Nowadays, thanks to the electrospinning process, polymeric fibers in nanoscale diameters (10–500 nm) are easily producible. During the last decade, the electrospinning technique has been greatly investigated and developed. One of the most important fields of study on the electrospinning process is the influence of effective parameters on electrospun nanofibers and nanoweb properties. In this study, using polyamide-6 (PA-6)/formic acid polymer solution, three important parameters of the electrospinning process, including polymer solution concentration, needle-tip-to-collector distance, and needle length, were precisely studied. The solution concentration is a very important parameter that affects the nanowebs’ homogeneity and nanofibers’ diameter evenness. Scanning electron microscopy (SEM) analysis of the electrospun nanowebs showed that among five polymer solution concentrations (5, 10, 15, 20, and 25 wt%), 25 wt% was more suitable and provided the homogeneity and reproducibility of PA-6 nanowebs. It has been found that the needle-tip-to-collector distance had a considerable influence on the nanofibers’ diameter and the nanoweb collection zone. Morphological investigation and statistical studies showed that the nanofibers’ diameter increased with the reduction of the needle-tip-to-collector distance. Moreover, the average diameter of the nanoweb collection zone decreased by the reduction of this distance. The effect of needle length on the nanofibers’ morphology and nanowebs’ collection zone was investigated. Statistical analysis of the obtained results revealed that the increase of needle length significantly increased the average nanofibers’ diameter. Inversely, the diameter of the nanoweb collection zone reduced when needle length increased. All previously mentioned studies helped to define the optimal electrospinning condition to produce the bead-free, non-branched, and homogeneous PA-6 electrospun nanofibers and nanowebs.

Fabric inspection has an importance to prevent the risk of delivering inferior quality product. Until recently, the process was still undertaken offline and manually by humans, which has many drawbacks. The continuous development in computer technology introduces the automated fabric inspection as an effective alternative. In our work, Fast Fourier Transform and Cross-correlation techniques, i.e. linear operations, are first implemented to examine the structure regularity features of the fabric image in the spatial domain. To improve the efficiency of the technique and overcome the problem of detection errors, further thresholding operation is implemented using a level selection filter. Through this filter, the technique is able to detect only the actual or real defects and highlight its exact dimensions. A software package such as Matlab or Scilab is used for this procedure. It is implemented firstly on a simulated plain fabric to determine the most important parameters during the process of defect detection and then to optimize each of them even considering noise. To verify the success of the technique, it is implemented on real plain fabric samples with different colors containing various defects. Several results of the proposed technique for the simulated and real plain fabric structures with the most common defects are presented. Finally, a vision-based fabric inspection prototype that could be accomplished on-loom to inspect the fabric under construction with 100% coverage is proposed.

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