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A multi-objective Gaussian process approach for optimization and prediction of carbonization process in carbon fiber production under uncertainty

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Abstract

During composite fiber production, carbon fibers are normally derived from polyacrylonitrile precursor. Carbonization, as a key step of this process, is significantly energy-consuming and costly, owing to its high temperature requirement. A cost-effective approach to optimize energy consumption during the carbonization is implementing predictive modeling techniques. In this article, a Gaussian process approach has been developed to predict the mechanical properties of carbon fibers in the presence of manufacturing uncertainties. The model is also utilized to optimize the fiber mechanical properties under a minimum energy consumption criterion and a range of process constraints. Finally, as the Young’s modulus and ultimate tensile strength of the fibers did not show an evident correlation, a multi-objective optimization approach was introduced to acquire the overall optimum condition of the process parameters. To estimate the trade-off between these material properties, the standard as well as an adaptive weighted sum method were applied. Results were summarized as design chart for potential applications by manufacturing process designers.

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Acknowledgments

The support of colleagues and the stimulating discussions at the Composites Research Network and Carbon Nexus Institute are greatly valued.

Funding

This study was financially supported by the Natural Sciences and Engineering Research Council (NSERC) of Canada.

Author information

Authors and Affiliations

  1. Composites Research Network, School of Engineering, University of British Columbia, Kelowna, V1V 1V7, Canada

    Milad Ramezankhani, Bryn Crawford, Rudolf Seethaler & Abbas S. Milani

  2. School of Engineering, RMIT University, Melbourne, VIC 3000, Australia

    Hamid Khayyam

  3. Institute for Frontier Materials, Carbon Nexus, Deakin University, Waurn Ponds, VIC 3216, Australia

    Minoo Naebe

Authors
  1. Milad Ramezankhani
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  2. Bryn Crawford
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  3. Hamid Khayyam
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  4. Minoo Naebe
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  5. Rudolf Seethaler
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  6. Abbas S. Milani
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Corresponding author

Correspondence to Abbas S. Milani.

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Raw experimental data obtained from carbonization process trials. For each set of process conditions, 50 trials have been performed [15]

Raw experimental data obtained from carbonization process trials. For each set of process conditions, 50 trials have been performed [15]

Temperature of zone 1 (°C)

Temperature of zone 2 (°C)

Time (s)

Modulus (GPa)

Modulus STD (GPa)

Tensile strength (GPa)

Tensile strength STD (GPa)

Energy consumption (kWh)

1100

1400

156

228.8

18.47

3.016

1.06

11.87

1100

1400

167

227.7

9.288

3.201

0.68

11.95

1100

1400

162

227.5

9.89

3.275

0.77

11.92

1100

1400

151

234.6

13.67

3.458

0.76

11.86

1125

1425

156

228.3

14.48

2.925

1

12.19

1125

1425

167

229.2

34.03

3.185

0.81

12.44

1125

1425

162

226.7

11.66

3.031

0.81

12.4

1125

1425

151

231.9

15.9

3.225

0.59

12.37

1150

1450

156

219.8

7.797

2.945

0.63

12.49

1150

1450

167

221.8

10.11

3.13

0.87

12.58

1150

1450

162

217.6

32.99

3.11

0.65

12.51

1150

1450

151

224.3

10.78

3.18

0.63

12.47

1175

1475

156

197.7

35.32

2.78

0.68

12.7

1175

1475

167

154.2

9.5

2.11

0.36

12.81

1175

1475

162

157.5

9.13

2.35

0.41

12.77

1175

1475

151

163.02

5.39

2.209

0.34

12.65

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Ramezankhani, M., Crawford, B., Khayyam, H. et al. A multi-objective Gaussian process approach for optimization and prediction of carbonization process in carbon fiber production under uncertainty. Adv Compos Hybrid Mater 2, 444–455 (2019). https://doi.org/10.1007/s42114-019-00107-6

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  • DOI: https://doi.org/10.1007/s42114-019-00107-6

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