Latest revision as of 16:06, 25 November 2022

Summary

Additive manufacturing (AM) has undergone different phases of technological changes from being a mere manufacturing method for consumer goods, prototyping, and tooling to industrial series production of functional end-use parts. The seven AM sub-categories allow the creation of unprecedented designs that are otherwise impossible using conventional manufacturing (CM) methods. The layer-by-layer approach to manufacturing enables the creation of metal components with hollows and overhangs, often requiring sacrificial support structures which are removed prior to or during the post-processing phase. Factors such as poor part quality, high investment cost, low material efficiency, and long manufacturing time hindered the widespread adoption of AM in the past. The adoption of laser-based powder bed fusion for metals was particularly hindered due to reasons such as the need for support structures, demand for post-processing, the numerous affecting processing parameters and the lack of understanding of the interaction between laser beam and material. Technological advances in AM have helped users reduce or omit some of the limitations to adoption, such as optimized support structures for better material efficiency. Simulation-driven tool is one means offering ways to time-efficient product development and more superior structural components amidst the raw material and cost reductions. This study elucidates how such benefits are feasible via using simulation tools. Simulation-driven optimization of the product design, process, and manufacturing is revealed to change the design, support structures and postprocessing required to bring parts to the required reliability. Virtual manufacturing planning also gives a prior understanding of how processing parameters such as laser scan velocity, laser power, scanning strategy, hatch distance and others can be controlled; to achieve optimal interaction between laser beam and material for the required part quality. Simulation-driven design for additive manufacturing (DfAM) allows for agile design optimizing with design parameters and rules, boosting resource efficiency and productivity. This research proposes a life cycle cost (LCC)driven DfAM tool, which potentially improves service life and life cycle cost. The results provide insight into the simulation-driven DfAM of laser-based PBF and demonstrate the potential for LCC-based approaches to enhance the confidence in adopting PBF for metals.

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