A design for additive manufacturing case study: fingerprint stool on a BigRep ONE

Abstract

Purpose This paper aims to present new qualitative and quantitative data about the recently released “BigRep ONE” 3 D printer led by the design of a one-off customized stool. Design/methodology/approach A design for additive manufacturing (DfAM) framework was adopted, with simulation data iteratively informing the final design. Findings Process parameters can vary manufacturing costs of a stool by over AU$1,000 and vary print time by over 100 h. Following simulation, designers can use the knowledge to inform iteration, with a second variation of the design being approximately 50 per cent cheaper and approximately 50 per cent faster to manufacture. Metrology data reveal a tolerance = 0.342 per cent in overall dimensions, and surface roughness data are presented for a 0.5 mm layer height. Research limitations/implications Led by design, this study did not seek to explore the full gamut of settings available in slicing software, focusing predominantly on nozzle diameter, layer height and number of walls alongside the recommended settings from BigRep. The study reveals numerous areas for future research, including more technical studies. Practical implications When knowledge and techniques from desktop 3 D printing are scaled up to dimensions measuring in meters, new opportunities and challenges are presented for design engineers. Print times and material costs in particular are scaled up significantly, and this study provides numerous considerations for research centers, 3 D printing bureaus and manufacturers considering large-scale fused filament fabrication manufacturing. Originality/value This is the first peer-reviewed study involving the BigRep ONE, and new knowledge is presented about the practical application of the printer through a design-led project. Important relationships between material volume/cost and print time are valuable for early adopters.

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A Boolean Method to Model Knit Geometries with Conditional Logic for Additive Manufacturing

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