the Universal Hook Generator - an instantiation of this design methodology applied to the design of a generic load bearing component. It is used as a platform to explore the suitability of three metaheuristic search techniques; Evolutionary Algorithms, Simulated Annealing and Particle Swarm Optimisation. Each is assessed with respect their ability to auto-generate manufacturing and geometric parameters of a load bearing hook. Particle Swarm Optimisation is found to outperform both Evolutionary Algorithms and Simulated Annealing with respect to both quality and consistency of generated solutions.
|Title of host publication||29th International Conference on Flexible Automation and Intelligent Manufacturing|
|Publication status||Published - 20 Jan 2019|
Goudswaard, M. A., Hicks, B. J., & Nassehi, A. (2019). Towards the democratisation of design: the implementation of meta-heuristic search strategies to enable the auto-assignment of manufacturing parameters for FDM. In 29th International Conference on Flexible Automation and Intelligent Manufacturing https://doi.org/10.1016/j.promfg.2020.01.049