TY - JOUR
T1 - Improving tensile strength of an injection-molded biocompatible thermoplastic elastomer
AU - Fittipaldi, Mauro
AU - Rodriguez, Luis A.
AU - Damley-Strnad, Alexandra
AU - Grace, Landon R
PY - 2015/12/5
Y1 - 2015/12/5
N2 - Poly(styrene-block-isobutylene-block-styrene) (SIBS) is a thermoplastic elastomer often used in implantable structures due to its exceptional biocompatibility. However, because overall performance is extremely sensitive to fabrication conditions, optimal processing of the raw material remains a challenge. In this study, the Taguchi method is proposed for characterization of the effect of injection molding parameters on the ultimate tensile strength of a SIBS block copolymer. An L9 orthogonal array is used with three factor levels for nozzle temperature, mold temperature, packing time and injection speed. Analysis indicates that mold temperature has the least effect on tensile strength, and injection speed the greatest effect. A response surface methodology (RSM) design and an artificial neural network (ANN) were used to model tensile strength based on processing parameters. Both methods proved successful in predicting tensile strength with errors of 3% and 2.55% for RSM and ANN, respectively. Optimized validation samples showed ultimate tensile strengths of 17.7MPa, which is an improvement of almost 40% over reported strengths for the same material. The results presented here are expected to expand the use of SIBS into new applications requiring improved mechanical properties, without sacrificing biocompatibility via the addition of fiber or particle reinforcement.
AB - Poly(styrene-block-isobutylene-block-styrene) (SIBS) is a thermoplastic elastomer often used in implantable structures due to its exceptional biocompatibility. However, because overall performance is extremely sensitive to fabrication conditions, optimal processing of the raw material remains a challenge. In this study, the Taguchi method is proposed for characterization of the effect of injection molding parameters on the ultimate tensile strength of a SIBS block copolymer. An L9 orthogonal array is used with three factor levels for nozzle temperature, mold temperature, packing time and injection speed. Analysis indicates that mold temperature has the least effect on tensile strength, and injection speed the greatest effect. A response surface methodology (RSM) design and an artificial neural network (ANN) were used to model tensile strength based on processing parameters. Both methods proved successful in predicting tensile strength with errors of 3% and 2.55% for RSM and ANN, respectively. Optimized validation samples showed ultimate tensile strengths of 17.7MPa, which is an improvement of almost 40% over reported strengths for the same material. The results presented here are expected to expand the use of SIBS into new applications requiring improved mechanical properties, without sacrificing biocompatibility via the addition of fiber or particle reinforcement.
KW - ANN
KW - Injection molding optimization
KW - RSM
KW - SIBS
KW - Taguchi
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U2 - 10.1016/j.matdes.2015.07.070
DO - 10.1016/j.matdes.2015.07.070
M3 - Article
AN - SCOPUS:84942251391
VL - 86
SP - 6
EP - 13
JO - Materials and Design
JF - Materials and Design
SN - 0261-3069
ER -