In-line Moisture Research Articles

Preliminary Design and Test of a Microwave Inline Moisture Sensor for the Carasau Bread Industry

Preliminary Design and Test of a Microwave Inline Moisture Sensor for the Carasau Bread Industry

Employing a multi-resonance microwave sensor for in-line moisture monitoring of fluidized bed agglomeration

Amorphous substances are relatively common in food industry and their characteristics depend highly on the moisture content. Process parameters are adjusted based on online measurements to control the product quality of the agglomerates. This leads to two major challenges: precise moisture content measurements of amorphous particles at (i) different temperatures and for (ii) a wide moisture content range.In this study two workflows (inline fluidized bed and conditioned fixed bed) calibration of microwave sensors are compared and it is shown that for fluidized beds inline calibration is necessary to achieve accurate moisture measurements. The application of the novel microwave sensor MW 4200 working at resonance frequencies of 2.3 and 5.6 GHz is described. The temperature influence on the measurement is investigated with measurements of a fixed particle bed. Rapid, reliable in-process moisture control at a wide range of moisture contents and temperatures for agglomeration in fluidized beds, with a mean relative accuracy of 82 %, is achieved. This technology improves productivity and precision in industrial operations, minimizes waste and optimizes energy usage.

Implementation of Dynamic and Static Moisture Control in Fluidized Bed Granulation.

The application of process analysis and control is essential to enhance process understanding and ensure output material quality. The present study focuses on the stability of the feedback control system for a fluidized bed granulation process. Two strategies of dynamic moisture control (DMC) and static moisture control (SMC) were established based on the in-line moisture value obtained from the near-infrared sensor and control algorithm. The performance of these strategies on quality consistency control was examined using process moisture similarity analysis and principal component analysis. The stable moisture control performance and low batch-to-batch variability indicated that the DMC method was significantly better than other granulation methods. In addition, the investigation of robustness further showed that the implemented DMC method was able to produce predetermined target moisture values by varying process parameters. This study provides an advanced and simple control method for fluidized bed granulation quality assurance.

Accuracy Improvement of In-line Near-Infrared Spectroscopic Moisture Monitoring in a Fluidized Bed Drying Process.

An exploratory analysis of a large representative dataset obtained in a fluidized bed drying process of a pharmaceutical powder has revealed a significant correlation of spectral intensity with granulate humidity in the whole studied range of 1091.8–2106.5 nm. This effect was explained by the dependence of powder refractive properties, and hence light penetration depth, on the water content. The phenomenon exhibited a close spectral similarity to the well-known stochastic variation of spectral intensities caused by the process turbulence (the so-called “scatter effect”). Therefore, any traditional scatter-corrective preprocessing incidentally eliminates moisture-correlated variance from the data. To preserve this additional information for a more precise moisture calibration, a time-domain averaging of spectral variables has been suggested. Its application resulted in a distinct improvement of prediction accuracy, as compared to the scatter-corrected data. Further improvement of the model performance was achieved by the application of a dynamic focusing strategy when adjusting the model to a drying process stage. Probe fouling was shown to have a minor effect on prediction accuracy. The study resulted in a considerable reduction of the root-mean-square error of in-line moisture monitoring to 0.1%, which is close to the reference method's reproducibility and significantly better than previously reported results.

Prism-assembly for dual-band short-wave infrared region line-scan camera

A simple dichroic splitter for dual-band line scanning is described. It comprises prisms elements that enable cheapness of the whole prototype by using only one linear detector. Validity of the design is demonstrated via in-line moisture measurement.

In-line moisture monitoring in fluidized bed granulation using a novel multi-resonance microwave sensor

Microwave resonance technology (MRT) is known as a process analytical technology (PAT) tool for moisture measurements in fluid-bed granulation. It offers a great potential for wet granulation processes even where the suitability of near-infrared (NIR) spectroscopy is limited, e.g. colored granules, large variations in bulk density. However, previous sensor systems operating around a single resonance frequency showed limitations above approx. 7.5% granule moisture. This paper describes the application of a novel sensor working with four resonance frequencies. In-line data of all four resonance frequencies were collected and further processed. Based on calculation of density-independent microwave moisture values multiple linear regression (MLR) models using Karl-Fischer titration (KF) as well as loss on drying (LOD) as reference methods were build. Rapid, reliable in-process moisture control (RMSEP≤0.5%) even at higher moisture contents was achieved.

Moisture Determination of Static and In-Motion Powdered Infant Formula Utilising Multiprobe near Infrared Spectroscopy

Moisture content of powdered infant formula is a critical factor governing product quality, especially in terms of its physicochemical stability. High levels of moisture accelerate the conversion of amorphous lactose to α-lactose monohydrate, which is the main cause of sticking and caking problems. Conversely, milk powders may become more susceptible to lipid oxidation at relatively low moisture levels. Traditionally, moisture content has commonly been determined by methods based on the loss of weight when drying under controlled conditions in an oven. However, these methods are time consuming and not suitable for in-line measurement. Near infrared (NIR) spectroscopy is a rapid method and perhaps the most used and accepted alternative technique for the measurement of moisture content in the dairy industry. Significant challenges in using NIR spectroscopy in the manufacturing process are in-line measurement and real-time monitoring. In this work, a novel multiprobe NIR system based on a Fabry–Perot interferometer combined with four fibre probes was assessed for predicting the moisture content of samples with varying moisture levels (ranging from ca 2% to 13%) and recorded under static conditions and various levels of motion. Partial least squares (PLS) regression was used to correlate the spectral response to the reference moisture values. The coefficient of determination of calibration ( R2) and root mean square error of cross validation for the best model were 0.99% and 0.57%, respectively. The PLS calibration model was then applied to an independent set of samples recorded under both conditions: static [root mean square error of prediction ( RMSEP) = 0.62%] and motion at 0.01 m s−1 ( RMSEP = 0.66%), 0.07 m s−1 (1.07%) and 0.16 m s−1 (0.97%). Therefore, moisture predictions for both measuring modes agreed well with the reference values, even when samples were travelling at speeds of 0.16 m s−1. These results demonstrated that the approach is suitable for in-line moisture analysis of powdered infant formula.

NIR spectroscopic method for the in-line moisture assessment during drying in a six-segmented fluid bed dryer of a continuous tablet production line: Validation of quantifying abilities and uncertainty assessment

This study focuses on the thorough validation of an in-line NIR based moisture quantification method in the six-segmented fluid bed dryer of a continuous from-powder-to-tablet manufacturing line (ConsiGma™ 25, GEA Pharma Systems nv, Wommelgem, Belgium). The moisture assessment ability of an FT-NIR spectrometer (Matrix™-F Duplex, Bruker Optics Ltd, UK) equipped with a fiber-optic Lighthouse Probe™ (LHP, GEA Pharma Systems nv, Wommelgem, Belgium) was investigated. Although NIR spectroscopy is a widely used technique for in-process moisture determination, a minority of NIR spectroscopy methods is thoroughly validated.A moisture quantification PLS model was developed. Twenty calibration experiments were conducted, during which spectra were collected at-line and then regressed versus the corresponding residual moisture values obtained via Karl Fischer measurements. The developed NIR moisture quantification model was then validated by calculating the accuracy profiles on the basis of the analysis results of independent in-line validation experiments. Furthermore, as the aim of the NIR method is to replace the destructive, time-consuming Karl Fischer titration, it was statistically demonstrated that the new NIR method performs at least as good as the Karl Fischer reference method.

Validation of a multipoint near-infrared spectroscopy method for in-line moisture content analysis during freeze-drying

This study assessed the validity of a multipoint near-infrared (NIR) spectroscopy method for in-line moisture content analysis during a freeze-drying process. It is known that the moisture content affects the stability of a freeze-dried product and hence it is a major critical quality attribute. Therefore assessment of the validity of an analytical method for moisture content determination is vital to ensure the quality of the final product. An aqueous sucrose solution was used as the model formulation of the study. The NIR spectra were calibrated to the moisture content using partial least squares (PLS) regression with coulometric Karl Fischer (KF) titration as the reference method. Different spectral preprocessing methods were compared for the PLS models. A calibration model transfer protocol was established to enable the use of the method in the multipoint mode. The accuracy profile was used as a decision tool to determine the validity of the method. The final PLS model, in which NIR spectra were preprocessed with standard normal variate transformation (SNV), resulted in low root mean square error of prediction value of 0.04%-m/v, i.e. evidence of sufficient overall accuracy of the model. The validation results revealed that the accuracy of the model was acceptable within the moisture content range 0.16–0.70%-m/v that is specific for the latter stages of the freeze-drying process. In addition, the results demonstrated the method's reliable in-process performance and robustness. Thus, the multipoint NIR spectroscopy method was proved capable of providing in-line evaluation of moisture content and it is readily available for use in laboratory scale freeze-drying research and development.

Moisture and drug solid-state monitoring during a continuous drying process using empirical and mass balance models

Classically, the end point detection during fluid bed drying has been performed using indirect parameters, such as the product temperature or the humidity of the outlet drying air. This paper aims at comparing those classic methods to both in-line moisture and solid-state determination by means of Process Analytical Technology (PAT) tools (Raman and NIR spectroscopy) and a mass balance approach. The six-segmented fluid bed drying system being part of a fully continuous from-powder-to-tablet production line (ConsiGma™-25) was used for this study. A theophylline:lactose:PVP (30:67.5:2.5) blend was chosen as model formulation. For the development of the NIR-based moisture determination model, 15 calibration experiments in the fluid bed dryer were performed. Six test experiments were conducted afterwards, and the product was monitored in-line with NIR and Raman spectroscopy during drying. The results (drying endpoint and residual moisture) obtained via the NIR-based moisture determination model, the classical approach by means of indirect parameters and the mass balance model were then compared. Our conclusion is that the PAT-based method is most suited for use in a production set-up. Secondly, the different size fractions of the dried granules obtained during different experiments (fines, yield and oversized granules) were compared separately, revealing differences in both solid state of theophylline and moisture content between the different granule size fractions.

In-Line Multipoint Near-Infrared Spectroscopy for Moisture Content Quantification during Freeze-Drying

During the past decade, near-infrared (NIR) spectroscopy has been applied for in-line moisture content quantification during a freeze-drying process. However, NIR has been used as a single-vial technique and thus is not representative of the entire batch. This has been considered as one of the main barriers for NIR spectroscopy becoming widely used in process analytical technology (PAT) for freeze-drying. Clearly it would be essential to monitor samples that reliably represent the whole batch. The present study evaluated multipoint NIR spectroscopy for in-line moisture content quantification during a freeze-drying process. Aqueous sucrose solutions were used as model formulations. NIR data was calibrated to predict the moisture content using partial least-squares (PLS) regression with Karl Fischer titration being used as a reference method. PLS calibrations resulted in root-mean-square error of prediction (RMSEP) values lower than 0.13%. Three noncontact, diffuse reflectance NIR probe heads were positioned on the freeze-dryer shelf to measure the moisture content in a noninvasive manner, through the side of the glass vials. The results showed that the detection of unequal sublimation rates within a freeze-dryer shelf was possible with the multipoint NIR system in use. Furthermore, in-line moisture content quantification was reliable especially toward the end of the process. These findings indicate that the use of multipoint NIR spectroscopy can achieve representative quantification of moisture content and hence a drying end point determination to a desired residual moisture level.

Development of a fluid bed granulation process control strategy based on real-time process and product measurements

This article describes the results of three case studies conducted consecutively, in order to develop a process control strategy for a top-spray fluid bed granulation process. The use of several real-time particle size (i.e., spatial filter velocimetry and focused beam reflectance measurement) and moisture (i.e., near infrared (NIR) and Lighthouse near infrared spectroscopy) analyzers was examined. A feed-forward process control method was developed, where in-line collected granulation information during the process spraying phase was used to determine the optimum drying temperature of the consecutive drying phase. Via real-time monitoring of process (i.e., spraying temperature and spray rate) and product (i.e., granule size distribution and moisture) parameters during the spraying period, the batch bulk density was predicted at the end of the spraying cycle, using a PLS model. When this predicted bulk density was not meeting the desired value, the developed control method allowed the calculation of an adjusted drying temperature leading to the desired batch bulk density at the end of the granulation process. Besides the development of the feed-forward control strategy, a quantitative PLS model for in-line moisture content prediction of the granulated end product was built using the NIR data.

Towards a Tensiometer Based Suction Control System for Laboratory Testing of Unsaturated Soils

Abstract This paper presents the development of an automated tensiometer based suction control system for testing unsaturated soil samples. The system is able to dry and wet soil, while measuring suction (pore water pressure – air pressure) and water content. The system uses air circulation within a closed loop to dry the soil, or water injection to wet the soil, to achieve the required pore water pressure while the air pressure is kept atmospheric. Pore water pressure is controlled by using a feedback computer system that dries or wets soil samples according to measurements obtained from sample-mounted high suction tensiometers. Excess moisture in the air circulation loop is captured by an in-line moisture trap consisting of a sealed cell containing a desiccant (silica gel), which is placed on an electronic balance to give continuous measurements of retained water. Changes of the sample water content are measured as the difference between the amount of water injected and that retained by the moisture trap. The system is fully automated and runs controlled by software with minimum assistance. The proposed suction control system presents advantages over the conventional axis translation technique as it avoids the need for elevated pore air pressures and hence better replicates the natural processes of wetting and drying of soils. The system was developed for use in a triaxial cell, but could also be used with other instruments and for the determination of water retention curves.

In-Line Moisture Content Measurement of Kiln-Dried Lumber for Process Improvement

The in-line moisture meter at the planer measures the moisture content of every board. This information is often not used for process improvement because of difficulty in linking the moisture information to a point in the process and reliable statistical methods for analyzing the data. Test programs in which the moisture contents measured at the planer were used to create process charts for kilns and to identify kilns or zones within kilns with high moisture content or moisture content variability were established in four mills. Tagging units, either with bar codes or with alphanumeric tags, to identify their location in a kiln was a practical and effective way to diagnose kiln performance when the moisture content information collected at the planer was associated with location. Wet areas and dry areas could be identified, and the consistency of moisture content from charge to charge could be evaluated, as could the variability within charges. The latter items can be accomplished without knowing the location of a unit in the kiln if the kiln from which the lumber came is known at the time of planing. The methods developed also allow other factors, such as operator decisions and the performance of in-kiln moisture meters, to be evaluated.

In-line monitoring of granule moisture in fluidized-bed dryers using microwave resonance technology

This is the first report on in-line moisture measurement of pharmaceutical products by microwave resonance technology. In order to meet the FDA's PAT approach, a microwave resonance sensor appropriate for pharmaceutical use was developed and implemented into two different fluidized-bed dryers. The novel sensor enables a continuous moisture measurement independent from the product density. Hence, for the first time precise real time determination of the moisture in pharmaceutical granules becomes possible. The qualification of the newly developed sensor was performed by drying placebo granules under experimental conditions and the validation using drug loaded granules under real process conditions. The results of the investigations show good correlations between water content of the granules determined by the microwave resonance sensor and both reference methods, loss on drying by infrared light exposure and Karl Fischer titration. Furthermore, a considerable time saving in the drying process was achieved through monitoring the residual water content continuously by microwave resonance technology instead of the formerly used discontinuous methods.

Near infrared reflectance spectroscopy as a tool for the in-line determination of the moisture concentration in extruded semolina pasta

After extrusion, the optimal moisture content of pasta is attained through drying, taking into account energetic and bio-physical concerns. Monitoring the moisture content of the pasta after the extrusion process, but before the drying process, is useful as the moisture content is variable and may be used to adapt the air characteristics during drying. In this paper, near-infrared (NIR) reflectance spectroscopy is proposed for in-line determination of moisture concentrations in semolina pasta immediately after the extrusion process. Several pasta samples with different moisture concentrations were extruded while the reflectance spectra between 308 and 1704 nm were measured at the extrusion die. An adequate prediction model for the in-line moisture concentration was developed based on the Partial Least Squares (PLS) method using leave-one-out cross-validation. Best cross-validation results were obtained for non-transformed data, confirming the ability to predict excellently the moisture concentration of the extruded pasta (coefficient of determination r CV 2 =0.956; root-mean-square error of cross-validation RMSECV=0.024 kg/kg). Comparable cross-validation results were obtained based on the most important wavelengths (when at least two different wavelengths were used). This creates opportunities for measuring the moisture content with a low-cost sensor.

In-line moisture measurement during granulation with a four-wavelength near-infrared sensor: an evaluation of process-related variables and a development of non-linear calibration model

The near-infrared set-up based on simultaneous detection of four wavelengths was applied for in-line moisture measurement during fluid bed granulation. In addition to the spectral response, several other process measurements describing the state of the granulation were evaluated. The near-infrared moisture measurement is disturbed by the variation in physical properties of the sample (e.g., temperature, particle size, bulk density). The factors explaining the non-linearity of spectral response during different phases of granulation could be extracted. Combining all this process information improved the prediction capability of the multivariate calibration models tested (partial least squares and artificial neural network (ANN)). The back-propagation neural network approach was found to have most predictive power with the independent test data.

In-line moisture measurement during granulation with a four-wavelength near infrared sensor: an evaluation of particle size and binder effects

Factors affecting in-line near infrared (NIR) moisture measurement with a four-wavelength sensor were evaluated (choice of binder used in granulation liquid and the increase in particle size). An entire NIR spectrum is not necessary for the measurement of water, and often the use of only a few NIR wavelengths around the water band enables reliable and high-speed detection of moisture. Glass ballotini and microcrystalline cellulose (MCC) were used as model test materials. The binders studied were poly[1-(2-oxo-1-pyrrolidinyl)ethylene] (PVP) and gelatin. Full off-line NIR spectra of test materials at different levels of binder solutions were measured. The major spectral features for both the binders were bands around 1700 nm (first overtones CH related stretches) and 2200 nm (combination bands). Gelatin also had an NH band around 1500 nm (first overtones of NH stretches) and combination bands at about 2050 nm. Particle size effects were observed as an increase in spectra baseline. All these factors should be considered when choosing NIR wavelengths used for detection of water with a fixed wavelength set-up. A robust calibration model enables the development of in-process control of wet granulation processes.

Use of the Near-Infrared Reflectance Method for Measurement of Moisture Content During Granulation

The purpose of this study was to demonstrate the use of a near-infrared (NIR) method for in-process control of a placebo formulation. An NIR setup with a multichannel detector was applied in the measurement of water during fluidized bed granulation. The effects of two critical granulation parameters were studied using the central composite design. The present NIR setup with three wavelengths proved applicable for in-line moisture measurement. The 1990 nm signal was used for measurement of water and the 1745 and 2145 nm signals were used to correct the change in spectra baseline during granulation. Variations in inlet air conditions proved to be critical factors, explaining differences in the granule size distributions. Differences in granule moistening and drying rates resulting from varying inlet air conditions could be measured with the NIR setup. The moisture content of granules at the end of the spraying phase explained part of the differences in granule size distributions. The moisture content of granules at the end of the drying phase affected the tableting behavior of granules. The results suggested that direct measurement of granule moisture content facilitates the in-process control of the granulation.

In-Line Moisture Monitoring in Semiconductor Process Gases by a Reactive-Metal-Coated Quartz Crystal Microbalance

A new in-line sensor for trace moisture monitoring has been developed based on a piezoelectric quartz crystal microbalance (QCM) coated with a reactive metal thin film. The properties of the metal coating and QCM allow the sensor to have fast response and fast recovery to moisture in the process gas stream. The properties of the metal-coated QCM also allow the sensor to be compact so it can be in-line in the gas distribution system and readily integrated into the process tools. This paper presents the principle of moisture detection using this technology. The experimental results of accuracy, limit of detection (< 1 ppb), and error analysis of this sensor in parallel with atmospheric pressure ionization mass spectrometry (APIMS) are presented. The experimental setup and procedures are described. The effect of an upstream gas purifier on its rate of response was also studied and the results are presented and discussed. The applications of this technology in semiconductor processing are briefly mentioned.