Data-driven Soft Sensors in the Process Industry

In the last two decades Soft Sensors established themselves as a valuable alternative to the traditional means for the acquisition of critical process variables, process monitoring and other tasks which are related to process control. This paper discusses characteristics of the process industry data which are critical for the development of data-driven Soft Sensors. These characteristics are common to a large number of process industry fields, like the chemical industry, bioprocess industry, steel industry, etc. The focus of this work is put on the data-driven Soft Sensors because of their growing popularity, already demonstrated usefulness and huge, though yet not completely realised, potential. A comprehensive selection of case studies covering the three most important Soft Sensor application fields, a general introduction to the most popular Soft Sensor modelling techniques as well as a discussion of some open issues in the Soft Sensor development and maintenance and their possible solutions are the main contributions of this work

Monitoring and Control of Hydrocyclones by Use of Convolutional Neural Networks and Deep Reinforcement Learning

The use of convolutional neural networks for monitoring hydrocyclones from underflow images was investigated. Proof-of-concept and applied industrial considerations for hydrocyclone state detection and underflow particle size inference sensors were demonstrated. The behaviour and practical considerations of model-free reinforcement learning, incorporating the additional information provided by the sensors developed, was also discussed in a mineral processing context

Artificial Intelligence in Process Engineering

In recent years, the field of Artificial Intelligence (AI) is experiencing a boom, caused by recent breakthroughs in computing power, AI techniques, and software architectures. Among the many fields being impacted by this paradigm shift, process engineering has experienced the benefits caused by AI. However, the published methods and applications in process engineering are diverse, and there is still much unexploited potential. Herein, the goal of providing a systematic overview of the current state of AI and its applications in process engineering is discussed. Current applications are described and classified according to a broader systematic. Current techniques, types of AI as well as pre- and postprocessing will be examined similarly and assigned to the previously discussed applications. Given the importance of mechanistic models in process engineering as opposed to the pure black box nature of most of AI, reverse engineering strategies as well as hybrid modeling will be highlighted. Furthermore, a holistic strategy will be formulated for the application of the current state of AI in process engineering

Frontiers in Ultra-Precision Machining

Ultra-precision machining is a multi-disciplinary research area that is an important branch of manufacturing technology. It targets achieving ultra-precision form or surface roughness accuracy, forming the backbone and support of today’s innovative technology industries in aerospace, semiconductors, optics, telecommunications, energy, etc. The increasing demand for components with ultra-precision accuracy has stimulated the development of ultra-precision machining technology in recent decades. Accordingly, this Special Issue includes reviews and regular research papers on the frontiers of ultra-precision machining and will serve as a platform for the communication of the latest development and innovations of ultra-precision machining technologies

Dynamic simulation of industrial grinding circuits : mineral liberation, advanced process control, and real-time optimisation

Étant donné que les minéraux apparaissent fréquemment dans des associations complexes dans la nature, la libération minérale est un aspect clé du traitement de minerais et celle-ci est accomplie par comminution. Cette opération est certainement l’une des plus importantes, mais aussi des plus coûteuses dans l’industrie. La réussite globale d’une usine dépend souvent de la performance du circuit de broyage car il existe un compromis pour atteindre la taille des particules libérant les minéraux ciblés afin d’obtenir des concentrés de haute pureté tout en ayant de faibles coûts d’opération, lesquels sont largement influencés par la consommation énergétique. Dans les années récentes, les entreprises ont été confrontées à des objectifs de performance plus exigeants, une concurrence accrue sur les marchés, et des réglementations environnementales et de sécurité plus strictes. D’autres défis supplémentaires sont inhérents aux circuits de broyage, par exemple les réponses non linéaires, le niveau élevé d’intercorrélation entre les variables et les recirculations de matière. Les problèmes ci-dessus soulignent la pertinence d’avoir des systèmes de contrôle et d’optimisation adéquats pour lesquels les praticiens profitent de plus en plus des approches basées sur des modèles pour y faire face de façon systématique. La modélisation et la simulation sont des outils puissants ayant des avantages significatifs tels que les faibles coûts, les temps requis pour réaliser des expériences relativement courts et la possibilité de tester des conditions opérationnelles extrêmes ainsi que différentes configurations des circuits sans interrompre la production. De toute évidence, la qualité des résultats sera aussi bonne que la capacité du modèle à représenter la réalité, ce qui souligne l’importance d’avoir des modèles précis et des procédures de calibrage appropriées, un sujet fréquemment omis dans la littérature. Un autre aspect essentiel qui n’a pas été rapporté est l’intégration efficace de la libération minérale aux systèmes de contrôle et d’optimisation de procédés. Bien qu’il s’agisse d’une information clé directement liée aux performances de l’étape de concentration, la plupart des stratégies se concentrent exclusivement sur la taille de particule du produit. Ceci est compréhensible étant donné qu’il est impossible de mesurer la distribution de libération présentement. Basée sur une librairie de simulation d’usines de traitement des minerais déjà existante, cette recherche aborde lesdits problèmes en (1) développant un modèle de libération minérale visant à coupler les étapes de broyage et de concentration ; (2) programmant et validant par calibrage un modèle phénoménologique de broyeur autogène/semi-autogène (BA/BSA), nécessaire pour compléter la librairie de simulation ; (3) couplant un simulateur de circuit de broyage à un procédé de concentration avec le modèle de libération, et (4) développant un système de contrôle et d’optimisation qui considère explicitement des données de libération minérale pour évaluer les avantages économiques. Les principaux résultats confirment que le modèle de libération est capable de reproduire avec précision des distributions de libération minérale couramment observées dans l’industrie. Cependant, si les données de calibrage correspondent à un point d’opération unique, la validité pourrait être limitée aux régions voisines proches. Le problème de caractériser l’évolution de la libération minérale aux diverses conditions d’opération ainsi qu’aux régimes transitoires reste à être abordé. Le modèle de libération s’est aussi révélé utile pour coupler des circuits de broyage avec des procédés de concentration, en particulier pour une unité de flottation. Quant au modèle de BA/BSA, celui-ci peut capturer le régime statique ainsi que la dynamique d’un broyeur réel et conjointement avec le reste des équipements dans la librairie de simulation, des circuits de broyage industriels. Ceci a été confirmé par le calibrage à partir des données d’opération d’une usine et des tests en laboratoire, tout en suivant une procédure systématique, contribuant aussi au sujet de l’établissement de méthodologies de calibrage standardisées. Pour terminer, les expériences concernant la stratégie de contrôle et d’optimisation basée sur la libération minérale suggèrent que l’utilisation de cette information peut améliorer la performance globale des circuits de broyage-séparation en réagissant aux variations des caractéristiques de libération, qui à leur tour influencent l’efficacité de séparation. L’étude de cas réalisé révèle que cela peut entraîner une augmentation du débit massique et de la teneur du concentré, de la récupération des métaux et des revenus de l’ordre de +0.5%, +1%, +1% et +5%, respectivement, par rapport au cas où ces informations sont omises.As minerals frequently appear in complex associations in nature, mineral liberation is one of the most relevant aspects in ore processing and is achieved through comminution. This operation is one of the most important, but also one of the most expensive ones in industry. The global efficiency of a plant often depends on the performance of the grinding circuit, since there is a compromise to achieve the particle size liberating the targetted minerals in order to obtain high purity concentrates while maintaining low operating costs, which are largely influenced by the energy consumption. In recent years, companies have been facing more demanding performance targets, stronger competition, and more stringent environmental and safety regulations. Additional challenges are inherent to the grinding circuits themselves, e.g. the nonlinear responses, high degree of intercorrelation of the different variables, and material recirculations. The abovementioned issues highlight the relevance of adequate process control and optimisation, and practitioners rely more often on model-based approaches in order to face them systematically. Modeling and simulation are powerful tools with significant advantages such as low costs, required times for conducting experiments are relatively short, and the possibility of testing extreme operational conditions as well as different circuit configurations without disrupting production. Evidently, the quality of the results will only be as good as the model capacity to represent the reality, which emphasises the relevance of having precise models and proper calibration procedures, the latter being a topic frequently omitted in the literature. Another crucial aspect that has not been reported yet is the effective integration of mineral liberation in control and optimisation schemes. Although it is a key piece of information directly related to the performance of the concentration stage, most strategies focus exclusively on the particle size. This is understandable given that it is currently impossible to measure the liberation distribution online. Based on an existing mineral processing plant simulation library, this research addresses these problems by (1) developing a mineral liberation model aiming at linking the grinding and concentration stages; (2) programming a phenomenological autogenous/semiautogenous (AG/SAG) mill model, required to complement the simulation toolbox, and validating it through calibration; (3) coupling a grinding circuit simulator to a concentration process by means of the liberation model, and (4) developing a plantwide control and optimisation scheme considering mineral liberation data explicitly to evaluate the economic benefits. The main results confirm that the liberation model is capable of reproducing accurately mineral distributions observed in industry. If calibration data correspond to a single operating point, its validity may however be limited to the close neighbourhood. Characterising the evolution of mineral liberation in different operating conditions and transient states remains to be addressed. The liberation model proved to be equally useful in coupling grinding circuits with concentration processes, specifically for flotation. As for the AG/SAG mill model, it can capture the steady state and dynamic behaviour of an actual device and, along with the rest of pieces of equipment in the simulation toolbox, of industrial grinding circuits. This was confirmed through calibration from plant data and laboratory testwork following a systematic procedure, contributing to the endeavour of establishing standard calibration methodologies. Lastly, the results of the designed control and optimisation scheme suggest that using liberation data for control and real-time optimisation can improve the overall performance of grinding-separation circuits by reacting to variations in the liberation characteristics, which in turn influence the concentration performance. The case study reveals that doing so can lead to increases in the concentrate mass flow rate and grade, metal recovery, and global profits in the order of +0.5%, +1%, +1%, and +5%, respectively, compared to the case omitting this information

Data Acquisition Applications

Data acquisition systems have numerous applications. This book has a total of 13 chapters and is divided into three sections: Industrial applications, Medical applications and Scientific experiments. The chapters are written by experts from around the world, while the targeted audience for this book includes professionals who are designers or researchers in the field of data acquisition systems. Faculty members and graduate students could also benefit from the book

Parametric modeling of tooling: Workpiece interaction with engineered abrasives

Abrasive processes are some of the most important operations employed in manufacturing to remove unwanted material and introduce desired geometry and surface finish. However, some of the difficulties encountered when trying to model abrasive process are related to a multi-point of contact tooling composed of extremely hard and brittle particles which geometry, shape and distribution are unknown. With the introduction of engineered abrasives to the market over the past few years, the opportunity to drastically improve the quality and consistency of abrasive machining now exists. One of the main benefits of engineered abrasives is the ability to control the abrasive grit properties i.e. size, shape, distribution and composition. The objective of this study was to develop a parametric model of the engineered abrasives that allows for studying the interaction of this particular tooling with various surfaces. This would also allow for prediction of surface roughness from a given tool-workpiece pair. The development of this model, the analysis of the tool-workpiece interaction, and the algorithms for surface generation are carried out using a computer model developed for each specific purpose. Additionally, experimental validation of this model is presented. It was found that the machined surface improves as the depth of indentation increases, but beyond a certain level the surface roughness obtained becomes asymptotic. It is observed that machining at 30 attack angle results in the smoothest surface and that increasing the number of abrasive grits beyond a certain number does not yield better surface. Contributions of this project include suggestions for new tooling geometry for abrasive manufacturing and optimization of machining parameters for efficient operations along with a simulation tool for a better understanding of the abrasive machining process

A Feasibility Study of Elementary Reinforcement Learning-Based Process Control

Process Engineerin

Manufacturing Metrology

Metrology is the science of measurement, which can be divided into three overlapping activities: (1) the definition of units of measurement, (2) the realization of units of measurement, and (3) the traceability of measurement units. Manufacturing metrology originally implicates the measurement of components and inputs for a manufacturing process to assure they are within specification requirements. It can also be extended to indicate the performance measurement of manufacturing equipment. This Special Issue covers papers revealing novel measurement methodologies and instrumentations for manufacturing metrology from the conventional industry to the frontier of the advanced hi-tech industry. Twenty-five papers are included in this Special Issue. These published papers can be categorized into four main groups, as follows: Length measurement: covering new designs, from micro/nanogap measurement with laser triangulation sensors and laser interferometers to very-long-distance, newly developed mode-locked femtosecond lasers. Surface profile and form measurements: covering technologies with new confocal sensors and imagine sensors: in situ and on-machine measurements. Angle measurements: these include a new 2D precision level design, a review of angle measurement with mode-locked femtosecond lasers, and multi-axis machine tool squareness measurement. Other laboratory systems: these include a water cooling temperature control system and a computer-aided inspection framework for CMM performance evaluation