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Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published

Standard

Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts. / Doicin, Cristian-Vasile; Ulmeanu, Mihaela-Elena; Rennie, Allan et al.
16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019). ed. / Allan Rennie; Eujin Pei; Philip Hackney. 2019.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Doicin, C-V, Ulmeanu, M-E, Rennie, A & Lupeanu, E 2019, Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts. in A Rennie, E Pei & P Hackney (eds), 16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019). 16th Rapid Design, Prototyping & Manufacturing Conference , Uxbridge, United Kingdom, 4/04/19.

APA

Doicin, C-V., Ulmeanu, M-E., Rennie, A., & Lupeanu, E. (2019). Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts. In A. Rennie, E. Pei, & P. Hackney (Eds.), 16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019)

Vancouver

Doicin C-V, Ulmeanu M-E, Rennie A, Lupeanu E. Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts. In Rennie A, Pei E, Hackney P, editors, 16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019). 2019

Author

Doicin, Cristian-Vasile ; Ulmeanu, Mihaela-Elena ; Rennie, Allan et al. / Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts. 16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019). editor / Allan Rennie ; Eujin Pei ; Philip Hackney. 2019.

Bibtex

@inproceedings{aca5200c535345e3b1b092b03d9fdce5,
title = "Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts",
abstract = "Since its introduction in the early 1990s Material Extrusion (MEX) has become the most popular additive manufacturing technology for a variety of applications. One of the reasons of its popularity amongst users is the affordability of the equipment, materials and the open source software. Given the large variety of combinations optimisation of MEX process parameters can be quite elaborate. The paper provides a method for optimisation of mass calculation using multivariable regression analysis. Layer thickness, printing temperature and printing speed were considered the independent variables for a two level factorial experimental program. DOE was used to plan 12 sets of programs, out of which four were found to have significant models. The four models were validated through measured and calculated responses.",
keywords = "Optimised Mass Calculation, Regression Analysis, Material Extrusion, Design Of Experiments",
author = "Cristian-Vasile Doicin and Mihaela-Elena Ulmeanu and Allan Rennie and Elena Lupeanu",
year = "2019",
month = apr,
day = "5",
language = "English",
isbn = "9781527251649",
editor = "Allan Rennie and Eujin Pei and Philip Hackney",
booktitle = "16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019)",
note = "16th Rapid Design, Prototyping & Manufacturing Conference , RDPM 2019 ; Conference date: 04-04-2019 Through 05-04-2019",
url = "http://www.rdpmconference.co.uk",

}

RIS

TY - GEN

T1 - Multivariable Regression Analysis for Optimised Mass Calculation of MEX 3D Printed Parts

AU - Doicin, Cristian-Vasile

AU - Ulmeanu, Mihaela-Elena

AU - Rennie, Allan

AU - Lupeanu, Elena

PY - 2019/4/5

Y1 - 2019/4/5

N2 - Since its introduction in the early 1990s Material Extrusion (MEX) has become the most popular additive manufacturing technology for a variety of applications. One of the reasons of its popularity amongst users is the affordability of the equipment, materials and the open source software. Given the large variety of combinations optimisation of MEX process parameters can be quite elaborate. The paper provides a method for optimisation of mass calculation using multivariable regression analysis. Layer thickness, printing temperature and printing speed were considered the independent variables for a two level factorial experimental program. DOE was used to plan 12 sets of programs, out of which four were found to have significant models. The four models were validated through measured and calculated responses.

AB - Since its introduction in the early 1990s Material Extrusion (MEX) has become the most popular additive manufacturing technology for a variety of applications. One of the reasons of its popularity amongst users is the affordability of the equipment, materials and the open source software. Given the large variety of combinations optimisation of MEX process parameters can be quite elaborate. The paper provides a method for optimisation of mass calculation using multivariable regression analysis. Layer thickness, printing temperature and printing speed were considered the independent variables for a two level factorial experimental program. DOE was used to plan 12 sets of programs, out of which four were found to have significant models. The four models were validated through measured and calculated responses.

KW - Optimised Mass Calculation

KW - Regression Analysis

KW - Material Extrusion

KW - Design Of Experiments

M3 - Conference contribution/Paper

SN - 9781527251649

BT - 16th Rapid Design, Prototyping & Manufacturing Conference (RDPM2019)

A2 - Rennie, Allan

A2 - Pei, Eujin

A2 - Hackney, Philip

T2 - 16th Rapid Design, Prototyping & Manufacturing Conference

Y2 - 4 April 2019 through 5 April 2019

ER -