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Using a d-optimal mixture design to study the thermal properties of short glass fiber- and polytetrafluoroethylene-reinforced polycarbonate composites

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Abstract

This study analyzed variations of thermal properties that depend on the injection molding techniques during the blending of short glass fiber (SGF)- and polytetrafluoroethylene (PTFE)-reinforced polycarbonate (PC) composites. The proposed planning of blending experiments is using a d-optimal mixture design (DMD). The thermal conductivity and thermal expansion coefficient were selected for discussion. Nine experimental runs, based on a DMD method, utilized to train the back-propagation neural network (BPNN), and then the simulated annealing algorithm (SAA) approach is applied to search for an optimal mixture ratio setting. In addition, the result of BPNN integrating SAA was also compared with response surface methodology (RSM) approach. The results of confirmation experiment show that DMD, RSM, and BPNN integrating SAA method are effective tools for the optimization of reinforced process. Furthermore, analysis of variance and response surface graphs were applied to identify the effect of mixture ratio of SGF- and PTFE-reinforced PC composites for the thermal conductivity and thermal expansion coefficient.

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Acknowledgments

The authors would like to thank the National Science Council of the Republic of China for financially supporting this research (contract no. NSC 99-2221-E-159-003).

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Authors and Affiliations

  1. Department of Mechanical Engineering, Minghsin University of Science and Technology, No. 1, Hsin Hsing Road, Hsin Feng, 304, Hsin-Chu, Taiwan

    Hsin-Te Liao, Chorng-Jyh Tzeng, Yung-Kuang Yang & Yung-Chih Li

  2. Department of Information Management, Yuanpei University, No. 306, Yuanpei Street, 30015, Hsin-Chu, Taiwan

    Chih-Hung Tsai

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  1. Hsin-Te Liao
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  2. Chorng-Jyh Tzeng
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  3. Yung-Kuang Yang
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  4. Yung-Chih Li
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Correspondence to Chih-Hung Tsai.

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Liao, HT., Tzeng, CJ., Yang, YK. et al. Using a d-optimal mixture design to study the thermal properties of short glass fiber- and polytetrafluoroethylene-reinforced polycarbonate composites. Neural Comput & Applic 24, 833–844 (2014). https://doi.org/10.1007/s00521-012-1299-1

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  • DOI: https://doi.org/10.1007/s00521-012-1299-1

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