An approach for mechanical property optimization of fused deposition modeling with polylactic acid via design of experiments

Purpose This paper aims to present the influences of several production variables on the mechanical properties of specimens manufactured using fused deposition modeling (FDM) with polylactic acid (PLA) as a media and relate the practical and experimental implications of these as related to stiffness, strength, ductility and generalized loading. Design/methodology/approach A two-factor-level Taguchi test matrix was defined to allow streamlined mechanical testing of several different fabrication settings using a reduced array of experiments. Specimens were manufactured and tested according to ASTM E8/D638 and E399/D5045 standards for tensile and fracture testing. After initial analysis of mechanical properties derived from mechanical tests, analysis of variance was used to infer optimized production variables for general use and for application/load-specific instances. Findings Production variables are determined to yield optimized mechanical properties under tensile and fracture-type loading as related to orientation of loading and fabrication. Practical implications The relation of production variables and their interactions and the manner in which they influence mechanical properties provide insight to the feasibility of using FDM for rapid manufacturing of components for experimental, commercial or consumer-level use. Originality/value This paper is the first report of research on the characterization of the mechanical properties of PLA coupons manufactured using FDM by the Taguchi method. The investigation is relevant both in commercial and consumer-level aspects, given both the currently increasing utilization of 3D printers for component production and the viability of PLA as a renewable, biocompatible material for use in structural applications.

[1]  Dominik Rietzel,et al.  Suitability of PLA/TCP for fused deposition modeling , 2012 .

[2]  Chee Kai Chua,et al.  Investigation of 3D Non-Random Porous Structures by Fused Deposition Modelling , 2002 .

[3]  Ming-Chang Jeng,et al.  Optimization of die casting conditions for wear properties of alloy AZ91D components using the Taguchi method and design of experiments analysis , 2009 .

[4]  Siba Sankar Mahapatra,et al.  OPTIMIZATION OF PROCESS PARAMETERS IN FUSED DEPOSITION MODELING USING WEIGHTED PRINCIPAL COMPONENT ANALYSIS , 2011 .

[5]  Richard Craig Van Nostrand,et al.  Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement , 2002, Technometrics.

[6]  Paulo Jorge Da Silva bartolo,et al.  Stereolithography: Materials, Processes and Applications , 2011 .

[7]  Caroline Sunyong Lee,et al.  Measurement of anisotropic compressive strength of rapid prototyping parts , 2007 .

[8]  Per Capita,et al.  About the authors , 1995, Machine Vision and Applications.

[9]  Neil Hopkinson,et al.  Rapid prototyping for direct manufacture , 2001 .

[10]  Ellen R. Girden,et al.  ANOVA: Repeated Measures , 1991 .

[11]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[12]  S. S. Mahapatra,et al.  Optimization of Fused Deposition Modelling (FDM) Process Parameters Using Bacterial Foraging Technique , 2009, Intell. Inf. Manag..

[13]  An Hua Peng,et al.  Process-Parameter Optimization for Fused Deposition Modeling Based on Taguchi Method , 2012 .

[14]  A. K. Sood,et al.  Parametric appraisal of mechanical property of fused deposition modelling processed parts , 2010 .

[15]  Donald Garlotta,et al.  A Literature Review of Poly(Lactic Acid) , 2001 .

[16]  Paul F. Jacobs,et al.  Rapid Prototyping & Manufacturing: Fundamentals of Stereolithography , 1992 .

[17]  H. Kuo,et al.  A Novel Algorithm with Orthogonal Arrays for the Global Optimization of Design of Experiments , 2013 .

[18]  Peter Beike,et al.  Beyond Anova Basics Of Applied Statistics , 2016 .

[19]  Jaimin P. Patel,et al.  A REVIEW ON VARIOUS APPROACH FOR PROCESS PARAMETER OPTIMIZATION OF FUSED DEPOSITION MODELING ( FDM ) PROCESS AND TAGUCHI APPROACH FOR OPTIMIZATION Mr , 2012 .

[20]  I. I. Karpunin,et al.  CLASSIFICATION OF BIODEGRADABLE POLYMERS , 2015 .

[21]  H. Yamane,et al.  Effect of the addition of poly(d-lactic acid) on the thermal property of poly(l-lactic acid) , 2003 .

[22]  Robert Bogue,et al.  3D printing: the dawn of a new era in manufacturing? , 2013 .

[23]  P. Wright,et al.  Anisotropic material properties of fused deposition modeling ABS , 2002 .

[24]  David Z. Zhang,et al.  Additive manufacturing: A framework for implementation , 2014 .

[25]  Ryan B. Wicker,et al.  3D printer selection: A decision-making evaluation and ranking model , 2013 .

[26]  A. Clarinval,et al.  1 – Classification of biodegradable polymers , 2005 .

[27]  M. Stanek,et al.  Comparison of Different Rapid Prototyping Methods , 2022 .

[28]  S. Desobry,et al.  Poly-Lactic Acid: Production, Applications, Nanocomposites, and Release Studies. , 2010, Comprehensive reviews in food science and food safety.

[29]  Michael F. Ashby,et al.  Materials and Design: The Art and Science of Material Selection in Product Design , 2002 .

[30]  P. Gruber,et al.  Polylactic Acid Technology , 2000 .

[31]  Sara McMains.  Layered manufacturing technologies , 2005, CACM.

[32]  Riccardo Russo,et al.  A Student's Guide to Analysis of Variance , 1999 .