Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes

The book documents 25 papers collected from the Special Issue “Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes”, highlighting recent research trends in complex industrial processes. The book aims to stimulate the research field and be of benefit to readers from both academic institutes and industrial sectors

Value of Mineralogical Monitoring for the Mining and Minerals Industry In memory of Prof. Dr. Herbert Pöllmann

This Special Issue, focusing on the value of mineralogical monitoring for the mining and minerals industry, should include detailed investigations and characterizations of minerals and ores of the following fields for ore and process control: Lithium ores—determination of lithium contents by XRD methods; Copper ores and their different mineralogy; Nickel lateritic ores; Iron ores and sinter; Bauxite and bauxite overburden; Heavy mineral sands. The value of quantitative mineralogical analysis, mainly by XRD methods, combined with other techniques for the evaluation of typical metal ores and other important minerals, will be shown and demonstrated for different minerals. The different steps of mineral processing and metal contents bound to different minerals will be included. Additionally, some processing steps, mineral enrichments, and optimization of mineral determinations using XRD will be demonstrated. Statistical methods for the treatment of a large set of XRD patterns of ores and mineral concentrates, as well as their value for the characterization of mineral concentrates and ores, will be demonstrated. Determinations of metal concentrations in minerals by different methods will be included, as well as the direct prediction of process parameters from raw XRD data

Contribution to the study and design of advanced controllers : application to smelting furnaces

In this doctoral thesis, contributions to the study and design of advanced controllers and their application to metallurgical smelting furnaces are discussed. For this purpose, this kind of plants has been described in detail. The case of study is an Isasmelt plant in south Peru, which yearly processes 1.200.000 tons of copper concentrate. The current control system is implemented on a distributed control system. The main structure includes a cascade strategy to regulate the molten bath temperature. The manipulated variables are the oxygen enriched air and the oil feed rates. The enrichment rate is periodically adjusted by the operator in order to maintain the oxidizing temperature. This control design leads to large temperature deviations in the range between 15ºC and 30ºC from the set point, which causes refractory brick wear and lance damage, and subsequently high production costs. The proposed control structure is addressed to reduce the temperature deviations. The changes emphasize on better regulate the state variables of the thermodynamic equilibrium: the bath temperature within the furnace, the matte grade of molten sulfides (%Cu) and the silica (%SiO2) slag contents. The design is composed of a fuzzy module for adjusting the ratio oxygen/nitrogen and a metallurgical predictor for forecasting the molten composition. The fuzzy controller emulates the best furnace operator by manipulating the oxygen enrichment rate and the oil feed in order to control the bath temperature. The human model is selected taking into account the operator' practical experience in dealing with the furnace temperature (and taking into account good practices from the Australian Institute of Mining and Metallurgy). This structure is complemented by a neural network based predictor, which estimates measured variables of the molten material as copper (%Cu) and silica (%SiO2) contents. In the current method, those variables are calculated after carrying out slag chemistry assays at hourly intervals, therefore long time delays are introduced to the operation. For testing the proposed control structure, the furnace operation has been modeled based on mass and energy balances. This model has been simulated on a Matlab-Simulink platform (previously validated by comparing real and simulated output variables: bath temperature and tip pressure) as a reference to make technical comparisons between the current and the proposed control structure. To systematically evaluate the results of operations, it has been defined some original proposals on behavior indexes that are related to productivity and cost variables. These indexes, complemented with traditional indexes, allow assessing qualitatively the results of the control comparison. Such productivity based indexes complement traditional performance measures and provide fair information about the efficiency of the control system. The main results is that the use of the proposed control structure presents a better performance in regulating the molten bath temperature than using the current system (forecasting of furnace tapping composition is helpful to reach this improvement). The mean square relative error of temperature error is reduced from 0.72% to 0.21% (72%) and the temperature standard deviation from 27.8ºC to 11.1ºC (approx. 60%). The productivity indexes establish a lower consumption of raw materials (13%) and energy (29%).En esta tesis doctoral, se discuten contribuciones al estudio y diseño de controladores avanzados y su aplicación en hornos metalúrgicos de fundición. Para ello, se ha analizado este tipo de plantas en detalle. El caso de estudio es una planta Isasmelt en el sur de Perú, que procesa anualmente 1.200.000 toneladas de concentrado de cobre. El sistema de control actual opera sobre un sistema de control distribuido. La estructura principal incluye una estrategia de cascada para regular la temperatura del baño. Las variables manipuladas son el aire enriquecido con oxígeno y los flujos de alimentación de petróleo. La tasa de enriquecimiento se ajusta perióodicamente por el operador con el fin de mantener la temperatura de oxidación. Este diseño de control produce desviaciones de temperatura en el rango entre 15º C y 30º C con relación al valor de consigna, que causa desgastes del ladrillo refractario y daños a la lanza, lo cual encarece los costos de producción. La estructura de control propuesta esta orientada a reducir las desviaciones de temperatura. Los cambios consisten en mejorar el control de las variables de estado de equilibrio termodinámico: la temperatura del baño en el horno, el grado de mata (%Cu) y el contenido de escoria en la sílice (%SiO2). El diseño incluye un módulo difuso para ajustar la proporción oxígeno/nitrógeno y un predictor metalúrgico para estimar la composición del material fundido. El controlador difuso emula al mejor operador de horno mediante la manipulación de la tasa de enriquecimiento de oxígeno y alimentación con el fin de controlar la temperatura del baño del aceite. El modelo humano es seleccionado teniendo en cuenta la experiencia del operador en el control de la temperatura del horno (y considerando el principio de buenas prácticas del Instituto Australiano de Minería y Metalurgia). Esta estructura se complementa con un predictor basado en redes neuronales, que estima las variables medidas de material fundido como cobre (%Cu) y el contenido de sílice (%SiO2). En el método actual, esas variables se calculan después de ensayos de química de escoria a intervalos por hora, por lo tanto se introducen tiempos de retardo en la operación. Para probar la estructura de control propuesto, la operación del horno ha sido modelada en base a balances de masa y energía. Este modelo se ha simulado en una plataforma de Matlab-Simulink (previamente validada mediante la comparación de variables de salida real y lo simulado: temperatura de baño y presión en la punta de la lanza) como referencia para hacer comparaciones técnicas entre la actual y la estructura de control propuesta. Para evaluar sistemáticamente los resultados de estas operaciones, se han definido algunas propuestas originales sobre indicadores que se relacionan con las variables de productividad y costos. Estos indicadores, complementados con indicadores tradicionales, permite evaluar cualitativamente los resultados de las comparativas de control. Estos indicadores de productividad complementan las medidas de desempeño tradicionales y mejoran la información sobre la eficiencia de control. El resultado principal muestra que la estructura de control propuesta presenta un mejor rendimiento en el control de temperatura de baño fundido que el actual sistema de control. (La estimación de la composición del material fundido es de gran ayuda para alcanzar esta mejora). El error relativo cuadrático medio de la temperatura se reduce de 0,72% al 0,21% (72%) y la desviación estandar de temperatura de 27,8 C a 11,1 C (aprox. 60%). Los indicadores de productividad establecen asimismo un menor consumo de materias primas (13%) y de consumo de energía (29%)

Measuring, modelling and controlling the pH value and the dynamic chemical state

pH value is a challenging quantity to measure, model and control. In fact, pH value is a mere one-dimensional projection of a multi-dimensional quantity called chemical state and measuring, modelling and controlling the chemical state is much more challenging. This thesis contributes to all aspects of pH processes. A new method for measuring the pH value under difficult conditions (pressure and flow variations in thick pulp) is presented. Classical physico-chemical modelling of chemical systems is extended with a concept of population principle which is a new formulation of the "reaction invariant - reaction variant" structure. Self-organising fuzzy controller (SOC) is modified to suit pH-processes better (high frequency noise and oscillations are damped more efficiently). All the methods described above were tested with practical applications that include a pilot neutralisation process, an industrial ammonia scrubber and a paper machine wet end. The new methods showed such a significant improvement that they were installed permanently on the industrial applications.reviewe

Development of performance functions for economic performance assessment of process control systems

Economic performance assessment (EPA) of control systems is receiving increasing attention in both academia and industry. It addresses the estimation of the potential benefits resulting from control upgrade projects and monitoring and improvement of economic performance of the control system. Economic performance of control systems can often be related to crucial controlled variables dynamically and when controlled variables move away from an optimal operating point either more profit will be made or more cost will be incurred. This relation can be modelled by performance functions (PFs). When the multivariate nature of a process’s economic model is not considered, PFs of different controlled variables are referred to as individual performance functions. Otherwise, PFs of dependent controlled variables are referred to as joint performance functions. PFs play an important role in the latest techniques of EPA. There appears, however, to be no systematic method for developing PFs. The lack of such a method restrains further research into EPA, as without well-established PFs an EPA cannot be conducted smoothly and therefore cannot effectively support decision-making for management. The development of PFs is a bottleneck in the further research into EPA. Furthermore, the multivariate nature of processes has not been taken into account sufficiently as far as the relevant literature is concerned, which hampers the accuracy of PFs and accordingly the accuracy of economic assessment results. The contributions of this thesis lie in the following aspects: • A methodology for developing PFs is proposed, based on the PF development for an electric arc furnace, a grinding mill circuit and a stage of a bleach plant. • A comprehensive case study of an EPA of three controllers of a grinding mill circuit is conducted using a newly published framework to show the significance of PFs and how to perform an EPA systematically. • The current practice and guidelines on the control and functional/economic performance assessment of grinding mill circuits are captured using a survey study. The multivariate nature of an electric arc furnace’s economic model is investigated and joint performance functions are built based on individual performance functions. A multivariate economic assessment is conducted that shows how joint performance functions can help to provide a more accurate estimate of the economic performance of a controlled process. A web-based survey study on grinding mill circuits in mineral processing industries is conducted. One of its objectives is to obtain general PFs of grinding circuits. The survey results provide instructive insight into the PFs of grinding circuits. Furthermore, an in-depth literature review is conducted and the relationship between the product’s particle size distribution of grinding mill circuits and mineral recovery in downstream flotation circuits is revealed. The PFs of a grinding mill circuit being considered are formed, based on the survey results and literature study. An investigation into the PF development of a stage of a bleach plant is performed and crucial ideas used for their development are abstracted. A methodology for developing PFs for the EPA of control systems is then proposed by synthesising the methods used in the PF development described above. This methodology mainly includes the following stages: Stage 1: Determine information required for PF development. • Process operation and control understanding. • Process economics understanding. Stage 2: Gain required information on PF development. • PF-related information elicitation using survey research. • PF-related information available in the literature, including textbooks, journal papers, conference papers. • PF-related information from plant tests. Stage 3: Obtain suitable performance measures. Stage 4: Make suitable assumptions. Stage 5: Determine PFs. Stage 6: Develop Joint PFs. An economic assessment of three controllers (a nonlinear model predictive controller, a decentralized controller and three single-loop proportional-integral-derivative controllers) of the considered grinding mill circuit is conducted, using an EPA framework published recently to show the central role of PFs in the EPA and how to perform an EPA systematically. The circuit’s PFs, developed as described above, are used for the assessment. The EPA also shows that the improvement in the economic performance with the nonlinear model predictive controller mainly results from the improvement of the operating point and the controlled variables’ variation reduction only contributes a small part to the overall improvement, due to the characteristic of the PF of the circuit’s product particle size distribution. In addition, a web-based survey study is conducted and the current practice and guidelines on the control and functional/economic performance assessment of grinding mill circuits are captured. The questionnaire used for the study includes five segments. The first part identifies the respondents and the second part is intended to obtain background information on the milling circuits. The third part concerns the choice of key process variables and their economic impact. Part four involves the control of milling circuits and control loop performance and part five covers economic issues.Thesis (PhD)--University of Pretoria, 2010.Electrical, Electronic and Computer Engineeringunrestricte

Municipal solid waste management system: decision support through systems analysis

Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental EngineeringThe present study intends to show the development of systems analysis model applied to solid waste management system, applied into AMARSUL, a solid waste management system responsible for the management of municipal solid waste produced in Setúbal peninsula, Portugal. The model developed intended to promote sustainable decision making, covering the four columns: technical, environmental, economic and social aspects. To develop the model an intensive literature review have been conducted. To simplify the discussion, the spectrum of these systems engineering models and system assessment tools was divided into two broadly-based domains associated with fourteen categories although some of them may be intertwined with each other. The first domain comprises systems engineering models including cost-benefit analysis, forecasting analysis, simulation analysis, optimization analysis, and integrated modeling system whereas the second domain introduces system assessment tools including management information systems, scenario development, material flow analysis, life cycle assessment (LCA), risk assessment, environmental impact assessment, strategic environmental assessment, socio-economic assessment, and sustainable assessment. The literature performed have indicated that sustainable assessment models have been one of the most applied into solid waste management, being methods like LCA and optimization modeling (including multicriteria decision making(MCDM)) also important systems analysis methods. These were the methods (LCA and MCDM) applied to compose the system analysis model for solid waste. The life cycle assessment have been conducted based on ISO 14040 family of norms; for multicriteria decision making there is no procedure neither guidelines, being applied analytic hierarchy process (AHP) based Fuzzy Interval technique for order performance by similarity to ideal solution (TOPSIS). Multicriteria decision making have included several data from life cycle assessment to construct environmental, social and technical attributes, plus economic criteria obtained from collected data from stakeholders involved in the study. The results have shown that solutions including anaerobic digestion in mechanical biological treatment plant plus anaerobic digestion of biodegradable municipal waste from source separation, with energetic recovery of refuse derived fuel (RDF) and promoting pays-as-you-throw instrument to promote recycling targets compliance would be the best solutions to implement in AMARSUL system. The direct burning of high calorific fraction instead of RDF has not been advantageous considering all criteria, however, during LCA, the results were the reversal. Also it refers that aerobic mechanical biological treatment should be closed.Fundação para a Ciência e Tecnologia - SFRH/BD/27402/200

Iron and manganese accumulation potential in water distribution networks

The occurrence of discoloured drinking water at customers’ taps, which is mainly caused by the deposition and release of iron (Fe) and manganese (Mn) in water distribution networks (WDNs), is a major concern for both customers and water companies. Increased concentrations of Fe and Mn in WDNs can lead to penalisation by the Drinking Water Inspectorate (DWI) and Water Services Regulation Authority in England and Wales (Ofwat). These high concentration levels can cause aesthetic problems such as giving water an unpleasant metallic taste and staining of laundry. It has also been found that increased Mn concentrations in drinking water can reduce intellectual function of children. Despite efforts by water companies to comply with standards for drinking water, they continue to receive customer complaints related to water discolouration. Currently, most water companies identify high-discolouration-risk regions in WDNs by either selecting areas in the network with high concentrations of Fe and Mn from their routine sampling, or using data obtained from customer complaints related to discolouration. However, these risk assessment methods are imprecise, because only few selected nodes are sampled and not all customers who experience water discolouration complain. Moreover, considering that the water mains in England and Wales span approximately 315,000 km, monitoring Fe and Mn concentrations will always be a difficult and expensive task. It is therefore imperative for water companies to gain a practical understanding of the processes and mechanisms that lead to water discolouration, and to develop a model to identify the high-risk areas in WDNs so that remedial measures can be effectively implemented.The factors that influence Fe and Mn accumulation from post-treatment to customers’ taps through WDNs can be categorised into physical, chemical and biological. However, to date, researchers have only studied these factors partially or separately, but never in combination. None of the current models are able to predict discolouration/Fe and Mn accumulation potential for every node in WSZs using chemical, biological, and hydraulic/physical variables. This study took a holistic approach in investigating these factors. A five-year data set comprising of 36 water quality, hydraulic, and pipe-related variables covering 176 different district metered areas (DMAs) were analysed to identify relevant variables that influence Fe and Mn accumulation potential. Customer complaint data were also investigated for seasonal trends. Majority of the DMAs (67.44%) showed significant peaks in customer complaints during summer. These spikes may be attributed to increased water consumption and warmer water temperatures during this period. An artificial neural network (ANN) model was developed using relevant variables identified through the data analysis. The model could predict Fe and Mn accumulation potential values for every node in a given water supply zone (WSZ). From the risk maps generated by the ANN model, it was observed that most of the regions in the network with high Fe and Mn accumulation potential also had high levels of customer complaints related to discolouration. Although the ANN model could predict Fe and Mn accumulation potential failures in WSZs, its black-box nature made it difficult to explain the causes of the failures, unless they were manually investigated.To overcome the limitation in the ANN model, a fuzzy inference system (FIS) was developed to predict Fe and Mn accumulation potential for every node in WDNs and also capture the chemical, biological and physical processes as water travels through the network. The rules and weights of the rules for the FIS were calibrated using a genetic algorithm. The FIS is also able to determine the causes of the Fe and Mn accumulation potential failures. The ability of the developed models in this research to predict and indicate the causes of high Fe and Mn accumulation potential at the node level make them a unique and practical tool to detect high risk nodes in all regions in WDNs, including regions which have not been sampled. Both models could be of great benefit to water resource engineers and drinking water supply companies in managing water discolouration. They could also be used to investigate variables that influence physical, chemical and biological processes in WDNs