Near-infrared chemical imaging used for in-line analysis of functional finishes on textiles.

This paper demonstrates for the first time that near-infrared (NIR) chemical imaging can be used for in-line analysis of textile finishing processes based on impregnation. In particular, it was shown that this analytical method is sufficiently sensitive for the quantitative determination of the application weight of rather thin layers of finishing chemicals. Quantitative analysis of the data recorded by a hyperspectral camera (1320-1900 nm) was based on chemometric approaches using the partial least squares (PLS) algorithm. In this work, a flame retardant and a polyvinyl acetate-based stiffening agent applied to polyester or cotton fabrics, respectively, were studied with application weights in the range between about 1 and 50 g m-2. For both systems, the prediction error (RMSEP) was found to be about 1.5-2 g m-2. Averaging of the predicted individual values of the application weight of the finishes across the complete surface of the fabric resulted in a very close correlation with the corresponding reference values obtained by gravimetry. Furthermore, NIR chemical imaging was used for the detection of remaining traces of a size (a processing agent) after washing, which had to be washed-out before subsequent processing steps. Results of the present investigations prove that even for very thin size layers between 0.4 and 5.5 g m-2 the application weight can be predicted with a precision of about 0.4 g m-2. Apart from the quantitative determination of the application weights, the use of NIR chemical imaging for the analysis of finished textiles was mainly directed towards the investigation of the spatial distribution or the homogeneity of the applied colorless finishes across the surface of the fabrics. It was shown that this method is able to detect and visualize various inhomogeneities on the finished textiles resulting for instance from processing defects or from various technical effects that may influence the drying process and consequently the spatial distribution of the finish. Moreover, the distribution of traces of size that had been sprayed purposely on a washed polyester fabric could be detected. All measurements in the present study were carried under conditions that were very similar to those in typical technical processes (e.g. with respect to line speed). Therefore, the outstanding performance of the method opens an immense potential for application in process and quality control.

Near-infrared chemical imaging used for in-line analysis of inside adhesive layers in textile laminates.

This paper demonstrates for the first time that near-infrared (NIR) chemical imaging can be used for in-line analysis of textile lamination processes. In particular, it was applied for the quantitative determination of the applied coating weight and for monitoring of the spatial distribution of hot melt adhesive layers using chemometric approaches for spectra evaluation. Layers with coating weights between about 25 and 130 g m(-2) were used for the lamination of polyester fabrics and nonwovens as well as for polyurethane foam. It was shown that quantitative data with adequate precision can be actually obtained for layers applied to materials with significantly heterogeneous surface structure such as foam or for hidden layers inside fabric laminates. Even the coating weight and the homogeneity of adhesive layers in composites consisting of black textiles only could be quantitatively analyzed. The prediction errors (RMSEP) determined in an external validation of each calibration model were found to range from about 2 g m(-2) to 6 g m(-2) depending on the specific system under investigation. All calibration models were applied for chemical imaging in order to prove their performance for monitoring the thickness and the homogeneity of adhesive layers in the various textile systems. Moreover, they were used for the detection of irregularities and coating defects. Investigations were carried out with a large hyperspectral camera mounted above a conveyor. Therefore, this method allows large-area monitoring of the properties of laminar materials. Consequently, it is potentially suited for process and quality control during the lamination of fabrics, foams and other materials in field-scale.

The effect of different gloss levels on in-line monitoring of the thickness of printed layers by NIR spectroscopy.

Near-infrared (NIR) reflection spectroscopy was used for monitoring the thickness or rather the coating weight of thin printed layers of transparent oil-based offset printing varnishes in a range from 0.5 to 5 g m(-2). Quantitative analysis of the spectral data was carried out with partial least squares regression. Surface properties such as the gloss were found to strongly affect the prediction of the coating weight. This influence was minimized by the development of calibration models, which contained spectra of layers with a broad range of gloss levels. The prediction error of these models was in the order of 0.12 to 0.16 g m(-2). In-line measurements were carried out at a sheet-fed offset printing press in order to test the performance of the models under real process control conditions. Varnishes were applied to paper at printing speeds of 90 or 180 m min(-1). A close correlation between the predictions from in-line NIR spectra and the reference data from gravimetry was observed regardless of the specific degree of gloss of the layers (errors between 0.15 and 0.17 g m(-2)). The results clearly prove the efficiency of NIR reflection spectroscopy for quantitative investigations on thin layers in fast processes such as printing and demonstrate its analytical potential for quality and process control.

In-line monitoring of the thickness of printed layers by near-infrared (NIR) spectroscopy at a printing press.

In this work, it is demonstrated that the coating weight of printed layers can be determined in-line in a running printing press by near-infrared (NIR) reflection spectroscopy assisted by chemometric methods. Three different unpigmented lacquer systems, i.e., a conventional oil-based printing lacquer, an ultraviolet (UV)-curable formulation, and a water-based dispersion varnish, were printed on paper with coating weights between about 0.5 and 7 g m(-2). NIR spectra for calibration were recorded with a special metal reflector simulating the mounting conditions of the probe head at the printing press. Calibration models were developed on the basis of the partial least squares (PLS) algorithm and evaluated by independent test samples. The prediction performance of the developed models was examined at a sheet-fed offset printing press at line speeds between 90 and 180 m min(-1). Results show an excellent correlation of data predicted in-line from the NIR spectra with reference values obtained off-line by gravimetry. The prediction errors were found to be ≤ 0.2 g m(-2), which confirms the suitability of the developed spectroscopic method for process control in technical printing processes.

Simultaneous in-line monitoring of the conversion and the coating thickness in UV-cured acrylate coatings by near-infrared reflection spectroscopy.

Near-infrared (NIR) reflection spectroscopy was used for in-line analysis of the conversion and the coating thickness (5-20 µm) of UV-cured clear and pigmented acrylate coatings. The quantitative evaluation of the recorded spectra was carried out by partial least-squares (PLS) regression, in particular with the PLS2 algorithm, which allows simultaneous prediction of both parameters. The efficiency of this method was investigated in roll coating experiments at line speeds up to 100 m min(-1). It was shown that the method is able to compensate for the effect of accidental variations of the coating thickness, which inevitably occur upon changes of the line speed, on the prediction of the conversion. Accordingly, the conversion could be determined with a precision of ±2...3%, whereas the error in the measurement of the thickness was found to be about 0.5-1 µm.

Monitoring of the thickness of ultraviolet-cured pigmented coatings and printed layers by near-infrared spectroscopy.

Near-infrared (NIR) reflection spectroscopy was used for the determination of the thickness or the coating weight, respectively, of white-pigmented acrylic coatings and layers of printing inks. The thickness of coatings was studied in the range from 5 to 60 microm, whereas the coating weights of the printed layers covered a range between 1 to 5 g m(-2). Quantitative analysis of the spectral data relied on partial least squares (PLS) regression. A thickness gauge or gravimetry, respectively, were used to obtain reference data. Calibration models were typically based on six factors. The corresponding root mean square errors of prediction (RMSEP) were found to be on the order of 0.87 for coatings and 0.38 for printed layers. Monitoring of the coating thickness under process conditions was carried out on a pilot-scale roll coating machine. In order to simulate thickness changes during a coating process, either the nip between the applicator rolls or the web speed was varied. Data with high precision (standard deviation approximately 1 microm for coatings, approximately 0.4 g m(-2) for printed layers) and an excellent correlation with off-line reference data were obtained. The investigations have shown that NIR spectroscopy can be used for process control in coating and curing technology.

Determination of the thickness of silazane-based SiO(x) coatings in the submicrometer range by near-infrared reflection spectroscopy.

The thickness of thin silica layers in the submicrometer range, i.e., between about 150 and 700 nm, was determined by near-infrared (NIR) reflection spectroscopy. Silica layers were prepared by spin-coating of perhydropolysilazane (PHPS) on silicon wafers or poly(ethylene terephthalate) (PET) foil and subsequent conversion of the PHPS into SiO(x) by vacuum ultraviolet (VUV) irradiation at 172 nm. Since the NIR spectra of the inorganic layers do not show overtone and combination bands, analysis is based on tiny differences in reflectance of samples provided with layers of different thicknesses. Quantitative investigations were carried out by use of chemometric approaches on the basis of the partial least squares (PLS) algorithm. Optimization of the chemometric models was achieved by systematic variation of the preprocessing of the spectra before application of the PLS regression. The root mean square error of prediction (RMSEP) and the coefficient of determination R(2) were used for the evaluation of the various pretreatment strategies. Reference data for the calibration procedures were obtained by means of gravimetry. The maximum error for the determination of the thickness was estimated to be on the order of 20%. The method was used to monitor the homogeneity of the thickness of silica layers made by use of a pilot scale coating machine. Thickness profiles recorded by NIR spectroscopy showed clear differences between layers with uniform or non-uniform quality of the application. Moreover, a close correlation of the profiles with the average coating weights determined by gravimetry was found.