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• Novel control framework based on optimization in the latent space of a SMB-PLS model. • Real-time optimization of continuous process facing raw material fluctuation. • Overcomes parametric disturbances with model adaptation and closed-loop structure. • Adjustment of process operating conditions based on quality thresholds and economics. Reducing the impact of lot-to-lot raw material variability through optimization of operating conditions is key when the lots are already purchased, and available in inventory. The objective of this paper is to provide a framework to optimize operating conditions to maximize profitability while aiming at achieving product quality targets each time a new lot of raw material is fed to a continuous process. The proposed approach consists of solving an optimization problem in the latent space of a sequential multi-block partial least square model (SMB-PLS). Model updating and closed-loop operation are considered to overcome parametric disturbances. The approach is illustrated using a simulated grinding-flotation plant for a sequence of ore lots with variable properties. The case study shows that optimizing operating conditions with the proposed approach allows increasing biannual gain by 1.5 to 2 % compared to nominal operation. This represents between 59 and 75 % of the true achievable gain. [ABSTRACT FROM AUTHOR]

Decision tools to determine the acceptability of an incoming lot of raw materials prior to its purchase from a supplier is essential to ensure efficient quality control. They allow mitigating the propagation of the raw material variability through the process and, ultimately, in the final product quality. Establishing multivariate specifications regions for raw material properties to achieve high and consistent end product quality using latent variable models is key. However, these specifications are typically designed assuming the process operates at nominal conditions. The objective of this work is to enlarge the raw material acceptance region to accept materials having a wider range of properties, and possibly at a lower cost, while meeting final product quality requirements. Using a sequential multi-block partial least squares model (SMB-PLS), the design of multivariate specification regions is combined with optimization of process operating conditions to better cope with fluctuations in raw material properties. An economic criterion is used to assess whether accepting lower cost materials, at the expense of adjusting plant operation, which incurs additional costs, is economically justified. The approach is illustrated using a grinding-flotation plant simulator where the objective is to assess the profitability of different lots of raw materials (i.e. ores). The impact of measurement noise is also investigated. The case studies show that the raw material processability is improved since the number of correctly accepted lots is increased by 7.3 % in comparison with maintaining nominal process conditions. • Adjusting process conditions widens multivariate specifications for raw materials. • Optimization in the latent space of SMB-PLS model is performed for the first time. • Development of multivariate specifications includes an economic criterion. • A general SMB-PLS prediction equation is provided and demonstrated. [ABSTRACT FROM AUTHOR]

Previous studies have established the potential of acousto-ultrasonic inspection (AU) for non-destructive testing and evaluation of pre-baked carbon anodes soundness. This work evaluates its repeatability through the development of a new experimental setup that allows testing a larger number of anodes and classifying them based on presence/absence of defects. Principal Component Analysis and Projection to Latent Structures Discriminant Analysis, both coupled with Linear Discriminants, are used to analyze AU signals, detect and locate various defects on the anodes. The proposed method is capable of detecting small defects, and has the potential to become an instrument for both process and quality control of the anode production. [ABSTRACT FROM AUTHOR]

The Sequential Multi-Block Partial Least Squares (SMB-PLS) model inversion is applied for defining analytically the multivariate raw material region providing assurance of quality with a certain confidence level for the critical to quality attributes (CQA). The SMB-PLS algorithm does identify the variation in process conditions uncorrelated with raw material properties and known disturbances, which is crucial to implement an effective process control system attenuating most raw material variations. This allows expanding the specification region and, hence, one may potentially be able to accept lower cost raw materials that will yield products with perfectly satisfactory quality properties. The methodology can be used with historical/happenstance data, typical in Industry 4.0. This is illustrated using simulated data from an industrial case study. • Definition of the multivariate raw material specification region from historical data. • Identifying variations in the process uncorrelated with raw materials and disturbances. • Expanding the raw material specification region by modifying the process conditions. [ABSTRACT FROM AUTHOR]

• New dynamic macro scale model of a tablet pan coater based on energy and mass transfer equations. • Modeling for control system design and the development of system observers to estimate critical unmeasured variables in real-time. • Model parametrization and calibration using pilot plant batch data. • Model captures the main process variable trajectories, with errors below 2 °C for the outlet gas and tablet bed temperatures, and 2% for the outlet gas relative humidity. Aqueous film coating is a common and important step in the production of most pharmaceutical tablets. Controlling this process is beneficial to maintain stable and optimal operation and the use of a model capable of describing its main physical phenomena is fundamental for control system design. This paper presents the development of a dynamic macro scale model of a pan coater based on energy and mass transfer equations. Model complexity is kept low to simplify parameterization and allow for real-time applications, such as the development of system observers to estimate critical unmeasured variables. Pilot plant data from seven batches, ran according to designed experiments, are used for model calibration and validation. The final model adequately captures the global trajectories of the main process variables; mean differences between experimental and simulated values are below 2 °C for the outlet gas and tablet bed temperatures, and 2% for the outlet gas relative humidity. [ABSTRACT FROM AUTHOR]

This work investigates the mechanical and aging properties of flax/glass fibers reinforced polypropylene hybrid composites. The mechanical properties as a function of reinforcement content show that adding glass fiber to polypropylene/flax composites improves tensile modulus and strength as well as impact resistance and hardness, but has negligible effect on strain at yield and elongation at break. Water uptake at 85℃ and variations in mechanical behavior are determined after water, thermal, and accelerated UV aging tests. The results indicate that glass fibers enhance water resistance of polypropylene/flax composites. Thermal aging at 85℃ reveals that irrespective of filler type and content the composites are thermally resistant. According to accelerated UV aging tests, the presence of glass fiber accelerates the degradation of the polypropylene matrix, but flax fiber can protect the composites. Finally, a partial least-squares model is built to correlate the composite composition to the properties of aged and unaged specimens. [ABSTRACT FROM AUTHOR]

Abstract: In this work, optical imaging is used to quantify the mixing dynamics of granular materials. Two different methods (GLCM and Multivariate RGB analysis) are combined to extract surface information and the time to achieve a specific degree of mixing. In particular, the effect of density, friction coefficient, surface quality and particle geometry was studied. The results show that the Froude number alone is not enough to completely characterize the rolling regime. In addition, the filling ratio must be in a specific range which depends on the material properties. [Copyright &y& Elsevier]

Abstract: This paper reports some observations on the behaviour of a binary particle bed consisting of a mixture of small and large particles in the axial plane of a rotating drum. The effects of Froude number, particle diameter, filling ratio and initial particle concentration on axial segregation are evaluated using polymer powders. The results show that the number of segregation bands formed depends strongly on bed composition and processing conditions. Based on the experimental results, a segregation model to quantify axial dispersion is proposed. [ABSTRACT FROM AUTHOR]

Abstract: In this work, the mixing quality of a multi-component blend of particles is determined using Multivariate Image Analysis of RGB images combined with the Grey Level Co-occurrence Matrix (GLCM) texture analysis. The mixing dynamics and flow behavior are studied in terms of mixing homogeneity and time to achieve equilibrium for binary, ternary and quaternary mixtures of equal size particles. The parameters studied are rotational speed, filling ratio, initial powder composition and particle sizes. Using the experimental data in the rolling regime, a second order model is proposed to predict the mixing curve as a function of time. [Copyright &y& Elsevier]

Abstract: In the production of rotomolded parts, the distribution of particle sizes in the form of polymer powder is highly important to produce parts of good quality. In the case of polymer blends, the particle size distribution becomes even more important to assure that good mixing occurs before the polymer melts. In this work, the mixing of free flowing polymer powders in a horizontal rotating cylinder has been studied. Special attention is given to the initial moments of mixing and the transition from a standstill to a fully developed rolling regime. The parameters studied include Froude number (rotational speed), cylinder loading, relative powder composition and particle sizes. For the first time, mixing dynamics are quantified using two image analyzes: grey-level co-occurrence matrix (GLCM) and Threshold methods. Using the experimental data, a model is proposed to follow the mixing dynamics and to determine the equilibrium time. The results also indicate that the Froude number is not enough to characterize the flow regime and the filling ratio must be accounted for. [Copyright &y& Elsevier]

• Individual anode current signals used to detect anode incidents in real-time. • Detection systems built with principal component analysis and an industrial dataset. • Best detection performance was achieved with the simplest system configuration. • Model profit metric developed to evaluate economic potential of detection systems. • Detection systems appear to be economically superior to standard detection method. Anodic incidents occur when an aluminum electrolysis cell short circuits at an anode position. They reduce the current efficiency of the affected cell, which makes it economically advantageous to detect and remove them as early as possible. This study evaluates the performance of three anodic incident detection systems of varying complexity. Individual anode current signals from 6 different cells were monitored with a Principal Component Analysis (PCA) model to detect anodic incidents using the Squared Prediction Error (SPE) statistic. The results suggest that a simple detection system using a common PCA model and a common detection threshold for all cells may be preferable. A novel approach to estimating the economic benefit of a detection system was also developed and used to optimize the systems' detection threshold. The anodic incident detection systems were found to deliver positive profits relative to the standard detection technique. [ABSTRACT FROM AUTHOR]

[Display omitted] In this study, an in-line Process Analytical Technology (PAT) for cosmetic (non-functional) coating unit operations is developed using images of the tablet bed acquired in real-time by an inexpensive industrial camera and lighting system. The cosmetic end-point of multiple batches, run under different operating conditions, is automatically computed from these images using a Multivariate Image Analysis (MIA) methodology in conjunction with a stability determination strategy. The end-points detected by the algorithm differed, on average, by 3% in terms of total batch time from those identified visually by a trained operator. Since traditional practice typically relies on a coating overage to ensure full batch aspect homogeneity in the face of disturbances, the current in-line method can be used to reduce coating material and processing time (over 40% for the operating policy adopted in this work). Additionally, monitoring of the color features calculated by the algorithm allowed the identification of abnormal process conditions affecting visible coating uniformity. This work also addresses practical challenges related to image acquisition in the harsh environment of a pan coater, bringing this tool closer to a state of maturity for implementation in production units and opening the path for their optimization, monitoring, and automatic control. [ABSTRACT FROM AUTHOR]

Abstract: In this work, the transverse mixing of free flowing particles in a horizontal rotating drum has been studied. Special attention is given to the initial moments of mixing and the transition from a standstill to a fully developed rolling regime. The parameters studied include rotational frequency (1.3 to 4.6 rpm), loading (15 to 50%), relative black/white powder content (1/3 to 2/3) as well as drum diameter (50 to 75 mm). To this end, four methods have been used to quantify dispersion: (1) Discrete Wavelet Transform (DWT), (2) Gray-Level Co-occurrence Matrix (GLCM), (3) Contact and (4) Entropy. Of these four methods, the GLCM algorithm was found best suited for this application: it is fast, reliable and easily interpretable despite requiring little user input. While Wavelet and Contact analysis methods also provide good results, Entropy systematically overestimates the degree of mixing for any given time. The results show that mixing dynamics from standstill can be modeled by a second-order dynamic based on the filling ratio and the number of drum rotations. [Copyright &y& Elsevier]

Abstract: In this paper, the use of different image analysis techniques is investigated for predicting alumina content of anode cover materials used in primary aluminum smelters. This approach is proposed in to order to allow on-line estimation of alumina content for feedback control purposes, which is not currently possible due to the long time delays and limited number of samples that can be analyzed in the laboratory. Both color and textural features of various anode cover materials are extracted from digital RGB images, and partial least squares (PLS) regression models are developed for predicting alumina content from these features. Most alumina content prediction errors are within of the X-ray fluorescence laboratory measurements, when larger variations are required by operators to make control decisions. Some challenges arising from the use of image analysis techniques for process control are also discussed. [Copyright &y& Elsevier]

Abstract: Variations in run-of-mine ore properties such as size, composition, and grindability strongly affect AG and SAG mills performance. In the past, most efforts to track and control these variations have focused on developing on-line size analysis using vision systems to reduce power consumption and avoid mill overload. To improve ore sorting/blending strategies and to account for variations in grindability, on-line run-of-mine composition analysis would be very helpful, but has received much less attention from the research community. This paper describes a general machine vision approach for on-line estimation of rock mixture composition, and is illustrated on a very challenging nickel mineral system: very heterogeneous minerals, similar coloration, and rock fragments can be dry or wet. The proposed mineral type recognition method involves: (1) dividing into sub-images; (2) extracting color and textural features using principal components analysis (PCA) and wavelet texture analysis (WTA), respectively; (3) reducing feature space dimensionality and removing dry/wet systematic variations using discriminant partial least squares (PLS-DA); and (4) establishing class boundaries using support vector machines (SVM). Through a pilot plant conveyor belt application, very good results were obtained for dry minerals. For wet rock mixtures, further investigation is required, but results are very promising. [Copyright &y& Elsevier]

Rotary dryers are very versatile process equipment as it can accommodate a large variety of products over a wide range of flow rates. To obtain a uniform product quality and to operate the dryer economically with minimal environmental impact, it is necessary to use efficient control strategies. In this article, two simple control strategies are proposed to improve the feedback-only controller that is normally used. One strategy is a partial feedforward control loop addition to the feedback loop and the second is a moisture predictor that allows taking control actions on the estimates of the discharge moisture content rather than waiting to measure its value at the discharge. The performance of these two strategies was compared with the performance of a feedback-only controller and an ideal feedback-feedforward controller. It is shown that the two proposed control strategies significantly improve the performance of a feedback-only control strategy without having to install new sensors. [ABSTRACT FROM AUTHOR]

• Introduction of a control strategy for batch tablet film-coating processes. • Effective use of available process data for online control of critical variables. • Use of a dynamic process simulator to validate a decentralized PI controller. • Potential reduction in total batch processing time and energy consumption. This paper proposes a control strategy for batch tablet film-coating processes using readily available process instrumentation. Outlet air conditions (temperature and relative humidity), which impact coating quality, are controlled by the manipulation of inlet air temperature and coating spray rate. Controller design, tuning and validation rely on the use of a dynamic process simulator, calibrated using data collected from a pilot plant coating unit. The final 2 × 2 decentralized PI controller demonstrated good performance for both setpoint tracking and disturbance rejection in simulation. Additionally, controlled variable setpoints were determined to maximize plant profits considering batch duration and energy consumption as optimization criteria. For the case study considered, the total batch processing time can potentially be reduced by 40 % while simultaneously reducing energy usage by 30 %, in comparison with the more conservative fixed recipe approach typically adopted in production. [ABSTRACT FROM AUTHOR]

The Sequential Multi-block PLS algorithm, called SMB-PLS, was recently proposed to improve interpretability of large multi-block data structures. It combines the strengths of Multi-block PLS (MB-PLS) and those of the Sequential Orthogonal PLS (SO-PLS) methods. It uses the two-level hierarchical structure of the first (i.e., block and super levels) providing two levels of scrutiny for the analysis of large datasets, and the sequential orthogonalization scheme of SO-PLS, while keeping between block correlated information in the model. This enables the exploration and interpretation of the full data structure without loss of information. SMB-PLS also allows the selection of a different number of latent variables for each regressor block. The modelling performance and interpretation of SMB-PLS were illustrated using two datasets, covering different types of structural relationships between the regressor blocks. SMB-PLS leads to similar predictive performance of response data as MB-PLS and SO-PLS. However, it was shown that SMB-PLS clearly reveals the correlation structure between the regressor blocks, while MB-PLS leads to more ambiguous results. The correlated information between the blocks extracted with SMB-PLS also improves interpretability, for example, by identifying control actions made to attenuate disturbances, such as raw materials variations. Such information cannot be obtained with SO-PLS since it removes between block correlated variations. [ABSTRACT FROM AUTHOR]

This paper reports on the application of an acousto-ultrasonic (AU) scheme for the inspection of industrial-size carbon anode blocks used in the production of primary aluminium by the Hall-Héroult process. A frequency-modulated wave is used to excite the anode blocks at multiple points. The collected attenuated AU signals are decomposed using the Discrete Wavelet Transform (DTW) after which vectors of features are calculated. Principal Component Analysis (PCA) is utilized to cluster the AU responses of the anodes. The approach allows locating cracks in the blocks and the AU features were found sensitive to crack severity. The results are validated using images collected after cutting some anodes. [ABSTRACT FROM AUTHOR]

A fast and non-invasive near-infrared (NIR) imaging system is proposed to characterize biodegradable polylactic acid (PLA) films containing talc, and produced by extrusion film-blowing for packaging applications. The ultimate goal is to use the system on-line for quality control and after a post-processing thermal treatment (annealing). A set of PLA-talc films with different talc contents (0–3% wt.) were produced and annealed under different conditions. NIR images of the films were collected after which the samples were characterized for their physical, mechanical, and gas barrier properties. Multivariate imaging techniques were then applied on the hyperspectral images. The results showed that the films with various talc loadings can be discriminated, and the information contained in the NIR spectra allowed predicting the annealed film crystallinity and O 2 permeability with good accuracy. [ABSTRACT FROM AUTHOR]

The large datasets resulting from operating HVAC&R systems are currently scrutinized to find ways to exploit the useful information that they might contain. In this work, historical data of a centrifugal water chiller over the course of more than 1.5 years of operation is used to learn about the system and to suggest modifications to its operation scheme. The results show that principal component analysis (PCA) captures well the variance in the historical data. The first two principal components explained between 62 and 80% of the variance, depending on the cases considered. The main factors responsible for the variation of the chiller operation are found to be the weather and the cold water temperature setpoint. The effect of the sampling time step on the results is also studied. Moreover, this work demonstrates that partial least squares (PLS) regression can adequately predict an important indicator of the chiller performance, namely the coefficient of performance (COP), one time step ahead with an R² of 77.49% and root-mean square error of estimation (RMSEE) of 0.463 using a separate validation set of data. The PLS model was also able to predict future COP values up to 2 time steps (∼3 h) in advance. [ABSTRACT FROM AUTHOR]

In this study, composite films based on polylactic acid and talc were prepared by extrusion film blowing to determine the effect of annealing temperature, annealing time, and talc content on the morphology and gas permeability, as well as thermal and mechanical properties. The results showed that annealing temperature, annealing time, and talc content have a direct effect on polylactic acid crystallinity leading to changes in gas permeability and gas diffusion coefficient, while gas solubility was constant. This effect is related to the talc particles and polylactic acid crystals producing higher tortuosity in the films. Finally, a direct relation between crystallinity level, mechanical properties and gas permeability was observed for all the conditions tested. [ABSTRACT FROM AUTHOR]

A novel methodology is proposed for defining multivariate raw material specifications providing assurance of quality with a certain confidence level for the critical to quality attributes (CQA) of the manufactured product. The capability of the raw material batches of producing final product with CQAs within specifications is estimated before producing a single unit of the product, and, therefore, can be used as a decision making tool to accept or reject any new supplier raw material batch. The method is based on Partial Least Squares (PLS) model inversion taking into account the prediction uncertainty and can be used with historical/happenstance data, typical in Industry 4.0. The methodology is illustrated using data from three real industrial processes. • A novel approach to define multivariate specifications overcoming the drawbacks of setting univariate specifications. • Definition of the multivariate raw material region from historical data typical from Industry 4.0 environment. • New methodology to back-propagate the uncertainty in Latent Variable Model Inversion when defining the Design Space. • Evaluation of the capability of a raw material batch prior to introducing it into the production process. [ABSTRACT FROM AUTHOR]

Combining color (spectral) and textural information often leads to improved performance of image-based sensors developed for different applications, such as process monitoring and prediction of process or product quality variables. A new method based on the undecimated wavelet transform and multivariate image analysis (UWT-MIA) is proposed in this paper for simultaneous extraction of spatial and spectral information. The key advantages of this approach are: 1) it uses continuous wavelets which have a constant resolution over all scales compared to discrete wavelets, and are better suited for extracting size distribution features, 2) the wavelet detail and approximation sub-images have the same size and are spatially congruent which allows stacking the sub-images obtained at all scales and orientations (and wavelengths for multi- and hyperspectral images) as a separate channel in a new multivariate image from which a single MIA model can be built. The performance of UWT-MIA is illustrated using both synthetic and natural images. It is shown that variations in color, size and orientation of objects of interest can be tracked efficiently within the same MIA model. The method can also be cast within the multiresolutional multivariate image analysis (MR-MIA) framework proposed in the literature. [ABSTRACT FROM AUTHOR]

To improve understanding of the mixing phenomena resulting from the interaction between uniform magnetic fields and magnetic nanofluids, this work presents an optical investigation of the coherent structures generated by rotating magnetic nanoparticles in dilute nanofluid suspension submitted to uniform rotating magnetic fields. A microscopic visualization technique was implemented inside the bore of an electromagnet to allow image and video capture of the variation in nanofluid behavior under time-varying magnetic fields and different operating parameters. The effects of magnetic core volume fraction, magnetic nanoparticle diameter, rotating magnetic field intensity and frequency as well as magnetic field type on coherent structure generation were explored. The observational results were subsequently correlated and analyzed making use of an automatic structure detection protocol at different scales based on multi-resolution orthogonal 2-Dimensional discrete wavelet transforms. All the parameters considered were found to substantially affect detectable structure inception in the nanofluid in different ways, with trends and thresholds emerging for different types of organisations at different scales. This information now opens the door for adequate tuning of rotating magnetic nanoparticle based mixing technologies at the micro-scale. [ABSTRACT FROM AUTHOR]

The potential and effectiveness of near-infrared (NIR) hyperspectral imaging was investigated for rapid and nondestructive spectral-spatial inspection of functional multilayer films. A series of film samples having different combinations of layers were used to demonstrate the sensor performance. Multivariate Image Analysis (MIA) was applied to NIR hyperspectral images of unprinted multilayer films with different compositions to distinguish them regarding absence/presence of particular layers. Since printing of commercial brands on the films may interfere with product inspection, the ability of MIA to detect the presence of the functional layer (barrier) in spite of film surface printing was also assessed. The results show that the proposed MIA approach is successful at classifying multilayer films, even in the presence of printing. [ABSTRACT FROM AUTHOR]

Abstract: This study examines the ability of chemometrics methods, namely multivariate image analysis (MIA) and Grey Level Co-occurrence Matrix analysis (GLCM), to extract meaningful information from visible and near-infrared spectral images of extruded wood/plastic composite materials for predicting spatio-temporal variations in their properties. The samples were produced under varying process and feed conditions according to designed experiments. Mechanical properties of the samples were measured using standard analytical methods both during steady-state and dynamic transition periods. A Bootstrap-PLS regression technique was first used for selecting the spectral bands (i.e. wavelengths) that were the most highly correlated with the material properties. In a second step, a more parsimonious PLS regression model was built between the spectral and textural features extracted from the lower dimensional spectral images and the corresponding quality properties of each sample. The imaging sensor was able to simultaneously monitor 7 properties in both steady-state operation and during transitions. [ABSTRACT FROM AUTHOR]

Abstract: A PLS-bootstrap-VIP approach is proposed as a simple wavelength selection method, yet having the ability to identify relevant spectral intervals. This approach is particularly attractive for wavelength selection within hyperspectral images due to its simplicity and relatively low computational cost compared to more sophisticated interval search methods. The method was tested on four visible-NIR spectral imaging datasets taken from the polymer, oil and pulp and paper industries. The results were compared with those obtained using PLS regression coefficients as well as with two more sophisticated methods involving several metrics or search for wavelength intervals. It is shown that a small number of well defined relevant spectral intervals are identified with the proposed approach, providing easy spectral interpretation in agreement with more complex interval search methods. Before final use, fine adjustments to the VIP threshold may be tested to verify whether predictive power can be improved. [Copyright &y& Elsevier]

Undesired particulate agglomeration can create powder flow issues during manufacturing. Potassium chloride (KCl), a commercial product used in powder form as a potassium source, is known to agglomerate. The main objective is to develop a method to assess KCl agglomeration, then use it to understand its driving forces and the phenomena taking place. Based on industrial data in pharmaceutical manufacturing, the following 5 parameters are considered as critical in terms of agglomeration: conditioning humidity, conditioning time, drying, applied pressure and particle size. Beakers containing 40 g of original or ground KCl powder are compacted under specific humidity conditions in a bell jar. Once the beakers are conditioned, agglomerate hardness tests evaluate agglomeration extent by correlating it with the energy required for powder penetration. This energy is calculated from force-distance curves. The results show that the Area Under the force vs distance Curve (AUC) is a good indicator of agglomeration extent. Thus, the AUC is a scalar and has units of work. Based on AUC analysis, the highest agglomeration is found in conditioning humidity of 85% relative humidity (RH), original particle size, drying and conditioning time of 16 h. The agglomeration of original versus ground particle size powders is further investigated over time in a conditioning test. Preliminary tests validate our method and indicate that KCl premixing with other materials can solve agglomeration problems encountered during manufacturing processes as KCl-particle-particle interactions per unit volume are reduced. [ABSTRACT FROM AUTHOR]

The petrography and mineral chemistry of magnetite from fifteen volcanogenic massive sulfide (VMS) deposits in Canada, and the Lasail VMS deposit in Oman, as well as from two VMS-associated banded iron formations (BIF), Austin Brook (New Brunswick, Canada) and Izok Lake (Nunavut, Canada), were investigated using optical microscopy, electron probe micro-analyzer (EPMA), and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). The method of robust estimation for compositional data (robCompositions) was applied to investigate geochemical censored data. Among thirty-seven elements analyzed by EPMA and/or LA-ICP-MS in magnetite from the studied deposits/bedrock lithologies, only the results for Si, Ca, Zr, Al, Mg, Ti, Zn, Co and Ni contain < 40% censored values, and thus could be imputed using robCompositions. Imputed censored data were transformed using centered log-ratios to overcome the closure effect on compositional data. Transformed data were classified by partial least squares-discriminant analysis (PLS-DA) to identify different compositional characteristics of magnetite from VMS deposits and BIFs. The integration of petrography and mineral chemistry identifies three types of magnetite in VMS settings: magmatic, hydrothermal, and metamorphic. Magmatic magnetite in VMS deposit host bedrocks is characterized by ilmenite exsolution and may be overprinted by metamorphism. Some VMS deposits contain hydrothermal magnetite, which is intergrown with sulfides, and shows a metamorphic overprint as it is partly replaced by common metamorphic minerals including chlorite, sericite, anthophyllite, and/or actinolite, whereas the majority of the deposits are characterized by metamorphic magnetite formed by replacing pre-existing sulfides and/or silicates, and is intergrown with metamorphic minerals. Among VMS deposits of the Noranda mining district, the West Ansil deposit is characterized by hydrothermal-metamorphic magnetite zoned by inclusion-free cores and Si- and Mg-rich rims. Magnetite from the studied VMS-associated BIFs is also metamorphic in origin. Aluminum, Ti and Zn contents of magnetite can separate BIF from the other mineralized and un-mineralized bedrock lithologies in the studied VMS settings. PLS-DA shows that variable compositions of magnetite slightly discriminate different studied deposits/bedrock lithologies. The geochemical observations suggest that the variation in magnetite chemistry from different VMS settings might be sourced from differences in: 1) the composition and temperature of parental magmas or hydrothermal fluids, 2) the composition of host bedrocks, 3) the composition of co-forming minerals, and 4) oxygen fugacity. PLS-DA distinguishes magnetite compositions from the studied VMS deposits and BIFs from that of the other ore deposit types including Ni–Cu, porphyry Cu-Mo-Au, iron oxide-copper- gold, iron oxide-apatite, and the Bayan Obo REE-Fe-Nb deposit. Magnetite from the VMS settings on average contains lower concentrations of Si, Zr, Al, Mg, Ti, Zn, Co and Ni relative to that from the other mineral deposit types. PLS-DA of magnetite data from VMS deposits and BIFs of the Bathurst mining camp as well as PLS-DA of magnetite compositions from various mineral deposit types yield discrimination models for application to mineral exploration for VMS deposits using indicator minerals in Quaternary lithified sedimentary rocks. [ABSTRACT FROM AUTHOR]

Primary aluminum production is a very energy-intensive industry (~13 MWh per ton of aluminum produced), involving several complex processes within a plant. The paper presents a mass, energy and exergy analysis of an entire smelter. This work was motivated by the need to evaluate the potential for waste heat recovery/thermal integration in such a plant. Three of the main sectors of a smelter are studied, namely the carbon anode production, the electrolytic reduction and the casting. The analysis is applied to a typical smelter producing 260 000 MTAl per year. It was found that the most important waste heat source is the exhaust gases, with an exergy of 0.57 MWh per ton of aluminum produced. The total exergy destroyed in the plant was found to be around 7.7 MWh/MTAl. The potential for doing useful work associated with heat dissipated at process boundaries is also evaluated. Results highlight sources of thermodynamic inefficiencies and indicate where exergy is mainly destroyed throughout the plant. The results contribute in developing a better understanding of the energy and exergy flow within a smelter. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Magnetite grains from the Izok Lake (Nunavut, Canada) and the Halfmile Lake (New Brunswick, Canada) volcanogenic massive sulfide deposits, and from till covering the nearby areas were investigated using the scanning electron microscopy (SEM), electron probe micro-analyzer (EPMA), laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), and optical microscopy. The method of robust estimation for compositional data (rob-composition) was applied to censored geochemical data, and the results were analyzed by principal component analysis (PCA). Textural relationships and mineral association of magnetite reveal the history of formation, and contribute to the explanation of characteristic compositional differences of magnetite from different geological settings. The integration of petrography and mineral chemistry allows discriminating magmatic, metamorphic and hydrothermal magnetite grains in the VMS deposits bedrock samples. Magmatic magnetite is found in Izok Lake gabbro, and Halfmile Lake syenite, felsic ash tuff and gossan samples, whereas magnetite in Izok Lake massive sulfides, gahnite-rich dacite and iron formations formed during the amphibolite facies metamorphism. In Halfmile Lake andesite, magnetite recrystallized during greenschist facies metamorphism. In the magnetite alteration zone associated to the Halfmile Lake deposit, hydrothermal magnetite has been overprinted by metamorphic magnetite. Halfmile Lake massive sulfides in chloritic argillite contain hydrothermal magnetite. PCA identifies discriminator elements and their contributions to magnetite composition from different Izok Lake Lake and Halfmile Lake bedrock samples. The results suggest that Si, Ca, Zr, Al, Ga, Mn, Mg, Ti, Zn, Co, Ni and Cr are discriminator elements for VMS deposits and their host bedrocks. The distinct chemical signatures for magnetite from various bedrock lithologies demonstrate that magnetite grains of the same origin share more similarities in chemistry, as high Ti indicates magmatic sources for magnetite, whereas high Si, Ca and Mg are indicative of hydrothermal settings. Variable compositions of metamorphic magnetite suggest that the chemistry of this type of magnetite is controlled by the composition of host rocks, the grade of metamorphism and oxygen fugacity. PCA of EPMA and LA-ICP-MS data of magnetite from the Izok Lake and Halfmile Lake bedrock samples yield discrimination models for classification of magnetite grains from till. Decreases in the proportion of magnetite grains with the chemical signature of the Izok Lake massive sulfides and gahnite-rich dacite down-ice from the Izok Lake deposit show the use of magnetite chemistry in geochemical exploration. In the Halfmile Lake area, till magnetite grains with the signature of VMS mineralization make a glacial dispersal train more than 2 km down-ice from the deposit. [ABSTRACT FROM AUTHOR]

The estimation of the flotation rate constant is generally considered difficult because of the number of variables – not always measurable – determining its value. Among them, the particle size distribution and hydrodynamic characteristics are considered key elements. Part 1 of this paper introduced the interfacial area of bubbles ( I b ) as a hydrodynamic variable providing more information about the size distribution than the bubble surface area flux ( S b ). Fundamental expressions were proposed to characterize I b using the population mean and standard deviation. Experimental results indicated that for lognormal bubble size distributions, I b correlates very well with the gas hold-up and d 32 . Part 2 investigates the correlation between the flotation rate constant and particle size as well as given hydrodynamic variables using a Projection to Latent Structures (PLS) analysis. The tests were conducted under ‘ideal’ conditions (i.e. shallow froth, low mineral concentration and pure mineral particles). Results suggest that for the fine particle sizes, the bubble surface area flux ( S b ) should be considered for the kinetic constant modeling. For coarser particle, the gas hold-up ( ε g ) is the determining parameter. In practice though, the particle size distribution often lies between these two extreme cases, and can either span a very large range or contains intermediate size particles. In such cases, the interfacial area of bubbles ( I b ) better correlates with the flotation kinetics. [ABSTRACT FROM AUTHOR]

Abstract: The long-term patency rates of vascular grafts and stents are limited by the lack of surface endothelialisation of the implanted materials. We have previously reported that GRGDS and WQPPRARI peptide micropatterns increase the endothelialisation of prosthetic materials in vitro. To investigate the mechanisms by which the peptide micropatterns affect endothelial cell adhesion and proliferation, a TAMRA fluorophore-tagged RGD peptide was designed. Live cell imaging revealed that the micropatterned surfaces led to directional cell spreading dependent on the location of the RGD-TAMRA spots. Focal adhesions formed within 3 h on the micropatterned surfaces near RGD-TAMRA spot edges, as expected for cell regions experiencing high tension. Similar levels of focal adhesion kinase phosphorylation were observed after 3 h on the micropatterned surfaces and on surfaces treated with RGD-TAMRA alone, suggesting that partial RGD surface coverage is sufficient to elicit integrin signaling. Lastly, endothelial cell expansion was achieved in serum-free conditions on gelatin-coated, RGD-TAMRA treated or micropatterned surfaces. These results show that these peptide micropatterns mainly impacted cell adhesion kinetics rather than cell proliferation. This insight will be useful for the optimization of micropatterning strategies to improve vascular biomaterials. [Copyright &y& Elsevier]

We investigated the effect of variousplasma parameters (relativedensity of atomic N and H, plasma temperature, and vibrational temperature)and process conditions (pressure and H2/(N2+H2) ratio) on the chemical composition of modified poly(tetrafluoroethylene)(PTFE). The plasma parameters were measured by means of near-infrared(NIR) and UV–visible emission spectroscopy with and withoutactinometry. The process conditions of the N2–H2microwave discharges were set at various pressures rangingfrom 100 to 2000 mTorr and H2/(N2+H2) gas mixture ratios between 0 and 0.4. The surface chemical compositionof the modified polymers was determined by X-ray photoelectron spectroscopy(XPS). A mathematical model was constructed using the partial least-squaresregression algorithm to correlate the plasma information (processcondition and plasma parameters as determined by emission spectroscopy)with the modified surface characteristics. To construct the model,a set of data input variables containing process conditions and plasmaparameters were generated, as well as a response matrix containingthe surface composition of the polymer. This model was used to predictthe composition of PTFE surfaces subjected to N2–H2plasma treatment. Contrary to what is generally acceptedin the literature, the present data demonstrate that hydrogen is notdirectly involved in the defluorination of the surface but ratherproduces atomic nitrogen and/or NH radicals that are shown to be atthe origin of fluorine atom removal from the polymer surface. Theresults show that process conditions alone do not suffice in predictingthe surface chemical composition and that the plasma characteristics,which cannot be easily correlated with these conditions, should beconsidered. Process optimization and control would benefit from plasmadiagnostics, particularly infrared emission spectroscopy. [ABSTRACT FROM AUTHOR]

This study reports on using near-infrared(NIR) hyperspectral imaging for nondestructive spectral-spatial characterizationof natural fiber composites. To illustrate the approach, maleic anhydridegrafted polyethylene (MAPE)/hemp fiber composites were produced withdifferent filler contents between 0 and 60%. Two different chemometricsmethods based on (1) the traditional multivariate PLS calibrationand (2) multivariate image analysis and regression (MIA/MIR) weretested to predict tensile properties using NIR images. The resultsshow good agreement between the measured properties and their predictionsby both of these methods. The MIR ability to map chemical compositionwas compared to that of multivariate curve resolution (MCR) and theresults were found similar. The proposed MIR approach was found verypromising for quality control of polymer composites because of itscombined ability to quantify filler content and dispersion withinthe material, to distinguish compositional variations from physicaldefects, and to predict the end-user properties of the product allwith a single MIR model. [ABSTRACT FROM AUTHOR]

Abstract: In this paper a methodology for extraction of qualitative descriptions of data series is extended for proper inflection point recognition. The original method allows the extraction of qualitative information such as the sign of the first and second derivatives of the assumed signals underlying univariate noisy time series. However, it is not able to handle consecutive inflection points, i.e. inflection points which follow each other in time with no minimum or maximum in between them. To improve this method for proper assessment of inflection points, the original method is compared with three modifications of the original method. One of the alternatives based on repeated application of Witkin''s stability criterion delivers better results for both identification of the qualitative descriptions and the locations in time of extrema and inflection points. Furthermore, the same modified method is shown to deliver the best fault diagnosis performance in a benchmark batch fermentation study. Furthermore, the same modified method is shown to deliver the best fault diagnosis performance in a benchmark batch fermentation study. [Copyright &y& Elsevier]

Abstract: This paper summarizes research into the study of the control of flotation processes based on froth images. A review of the froth flotation operation background and the relevance and role of the froth phase are presented. The use of numerical image analysis techniques for the extraction of significant patterns from industrial flotation froths is discussed. First, the froth was analysed by the use of the Multivariate Image Analysis (MIA) method to extract the spectral variation contained in a RBG image. The Partial Least Squares (PLS) method was applied to develop an empirical model for the prediction of froth grade. The results of this application are illustrated using an industrial case study. Second, the froth was also analysed by Grey-Level Co-occurrence Matrix (GLCM) and Wavelet Transform Analysis (WTA) to extract features related more to morphological aspects. Since there is useful information hidden in froth texture, these methods are used as texture descriptor to classify different types of froths. They also provide qualitative information on the changes in the visual appearance of the froth. The pros and the cons of those methods are highlighted. Third, a control strategy based on a froth structure indicator was developed and implemented on an industrial zinc flotation circuit. The feedback controller uses the reagent flow-rate in order to maintain the froth structure at its set point. Process improvements obtained from the implemented control strategy are highlighted. Finally, the feasibility of implementing a hybrid control strategy consisting in a froth structure supervision controller based on the froth concentrate grade estimated by MIA and recovery inferred by image analysis is discussed. [Copyright &y& Elsevier]