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Review
. 2021 Aug 4;13(16):2592.
doi: 10.3390/polym13162592.

Classification of Textile Polymer Composites: Recent Trends and Challenges

Nesrine Amor  1 , Muhammad Tayyab Noman  1 , Michal Petru  1
Affiliations
Review

Classification of Textile Polymer Composites: Recent Trends and Challenges

Nesrine Amor et al. Polymers (Basel). .

Abstract

Polymer based textile composites have gained much attention in recent years and gradually transformed the growth of industries especially automobiles, construction, aerospace and composites. The inclusion of natural polymeric fibres as reinforcement in carbon fibre reinforced composites manufacturing delineates an economic way, enhances their surface, structural and mechanical properties by providing better bonding conditions. Almost all textile-based products are associated with quality, price and consumer's satisfaction. Therefore, classification of textiles products and fibre reinforced polymer composites is a challenging task. This paper focuses on the classification of various problems in textile processes and fibre reinforced polymer composites by artificial neural networks, genetic algorithm and fuzzy logic. Moreover, their limitations associated with state-of-the-art processes and some relatively new and sequential classification methods are also proposed and discussed in detail in this paper.

Keywords: Sequential Monte Carlo methods; artificial neural network; classification; fiber reinforced polymer composites; fuzzy logic.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Comparison of machine learning approaches with traditional deterministic models.
Figure 2
Figure 2
A schematic illustration of this study.
Figure 3
Figure 3
Summary of machine learning procedure validated for fiber reinforced polymer composites including CFRP, GFRP, BFRP and AFRP etc. [100].
Figure 4
Figure 4
A general schematic layout of the state estimation method with data assimilation.
Figure 5
Figure 5
Examples of: Defective fabric samples with different patterned textures (from a1–a5). Different types of defects in cotton fabric (from b1–b3). Defect with polymer composite (c1,c2).
Figure 6
Figure 6
Example of identification and classification fabrics weave samples based on patterns.
See this image and copyright information in PMC

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