Title: Mass optimisation of 3D-printed specimens using multivariable regression analysis

Authors: Cristian-Vasile Doicin; Mihaela-Elena Ulmeanu; Allan E.W. Rennie; Elena Lupeanu

Addresses: University Politehnica of Bucharest, Bucharest 060042, Romania ' University Politehnica of Bucharest, Bucharest 060042, Romania ' Engineering Department, Lancaster University, Lancaster, UK ' National Institute of Geriatrics and Gerontology 'Ana Aslan', Bucharest 011241, Romania

Abstract: Fused deposition modelling popularity is attributed to equipment affordability, materials availability and open-source software. Given the variety of optimisation combinations, process parameters can be elaborate. This paper provides methods for optimisation of mass calculation using multivariable regression analysis. Layer thickness, extrusion temperature and speed were considered independent variables for a two-level factorial experiment. DOE was used for 12 sets of programs and analysis (two stages) undertaken using Design-Expert® V11 Software. In stage-1, four models were found to be significant. Stage-2 involved redesigning the remaining eight models, iteratively increasing the number of replicates and blocks. Adequacy of models was analysed, demonstrating that: model is significant, F-value is large, p < 0.05; lack of fit is insignificant; adequate precision >4.00; residuals are well behaved; R2 is as close as possible to 1.00 or for models with multiple replicates, the adjusted R2 and predicted R2 differential <0.2. All models were validated through measured, calculated responses.

Keywords: optimised mass calculation; material extrusion; design of experiments; DOE; multivariable regression analysis; MRA.

DOI: 10.1504/IJRAPIDM.2021.119936

International Journal of Rapid Manufacturing, 2021 Vol.10 No.1, pp.1 - 22

Received: 29 Oct 2019
Accepted: 13 Jan 2020

Published online: 04 Jan 2022 *

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