Categoria: Digitalization

Industry-4-0-it 20 Dicembre 2022

NIR Chocolate Analyser: Viscosity and Particle Size in Real-Time

Espectroscopía NIR en la producción de chocolate
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NIR Chocolate Analyser: NIR spectroscopy applications in chocolate production

 

In this article we will address real-time analysis using NIR spectroscopy for the determination of viscosity and particle size in the chocolate industry, two key product parameters to ensure the highest quality and unique smoothness and taste that make chocolate such a popular food among consumers.

 

NIR spectroscopy (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. NIR is therefore a widespread technique for physical-chemical control in industry, both in laboratory and real-time process analyzers.

 

In chocolate production, the particle size and composition of the ingredients play a fundamental role in shaping their rheological behavior and sensory perception. The flow properties of chocolate are important because product quality control is a necessity. If the viscosity is too low, the weight of the chocolate on the coated candy will also be too low. When it is too high, bubbles may form inside the chocolate bar. In addition, the taste of the chocolate in the mouth is affected by the viscosity; therefore, the consumer’s tongue may perceive incorrect flow properties. Furthermore, the perceived taste depends on the order and speed of contact, which are related to viscosity and melting speed.

 

Why does the viscosity have to be right?

 

  • It guarantees the texture, flavor and quality of the chocolate.
  • It provides a uniform flow speed (homogeneity), which is very important if there are coatings of nuts, almonds, cookies or others on the chocolate bars.
  • Reduces typical defects and processing errors (breaks, cracks and others).
  • Mitigates the inherent variability in the line, thus reducing raw material and viscosity modifying ingredients costs.

 

However, up to now, most of the industry performs a traditional control, either with temperature measurements and adjustments -which we will not discuss in this article-, sampling and laboratory analysis, a viscometer or other monoparametric sensors.

 

Unlike the above, IRIS Technology’s Visum® process analyzers are multi-parametric and provide the added value of monitoring the entire product flow and reporting directly to the control systems or PLC of the area to generate the necessary corrections in the process, thus ensuring the highest possible homogeneity at all times.

 

NIR analysis in the chocolate production process

 

The chocolate production process consists of four main stages: mixing, refining, conching and tempering.

The conching process (dry, plastic and liquid) is one of the most critical and important in chocolate production, where the mixture becomes a fluid liquid and where acidic flavors are eliminated and the cocoa paste is refined to the desired texture and flavor. This structural transition is achieved through the use of thermal and mechanical energy and the incorporation of different ingredients that break up, disintegrate and disperse the large agglomerates until the molten chocolate is obtained.

 

In this process, a Visum NIR In-Line™ multiparametric analyzer was used for the on-line determination of viscosity in the range 2000-16000 cps and where an R2 >0.96 was obtained. In addition, its results were correlated with in-line moisture measurements since an increase in the moisture content of chocolate leads to an increase in its viscosity and an excess of moisture could lead to the formation of sugar agglomerates thus affecting the final texture of the chocolate. NIR is a particularly sensitive method for moisture determination.

 

Picture 1: Visum NIR In-Line™ Analyser – Conching process monitoring.

Espectroscopía NIR en la producción de chocolate

While this application was developed on milk chocolate, one would expect that no major differences in compositional changes would be found.

A limitation of the Visum NIR In-Line™ process analyzer is that it does not provide the particle size distribution but the average value resulting from continuous analysis every few seconds. In the case of milk chocolate, a range of 0 to 160 µm was monitored and a correlation coefficient of 0.92 was obtained.

 

Table 1: Particle size and viscosity with NIR.

 

Once the chocolate is properly cooked, it must be tempered and this stage consists of crystallizing a small proportion of the fat, which facilitates its proper solidification after molding. Tempering consists of several stages: first, the chocolate is completely melted (usually at 50⁰C), then cooled to the crystallization point (32-34⁰C), then the temperature is further reduced until crystallization occurs (25-27⁰C) and finally, the chocolate is subjected to a temperature increase to destroy any of the unstable crystals (29-32⁰C). Although a detailed analysis was not performed due to the lack of samples at the different tempering stages and the difficulty of obtaining them for the calibration of the predictive model, the image below validates on-line infrared spectroscopy as a reliable method for the determination of the tempering level.

 

Figure 1: “Tempered” “Untempered” classification by infrared spectroscopy – Exploratory analysis.

NIR spectroscopy in chocolate production

 

These tests open a development window to further develop a classificatory and/or quantitative model capable of determining, by means of dedicated machine learning tools, the tempering level of chocolate in real time without having to resort to an offline method such as the temperature meters (tempermeter) commonly used in the industry.

 

We hope you found this article on new applications of infrared spectroscopy in the chocolate industry useful. For further information, we invite you to contact us by email at info@iris-eng.com.

Di IRIS Technology Solutions
Environment-it, Industry-4-0-it, Innovation-it 15 Dicembre 2022

Recycling of multilayer and composite plastics

Reciclaje de plásticos multicapa
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Plastics bring value as convenient, versatile and lightweight consumer products, as well as advanced performance in high-end applications such as automobiles. However, despite their usefulness, it is clear that linear, single-use consumption of plastics is incompatible with Europe’s transition to a circular economy. This model prioritises the reuse and recycling of resources, with the aim of reducing waste and retaining as much value as possible.

In terms of plastics recycling, some progress has been made. For example, 41.5% of the plastic packaging waste generated was recycled in 2018. This is still not enough to achieve full circularity, especially in the recycling of multilayer plastics that are difficult to separate. In addition, it is essential that recycling technologies keep up with new materials entering the market

Advanced plastics recycling

The EU-funded MultiCycle project aims to develop a pilot plant for industrial recycling and treatment of multilayer plastics. This plant focuses on two important industrial segments that pose a challenge for recyclers: multilayer packaging/flexible films and fibre-reinforced thermoplastic composites of the type used in the automotive sector.

Technology selection

NIR and HSI-NIR are the techniques conventionally used for container sorting. The former is suitable for individual pieces of packaging prior to shredding and can also provide an initial assessment of suitability before moving on to the latter, which provides a mode of imaging. In the MultiCycle project, packaging materials were fed onto a conveyor in the form of flakes up to 5 cm and therefore HSI was the target technique for final implementation in the prototype incoming control system. However, point NIR spectroscopy was the target technique used for monitoring dissolved and recovered plastics during and after the CreaSolv® process, where no imaging capability is required. Complementary techniques such as LIBS and FTIR have also been preliminarily tested to detect other fractions such as AlOx or to enable the detection of black containers, which could improve the accuracy of monitoring when a full system is implemented.

Near Infrared Spectroscopy (NIRS)

NIR spectroscopy is a vibrational spectroscopic technique. In this region, absorption spectra are composed of overtones and combination bands with respect to the fundamental modes of molecules in the mid-infrared region. NIR radiation has a wavelength range of 900 to 2500 nm. The absorption bands in this region are broad, due to the high degree of band overlap. In addition, due to the selection rules of the phenomena, the signal intensity is ten to a thousand times weaker than signals in the mid-infrared region. However, this lack of intensity and the high band overlap is compensated by its high specificity. The specificity of NIR spectroscopy is based on the fact that NH, OH and CH bonds strongly absorb radiation at these wavelengths, which makes it an optimal tool for the study of organic compounds and polymers. In addition, the use of multivariate methods for the analysis of spectral data has made it possible to exploit the full potential of the technique for identification, discrimination, classification and quantification purposes.

Hyperspectral imaging system in the shortwave infrared region (HSI-SWIR)

Current technologies for the monitoring and classification of solid plastic waste in the near-infrared region have incorporated hyperspectral cameras in their configuration. They allow, instead of collecting a single spectrum, to record a hyperspectral image (HSI) of the sample (hyperspectral cube), which contains not only the spatial location of the sample, but also its chemical composition and distribution. In this regard, several publications and technological developments have been made using HSI-SWIR for the classification and identification of plastics.

A basic hyperspectral imaging system, shown in Fig.3, includes in its configuration, a sensitive sensor (CCD camera); a broadband illumination source; a spectrometer, which separates the backscattered/transmitted light into its different wavelengths and, when required, a conveyor belt for sampling. In this case, it should be noted that the conveyor belt must be synchronised with the recording speed of the CCD sensor for proper image acquisition. A hyperspectral system provides a hypercube as output. A hypercube is a set of data arranged in three dimensions, two spatial (an XY plane) and one spectral (𝜆, wavelength), as depicted below.

Measurement parameters:

The most relevant parameters for hyperspectral cube recording can be summarised as follows:

  • Camera frame rate (fps)
  • Transporter speed (m/s)
  • Camera-transporter distance (cm) and collection time (µs). These parameters are interrelated and must be optimised to obtain good quality recorded spectra.

The hyperspectral images were recorded with a SWIR camera operating in the range ∼900-1700 nm, at a frame rate of 214 fps, with an integration time of 350𝜇s and a transporter speed of 25m/min.

Reciclaje de plásticos multicapa

Figure 1: (Left) Sample set no. 1. Includes flexible plastic films of PE, PP, PA and PET. Single and double combinations of these polymers (i.e. polymer A/polymer B) were included. (Right) Classification image made by a PLSDA model.

Project conclusions

The HSI monitoring system has been able to provide a good approximation of the percentage of polymer content in a multilayer polymer sample. In the worst case, the most abundant polymer present in the sample is predicted, so with large batches, the final percentages would be fairly accurate. In terms of monitoring the dissolution process, only 1 polymer and 1 solvent were provided for testing in IRIS. The results obtained with Visum Palm™ were as expected, but no process models were tested over time. The dissolution control was not performed due to problems with the viscometer installed in LOEMI. For this reason, there are no further results in this section.

For the monitoring of the automotive samples, the selected technique was LIBS. The optimisation of LIBS was complicated, as it was the first time it was used. Models were run by changing different parameters to select the best conditions. The PATbox tool for LIBS did not allow data acquisition at the same speed as the LIBS software, so the models had to be modified. Finally, the models were calibrated and tested to predict the type of fibres in the black plastics PP and PA. The results obtained in the 3 batches were satisfactory, as the predictions given by the models (chemometrics and machine learning) were close to the real content. Some tests were performed to differentiate between PP and PA, but the classification rate was around 80% of good predictions. In general, mislabelling and soiling of the samples were not very useful for the development of the prediction models.

Di IRIS Technology Solutions
Ai-it, Industry-4-0-it 6 Ottobre 2022

Detection of defects in fish loins using machine vision and deep learning

detection of defects in fish
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Detection of defects in fish loins using machine vision and deep learning

Machine vision technology assisted by deep learning is an important ally for fish processing and distribution factories that makes it possible to inspect 100% of the production to ensure high standards of quality and food safety of the product that finally reaches the consumer’s table.

The new Visum DeepSight Loins™ system from IRIS Technology is a machine vision system designed for the detection of physical surface defects in fresh and frozen fish loins that makes it possible to automate the inspection of loins, quantify, classify and reject non-conformities to ensure superior quality of the final product.

Machine Vision and Deep Learning

While traditional computer vision systems learn to classify and recognize features from a set of historical images in order to correctly predict and classify new ones, deep learning neural networks are able to learn features from pixels (individual and group) and have an input layer (the raw image), a series of intermediate layers that are interconnected to simulate how a biological brain works, and an output layer that provides classification/prediction. Deep learning neural networks are especially good at learning complex features and segmenting an image at different levels of abstraction (edges, different colors, shapes, objects), including noise and probabilistic information.

Traditional machine vision that does not use this approach typically processes images but does not learn from the data, such as thermal imaging cameras, motion detection sensors, light intensity sensors, among others.

Detection of defects in fresh and frozen fish loins

Detection of defects in fish loins

The Visum DeepSight Loins™ system is capable of detecting numerous defects in fish loins such as bruises, blood stains, gapping (i.e. openings or tears in the musculature), skin remnants, superficial bones or other superficial foreign bodies that may reach the processing line. It also has built-in color measurement functionality under international CIELAB or L*a*b* standards, which is important as a quality parameter both on the surface and in relation to the freshness of the fish.

Visum DeepSight Loins™ has a high IP protection for easy cleaning of the line and has a built-in anti-reflective and anti-humidity system that allows it to operate normally on both fresh and frozen fish loins.

Usability, Operation and Communication

The Visum DeepSight Loins™ system incorporates 2 user levels: “Administrator” for modifying settings, working mode, adjusting rejection sensitivity or taking references and “Operator” for automatic operation mode of the device.

The system is complemented by a trap door rejection that allows the ejection of non-conforming units for reprocessing or control by the operators.

The information and results of the analysis, such as the quantification of defects and rejects by class, lot information and the quantity of products inspected, can be viewed on the built-in computer module, on a computer connected to the network or on the plant’s own information management system. In addition, automatically generated reports can be exported in different formats.

The sensitivity adjustment functionality is an essential tool for calibrating the level of rejection of the device in the event of certain defects and thus regulating the system’s operating performance without causing any inconvenience to the line’s production capacity.

For more information about the device and inquiries write to info@iris-eng.com.

Di IRIS Technology Solutions
Environment-it, Industry-4-0-it 22 Settembre 2022

Sorting and quantification of organic waste

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Sorting and control of organic waste in biogas production

In this article we will discuss how it is possible to optimize the treatment of organic municipal solid waste used for biogas production with hyperspectral technology to improve the quality and yield of biomethane, based on the application that IRIS Technology has developed for the Biomethanization Plant of Las Dehesas (FCC), in Madrid based on its Visum HSI™ organic waste sorting system.

The problem of organic waste separation

In the last year alone, the Spanish economy generated more than 138 million tons of waste, of which only 15% was reused to manufacture new products, by-products or raw materials. Moreover, Spain is still below the EU target of recycling 50% of Municipal Solid Waste (MSW) also stipulated in Law 22/2011 on waste and contaminated soils. Despite the fact that some communities have managed to achieve high recycling rates, organic waste remains one of the main headaches for the Administration and waste treatment and recycling plants.

This is because a large part of the organic fraction of municipal solid waste (MSW) is contaminated with inorganic materials, mainly packaging – another of the great challenges of recycling – and plastics, where optical sorting and spectroscopy technologies have become great allies.

Biogas production

One of the main destinations for the reuse and revaluation of organic waste is the production of biogas, which is converted in biomethanization plants into biomethane, a type of gas suitable for injection and commercialization in the gas network, complying with certain quality and safety standards. In these plants, such as the one in Las Dehesas in Madrid, the organic fraction of the solid waste is treated to avoid high percentages of “improper” (presence of inorganics) which, once in the biodigesters, cannot be used in the fermentation process and, consequently, the result is a suboptimal quality and performance of the process and the final product.

To this end, IRIS Technology, within the framework of the European Scalibur project, installed an HSI™ hyperspectral imaging system in the FCC line in order to quantify and classify waste according to whether it is organic or inorganic. Beyond the various intermediate controls, the removal of bulky waste, plastic bags, etc., knowing the percentage of organic waste is a key parameter for adjusting the biological process that takes place in the digesters.

Scalibur_HSI_clasificador de residuos orgánicos

Separation of organic and inorganic waste

The organic waste sorter Visum HSI™ based on hyperspectral technology allows to obtain real-time data on the percentage of organic and inorganic waste, as well as to locate the different components on the conveyor belt, to know the average composition of the waste, to monitor the evolution of the waste composition over time and to extract useful information for decision making in waste management, production and circularity.

Sortierung von organischen

The implementation of the HSI system has allowed FCC to monitor in real time the waste in order to improve the flow corresponding to the organic fraction and, consequently, a fermentation process with a lower level of impurities, maximizing the key parameters of the fermentation process.

For more information about this project and the technology, please visit Scalibur’s website or write to our mail: news@iris-eng.com

Di IRIS Technology Solutions
Industry-4-0-it 5 Settembre 2022

Real-time monitoring of biofuels with NIR spectroscopy

biothenol et nir
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In this post we will discuss NIR spectroscopy monitoring of the bioethanol production process and how on-line NIR is an important ally for real-time monitoring of fermentation results, final quality or purity, process inhibitors and other analytes of interest for the production of high value-added by-products for the industry.

Bioethanol and NIR

Bioethanol is a type of fuel obtained from the fermentation of organic matter rich in sugars and starch, such as corn, sugar beet, sugar cane, among the most popular ones used worldwide. It can even be produced from solid urban waste and biomass with no food value, known as “second generation” bioethanol or lignocellulosic bioethanol, which solves the added problem of giving a productive destination and added value to the organic waste we discard, converting it into biofuel.

As a result of the action of yeasts and enzymes in the fermentation process, and after distillation, bioethanol is obtained for use as biofuel and for blending with fossil fuels. From the rest of the components, by-products are obtained that can change depending on the raw material used in the process, for example, from dry milling, animal feed can be obtained due to its high protein content, or other by-products from wet milling such as corn oil, syrups, to mention a few. Also, from lignocellulosic biomass, by-products can be obtained for reuse in other industries, such as methanol and acetic acid.

Quality control of the bioethanol production process.

Bioethanol quality control is very important to ensure the purity of the product resulting from the process and the valorization of by-products for reuse in other industries. In most biorefineries, the control of reducing sugars (glucose) and ethanol is carried out using analytical techniques offline, i.e. in the laboratory, using high performance liquid chromatography (HPLC), which takes time and resources, or with benchtop NIR spectroscopy, which, unlike HPLC, provides accurate results in just seconds, but is still an unrepresentative and off-line sampling method.

Bioethanol and NIR in line

However, few biorefineries have bet on the introduction of in-line NIR technology to monitor the fermentation process, distillation, the action of process inhibitors or the control of by-products.

In this sense, IRIS Technology has developed several applications for process control in biorefineries using the Visum NIR In-Line ™ analyzer and the portable (handheld) Visum Palm™ NIR.

Table 1: Inline glucose and ethanol content prediction using a Visum NIR In-Line ™ analyzer.

Monitorização de biocombustíveis

Table 1 shows the main parameters, ranges and production stages in the manufacture of lignocellulosic bioethanol at IMECAL‘s Perseo Biotechnology plant, where municipal solid waste is transformed into bioethanol.

The lignocellulosic biomass delignification process was also monitored to free cellulose from hemicellulose and lignin and thus achieve depolymerization of carbohydrates to produce simple sugars and fermentation to produce ethanol.

Table 2: The pretreatment process consists of a combination of organosolvation with steam explosion (performed by LTU, Lulea Univ. of Technology). Parameters monitored: Lignin, cellulose and hemicellulose content.

bioethanol und nir tabelle

Another application developed in the framework of this project was the monitoring by Visum NIR In-Line ™ of the process of obtaining reducing sugars from hemicellulose present in lignocellulosic residues. In particular, it is shown that it is possible to control inhibiting factors of the fermentation process, such as acetic acid.

Table 3: Parameters monitored: xylose, glucose, acetic acid content.

bioethanol und nir

The installations and tests carried out demonstrate the effectiveness and importance of introducing in-line NIR technology in biorefineries in order to have a more precise control of the different phases of the bioethanol production process, achieve higher quality and therefore increase biofuel efficiency.

Di IRIS Technology Solutions
Industry-4-0-it 10 Agosto 2022

Hyperspectral NIR: Applications in the Food Industry

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In this article we will address cross-cutting applications of hyperspectral NIR technology in the food industry with the aim of questioning our current production process and considering effective ways to optimize it with in-line technology. We will not go into detail on each of the applications, but if you are interested in learning more, you can read the following post where we see a case of application in fried pastries to mitigate indeterminate fat variations in the process and optimize the use of raw material.

However, IRIS Technology’s hyperspectral NIR technology, Visum HSI™ opens a huge window of applications to the industry in process control, quality and food safety with an optical industrial system that is able to chemically monitor each product unit in real time and determine a large number of physical and chemical parameters simultaneously. A hyperspectral camera is equivalent, in practice, to having a spectrophotometer in every pixel.

Visum HSI™: pixel-by-pixel, spatially resolved chemical imaging

sistema di imaging iperspettrale

Fruit and vegetable industry

In this industry there are numerous non-destructive controls that can be performed with hyperspectral NIR technology. Among them we can mention ºBx, starch, dry matter that are relevant parameters to establish the degree of maturity and commercialization of fresh products, as well as pH, acidity, fat content, moisture or soluble solids that are part of the usual controls in the industry and that currently, as in most of the industry, are performed by traditional offline techniques (sampling and laboratory).

 

Likewise, hyperspectral NIR technology is effective for determining texture by levels, detecting and rejecting foreign bodies in the line and for sorting. In general terms, they are systems that can learn from a quantitative reference criterion or from a human expert when controlling a certain process. Therefore, as a non-destructive control method, it is an excellent alternative to classify and select products according to their composition in a fully automated way, providing greater value to the final product, for example, if you want to create a premium line.

Fish and seafood

Food safety controls for all seafood products are becoming increasingly stringent. In this context, the Visum HSI™ inline hyperspectral NIR technology facilitates the detection of foreign bodies coming from the seabed, such as shells, stones, other arthropods, net fragments, among others, which are visually little different from the product to be processed and can therefore escape visual inspection, or which, due to their low density, there are no useful detectors on the market. It is also possible to detect plastic packaging residues, even if they are transparent in fish fillets and slices. In addition to being able to quantitatively determine a large number of analytical parameters simultaneously (fats, proteins, acidity, among others), it is capable of detecting and classifying the application of sulfites or preservatives and the degree of freshness.

 

In case you are wondering, Hyperspectral NIR technology, at least as of 2022 and no other technology on the market that is in-line and continuous, is effective in quantifying histamine at the levels required by industry and regulations (<50 ppm).

 

In the next post you can read more about foreign body detection with our hyperspectral systems.

Nuts, grains and pulses

In nuts (almonds, pistachios, peanuts, among many others) it is possible to replace conventional laboratory analysis and combine these with in-line imaging spectroscopy vision techniques. This is useful for real-time control of chemical parameters such as moisture, fat, fibers, acidity, as well as to detect and separate foreign bodies: corn that appeared on the line, wood, plastics, stones. For visible defects such as spotting, moth-eaten, other grain defects or fruit with skin, it is required to complement with a machine vision system, such as Visum DeepSight™ .

Bread and pastries

We have covered this topic in our blog, focusing on fat control, a critical input for manufacturer costs, consumer trends and food taste and texture. However, Visum HSI™ technology can monitor unit by unit of product other critical parameters, such as moisture or sugar content and more importantly, interact through the line PLC with machinery and the plant management system.

In conclusion, hyperspectral technology, coupled with the breakthrough in optical systems in recent years, opens up a wealth of opportunities for food safety in industrial processes.

I hope this article on hyperspectral NIR technology in the food industry has been useful and applicable.  As always, we invite you to send us your questions, comments and suggestions to our e-mail address info@iris-eng.com.

Di IRIS Technology Solutions
Industry-4-0-it 26 Luglio 2022

Detection of foreign bodies in the production line

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Detection of foreign bodies in the production line

In this post we will address a recurrent and transversal problem in the industry related to food safety and security: the presence of foreign bodies in the production line and we will see how we can prevent this from happening with viable techniques at industrial level such as imaging spectroscopy or also known as Hyperspectral NIR or Hyperspectral Imaging (HSI).

Deteção de corpos estranhos

What do we mean by foreign bodies?

In general terms, for manufacturers, “foreign body” is anything that should not be in the production line, whether it is an organic element (bone, skin, shells, other food that is not the product to be packed, pieces of wood, wood chips to mention a few) or inorganic elements such as metals, screws, plastics, cardboard, paper, etc. The rule is that everything that is not product should not be there, as it is a problem that can alter the quality of the final product and therefore generate economic losses, as well as being a risk for the health of consumers and the image of the company.

State of the art

Until now, foreign body control in the vast majority of industries, whether food or non-food, has been carried out by visual inspection. That is to say, with operators on the production line watching the product flow and extracting any foreign bodies that may have crept in during the manufacturing process. On the one hand, X-ray detection systems, which have already been implemented in practically all industries, guarantee that no conductive elements, i.e. metals, will pass through the line, but do not exempt us from the possibility of non-conductive and low-density elements such as plastics, paper, cardboard, stones, glass, rubber, among others, which may appear and which are undetectable with this technology.

On the other hand, traditional machine vision, for the detection of foreign bodies, has important limitations due to the enormous variability that can exist in terms of type, shape, colour or size, which results in a high false positive rate (rejected “good” product). However, on a more contemporary level, artificial vision assisted by deep learning or machine learning algorithms is a technology that has its benefits at certain points in the line, such as in packaging, where it is useful for detecting the presence of certain physical contaminants.

Foreign body detection with hyperspectral NIR

If we have to say that by 2022 there is a sufficiently mature, easily integrated online and economically viable technology for detecting foreign bodies, it is hyperspectral NIR technology.

This technology is an extension of traditional machine vision in two ways: Firstly, instead of the usual three colour channels in machine vision, hyperspectral imaging uses up to hundreds of channels, making it possible to see very subtle differences. Secondly, hyperspectral cameras incorporating these systems often have an extended spectral range beyond the visible, i.e. into the infrared, where chemical composition is much more evident than in the visible range.

Hyperspectral imaging can therefore be seen as a paradigm shift in vision systems and as a source of abundant, high-quality data to feed vision systems based on artificial intelligence algorithms. In practice, having a hyperspectral camera is equivalent to having a spectrophotometer in each pixel, i.e. it allows obtaining chemical information on the composition of the product pixel by pixel and product unit by product unit, providing a clear image of the whole inspected area and distinguishing according to its chemical composition what is product and what is not, regardless of its shape, size or typology. It has a limitation; as it works with light and as this has a minimum penetration in the material, everything that is not superficial will not be detected. To prevent this from happening, at IRIS Technology, we integrate vibration or velocity to generate dispersion of the product in the section where the hyperspectral detection system is located.

The Visum HSI™ system can operate at a speed of up to 50 m/min detecting foreign bodies up to 3 mm² and with a minimum density of 0.7g/cm³. It is therefore a “compromise” solution between line speed, processing power and minimum detectable size.

Détection de corps étrangers

Visible NIR and chemical composition

IRIS Technology’s turnkey systems, such as the Visum HSI™ analyser, can operate in two spectral ranges, Vis-NIR (400 to 1000 nm) or SWIR (900-1700 nm). The application of one camera or the other in the hyperspectral system will depend on the manufacturer’s need. If it is only a question of detecting foreign bodies, a Vis-NIR camera will be used, since in this range there is enough chemical information to detect what is a product and what is not. On the other hand, if you also want to quantify or classify product composition parameters other than moisture, such as fats, proteins, fibres, acidity or other parameters, a camera working in the SWIR range will be used to obtain reliable and robust results like those of the laboratory.

Some final clarifications

It is important to note that hyperspectral technology is not useful for detecting foreign bodies inside the product, regardless of the product in question, because as mentioned above, the light has minimal penetration.

Although it is not the subject of this article, we believe it is important to clarify that hyperspectral technology is also not useful for the detection of microbiological activity at the concentrations and limits required by regulatory bodies (ppm), where the only viable analytical technique is still the swap or Elisa.

Therefore, at IRIS Technology we are constantly investing in R&D to increase the analytical capabilities of our systems, as well as to develop advanced solutions that are reliable and feasible to integrate into the production line.

Di IRIS Technology Solutions
Industry-4-0-it 21 Luglio 2022

Thickness control of multilayer films with Visum® technology

Films multicouches
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More than 60% of the films used in food packaging are transparent multilayer films

In recent years, multilayer film structures have made it possible to extend their applications in the packaging of food products, allowing the organoleptic and nutritional qualities of the product to be optimally preserved. Today, more than 60% of the films used in food packaging are transparent multilayer films obtained from coextrusion, where the different polymeric layers respond to certain needs: barrier against water, water vapor, temperature, sealability, mechanical resistance, among others.

Film thickness and its uniformity is a critical parameter to control changes in the structure without compromising the performance requirements of the same and therefore the on-line control of thickness is of great importance for designers and manufacturers of multilayer films. Up to now, this control has been done with offline methods that are not compatible with continuous production, such as using a micrometer or optical microscopy. There are also sensors on the market to control the uniformity of single-layer films, but there is no tool that is really effective in industrial and technological terms for controlling the thickness of multilayer films and guaranteeing their uniformity.

The patented Visum Thickness™ sensor technology is a tool for single or multipoint thickness control of thin translucent multilayer films, layer by layer, total thickness and in real time, which makes it suitable for different color coatings on substrates of different nature and therefore has potential uses in multilayer barrier packaging, but also coated textiles, metals, among others.

Some additional features of Visum Thickness™:

  • No calibration required.
  • Number of layers: unlimited.
  • Spot size: 5 mm. 
  • Inspection: single or multi-point.
  • Probe-to-film distance range: 5-30 cm.
  • Dimensions: 300 x 200 x 150 mm3 
  • Weight: 7 kg 
  • Power supply: 240 VAC, 100 W 
  • Operation: slave or continuous.
  • Communication: Wifi / Ethernet / Profinet / Profibus
  • Visum ® software
  • Embedded computer

 

IRIS Technology is a European leader in the development and manufacturing of industrial solutions with applied photonic technologies.

 

For more information, write to info@iris-eng.com

Di IRIS Technology Solutions
Industry-4-0-it 14 Luglio 2022

WhiteCycle: Europe’s big bet to recycle more than 1.8 million tonnes of plastic textile waste annually.

plastic
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What is WhiteCycle?

On 1st of July, the WhiteCycle project was launched with the aim of developing a circular solution to convert plastic textile waste into high added-value products. This unprecedented European project is coordinated by Michelin and is made up of a consortium of 17 public and private entities, co-funded by the European Commission’s Horizon Europe programme. IRIS Technology is a key member of the consortium as a European leader in the design of advanced optical systems.

WhiteCycle's objectives

By 2030, WhiteCycle is expected to adopt and deploy a circular solution to recycle more than 2 million tonnes of textile plastic waste annually, particularly the third most used plastic PET (Polyethylene Terephthalate). This is expected to reduce CO2 emissions by around 2 million tonnes per year and avoid the landfilling or incineration of more than 1.8 million tonnes of plastic each year.

Currently, complex textile-containing waste (PET) from various sources, such as multi-layer clothing, hoses or tyres, is difficult to recycle. However, soon all these products could be recyclable thanks to the results of the project. Thanks to the WhiteCycle project, PET 2 feedstock could be reused to create high-performance products. This would be possible thanks to a viable circular value chain.

This project will develop processes needed throughout the industrial value chain.

  • Develop and/or use innovative sorting technologies. This would allow an increase of the PET plastic content of complex waste streams in order to be able to process them better.
  • The recovered PET would be pre-treated for its content. This would be followed by an innovative process based on recycling enzymes to break down into pure monomers and pure monomers in a sustainable way.
  • Repolymerisation of the recycled monomers into a new plastic.
  • Manufacturing and verifying the quality of new products produced from recycled plastic materials.

WhiteCycle has an overall budget of ¤9.6 million and receives European funding of approximately ¤7.1 million. The companies participating in the project are located in five countries:

  • Germany: DITF, Estato, IPoint
    Spain: IRIS Technology Solutions, Inditex
    France: Axelera, Carbios, Dynergie, ERASME, IFTH, Michelin, PPRIME, Synergies TLC,UNIV POITIERS
    Norway: HVL, Mandals
    Turkey: Kordsa

IRIS Technology's role in White Cycle

There has long been an urgent need to develop a final circular solution for the industry to transform complex textile plastic waste into higher value-added products (new plastic for hoses, tyres and clothing).

As Europe’s leading designer of advanced optical systems, IRIS Technology will lead the development of a system capable of real-time monitoring and identification of textile PET waste for recycling. For this purpose, IRIS will implement hyperspectral NIR technology using the Visum HSI™ industrial analyser, which employs 2D imaging spectroscopy and extracts pixel-by-pixel and unit-by-unit chemical information from product passing over the line to detect chemical composition, content and spatial distribution. Finally, the HSI system for the detection and sorting of plastic textile waste will be validated on an industrial scale to facilitate its incorporation into recycling lines across Europe.

Di IRIS Technology Solutions
Digitalization-it, Environment-it, Industry-4-0-it 22 Giugno 2022

Identification and characterization of polymers with portable NIR technology

Charakterisierung von Polymeren
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The plastic recycling industry presents an enormous complexity for the separation of the different types of polymers and among the most widespread techniques for this purpose are the spectroscopic ones. We will not discuss all of them in this article, as it would imply diving into the world of R&D, new in-line detection technologies and their practical or economic limitations in trying to reach the aspirational standards in terms of recycling and circularity of the European Union.

However, following an eminently practical approach, an agile and effective way to identify different compounds or plastic mixtures for recycling or industrial reuse is through NIR spectroscopy. This technique is based on the interaction of light with matter and makes it possible to observe the different absorbances produced by the vibrations of the bonds between the atoms of the polymers. As a result, a characteristic spectrum of each type of plastic is obtained, which can be quantified and classified by means of a predictive machine learning model.

The Visum Palm™ handheld NIR analyzer.

The Visum Palm™ analyzer, a portable NIR instrument operating in the SWIR range (1-1.7 μm), is particularly suitable for successful quantitative (composition) and qualitative (identification and classification) characterization of a wide variety of materials and mixtures. For this reason, the use of the Visum Palm™ leads to significant savings in analytical workload and substantial reductions in waiting time.

In addition, its ubiquitous nature -due to its portability- and the possibility of programming it to determine multiple parameters at the same time, allows it to be used in a wide variety of analytical tasks at the production line, in logistics warehouses and even for applied research studies and the development of proprietary models carried out by AIMPLAS, a reference in the plastics sector in Spain.

Main features and generic advantages of SWIR spectroscopy:

  • Determination of multiple parameters with a single instrument.
  • Real-time and continuous analysis for automatic and instantaneous correction of process parameters.
  • Non-destructive determinations without sample preparation.
  • Excellent repeatability.
  • Use does not require skilled operators.

Although there are several portable NIR instruments on the market, it is essential to take into account the spectral range with which the instrument works and the size of the spot (measuring point) to ensure representativeness of the reading with respect to the sample. The Visum Palm™ System introduces a 10mm spot and a powerful spectrophotometer that works in the range 900-1700 nm.

Identification and classification of polymers in the industry

The Visum Palm™ instrument includes a library of models for reading and determination at the line, without sample preparation and in a few seconds that allows characterization of a large number of polymers, including PET (polyethylene terephthalate), HDPE (high density polyethylene), LDPE (low density polyethylene), PP (polypropylene), PS (polystyrene), PVC (vinyl or polyvinyl chloride), PC (polycarbonate), ABS (acrylonitrile butadiene styrene), to name a few, including more complex mixtures.

Identification and separation is important in polymer manufacturing, since in order to reprocess plastic waste, manufacturers must ensure that the polymers materials are as pure and clean as possible and, of course, the price manufacturers pay recyclers for the plastic waste they supply depends on this. In addition, low levels of impurities can already considerably affect the quality and yield of a complete recycling batch. In this context, spectroscopy techniques combined with machine learning models make it possible to introduce important automatisms and quality controls sensitive to the needs of the industry.

Di IRIS Technology Solutions