Spectroscopy and Machine Vision Solutions
NIR spectroscopy, or Near Infrared Spectroscopy, is an analytical technique for determining the chemical composition and certain physical properties of various materials and products based on the analysis of the interaction of optical radiation (light) with the molecular and atomic structures of these materials. For this reason, NIR is a very widespread technique in the analysis of food, grains, mixtures and pharmaceutical products, chemicals, cosmetics and even in other industries such as plastics for the identification of polymers, recycling, wood, among others.
In practical terms, NIR spectroscopy involves the development of machine learning models that convert spectral information into analytical parameter values, whether quantitative or qualitative.
Spectroscopy -and especially NIR spectroscopy- is becoming a versatile and robust tool in what is known as PAT (process analytical technologies), that is, the control of production processes and the quality of the finished product based on knowing, in real time and online, the composition and physical properties of what is intended to be produced and not only having information on process conditions.
For this reason, its applicability ranges from the exact determination of water content to the determination of the final mixing point, not to mention the degree of curing (polymerization), the identification of materials for separation, the validation of raw materials or even the detection of anomalies due to accidents or fraudulent practices.
The obvious advantage is the time needed to get the result and thus to make a decision on the ongoing process. With a spectroscopic probe the result is available in fractions of a second, whereas laboratory results can take from hours to days.
Also, as the determination is fully automatic, distorting factors in traditional analysis inherent in human intervention, both in sampling and analysis, are eliminated.
Inline NIR spectroscopy is generally not suitable for the determination of concentrations below 0.1% by weight, with 0.05% by weight being a fairly common threshold for applications of this technology when used inline or in real-time.
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