Keywords: Industry 4.0, Internet of Things, Smart Grids
Abstract: The concept of smart water management (SWM) encompasses a series of technologies and systems whose objective is to deliver a sustainable, efficient and quality water supply service for customers. However, it is necessary to deepen the discussion about how this diversity of applications can be integrated into an architecture. This article aimed to identify the basic structure of integration models for smart water management systems (SWMS). For this, a systematic literature review was carried out in the Web of Science and Scopus databases, resulting in 20 integration models selected for final analysis and having their characteristics detailed in the results section. The main findings of this article were the similarities of the models studied with the functional model proposed by ISA-95; which can be categorized into the layers field devices, middleware and applications and adding the cross-cutting security and management. However, the detailing and systematization of the information flow in a SWMS model represents an opportunity for future research, as well as the inclusion of aspects related to sewage and rainwater in the integration models to complete the concept of the natural water cycle.

Keywords: Industry 4.0
Abstract: O objetivo desta pesquisa é analisar os impactos da Indústria 4.0 sobre o trabalhador do cluster aeronáutico brasileiro. O método utilizado tem enfoque qualitativo e permite mapear e avaliar a adoção da Indústria 4.0 (I 4.0) na indústria aeronáutica brasileira, segundo a opinião de gestores do setor. Os dados coletados foram tratados e organizados por meio de análise de conteúdo para que possam ser resumidos, interpretados e categorizados. Os resultados encontrados possibilitam-nos concluir que tecnologias da I 4.0 têm, de fato, sido implementadas no setor, porém de modo específico e por vezes bastante pontual. Dentre os exemplos de implantação foram citados: implantação de poka-yokes, sistema de controle produtivo, digitalização de processos, monitoramento online da produção, criação de ambientes de simulação virtual de máquinas, entre outros. Ademais, constatou-se que um dos fatores que tem dificultado o processo de implantação é a falta de mão de obra qualificada ou de capital para investir em formação de capital humano. Portanto, conclui-se que se, por um lado, investimentos têm sido realizados na aplicação de tecnologias I 4.0, por outro, existe uma necessidade de maior atenção ao lado humano desse novo paradigma industrial. Acredita-se que para se obter bons resultados das transformações industriais que se apresentam, o desenvolvimento do conhecimento humano deve andar pari passu com o desenvolvimento tecnológico e de processos produtivos.

Keywords: Industry 4.0, Robotics and Mechatronics, Power and Eneergy Systems
Abstract: This work presents the digital twin development of a robotic system for inspection of pipe wall thickness in the turbine building of nuclear power plants. The robotic inspection system consists of 3 units, the first being the mobile unit, the second, a robotic unit for automatic measurement of pipe wall thickness using the ultrasound technique, and the third unit, for power supply, communication, and ancillary services. To develop the robotic inspection system, a prototype was built in laboratory to study different situations and geometric configurations that may appear in the field (turbine building). With the Process Simulate software, the digital twin of the prototype was developed including robot, metallic platform, and piping sections. This work presents the results for the virtual commissioning of the wall thickness measurement of a vertical piping section. The virtual commissioning allowed verifying that the robot could access any part of the surface of the pipe through movements of the robotic arm along its sides.

Keywords: Industry 4.0, Industrial Lighting, Internet of Things
Abstract: The Industrial Automation Theory emerged during the Third Industrial Revolution to address the new dynamics of a manufacturing process that had changed from manual to automated and it is focused on the idea that technology can be leveraged to improve manufacturing processes and enhance the competitiveness of businesses. It is usually illustrated by a pyramid, displaying technologies and its roles hierarchically and evidencing how should an automated process be structured based on that framework. However, in the second decade of the 21st Century a new industrial revolution started to thrive, the Fourth Industrial Revolution, and the classical Industrial Automation Theory no longer reflects its particularities. To better reflect the requirements of Industry 4.0, a revised model has been developed that incorporates its core tenets and emphasizes connectivity. This model recognizes various types of information flows, from strategic decision-making to tactical command, and identifies the most appropriate level for digitalizing manufacturing resources.

Keywords: Industry 4.0, Resource Efficienty & Circular Economy Tracking, Additive Manufaturing
Abstract: The reduction of greenhouse gas emissions by the industrial sector is a theme that has been gaining more and more popularity since the 20th century. The search for sustainable development is leading the development of alternative production methods beyond traditional manufacturing. Additive manufacturing is one of the methods being promoted to reduce impacts on the environment. However, the pace of growth in the implementation of additive manufacturing in the industry has not been followed by the development of research analyzing the effect of this manufacturing process on the emission of greenhouse gases. Among the 3D printing techniques with limited environmental literature is the Powder Bed Fusion (PBF). This article contributes to filling the gap in the literature on the environmental impact of PBF technology, through the application of the Life Cycle Assessment methodology. The experimental procedure for collecting part production data with a Powder Bed Fusion 3D Printer is presented. The Life Cycle Assessment methodology compares the environmental impact of the same part being manufactured through conventional machining and 3D printing. The LCA developed in this research, with a Cradle-to-gate scope, demonstrates that the PBF technology results in a lower environmental impact than conventional machining for this defined study case.

Keywords: Industry 4.0, Cyber Physical Systems, Digital Twins and Knowledge Systems, Self Configuration & Self Diagnosis
Abstract: This research paper presents the implementation including detailed design and development of a data-driven predictive maintenance methodology called LIVE which stands for Learn, Identify, Verify, Extend. The four-phase methodology is aimed at developing digital twins for the purpose of predictive maintenance. A case study on a lab-built pipe structure was conducted to evaluate the effectiveness of the LIVE methodology. The modal testing data from the physical and virtual models are used to validate and optimize a network of smart structural sensors (SSS). An experimental modal analysis is conducted with defined healthy and unhealthy cases to determine the vibrational behavior of the pipeline system. The outcome of the case study is a collection of algorithms capable of predicting and locating the induced fault in the system as well as a precursor to the online maintenance synonymous to digital twins. The developed algorithms show a high prediction accuracy of 95%. This study demonstrates the potential of the LIVE Methodology as a promising solution to problems in the predictive maintenance space.

Keywords: Industry 4.0, Electrical Vehicle and Energy Storage, Automation and Process Control
Abstract: Industry 4.0 (I4.0) is a transforming and global phenomenon based on connectivity and improvement of the of industrial data usage. I4.0 relies on some technological pillars, such as computer simulation, in order to optimize processes in real time and maximize their efficiency. However, there are uncertainties on how these technologies must be implemented at a strategic, technical, and human capital level. In fact, a gap can be found in scientific literature regarding how different I4.0 technologies will support the automotive electrification process. That said, this paper first provides a comprehensive review of the challenges associated with automotive electrification, which then allows the proposition of a preliminary correlation to I4.0 features, frameworks, and their benefits.

Keywords: Diagnosis, Prognosis and System Identification
Abstract: The interest about transformer monitoring systems has significantly increased in recent years. This interest comes both from academia and industry, as the detection of failures provides a high degree of control over the operating conditions of electrical machines and significant cost savings through timely maintenance. In the stages that precede the total failure of a transformer, it is common to detect partial or full discharges that initiate due to degradation of the dielectric materials that form the insulation in the transformer. Therefore, the identification and classification of these phenomena can indicate the quality of the insulation and allow complete failure of the electrical machine to be avoided. One of the main points to consider is where the fault is occurring. For example, a fault can occur in both the active part of the transformer and in its insulators. Therefore, diagnosing the type of failure is very important as they require different maintenance actions. One of the principal non-invasive methods is current pulse analys is using a high frequency current sensor, known as High-Frequency Current Transformer (HFCT), with a bandwidth of up to 50 MHz, to evaluate differences in the current signals originating from discharges in insulators from the total discharges that occur in the active part of an oil-isolated transformer. From this perspective, the Fourier Transform was applied to the acquired current signals and some parameters were extracted, like average bandwidth, skewness, and kurtosis to determine which of these combinations is the most effective in classifying the verified failures.

Keywords: Industry Applications, Diagnosis, Prognosis and System Identification, Optimization Heuristics and Methods
Abstract: This article implements the multi-objective grey wolf optimizer (MOGWO) in the identification process of a multivariable system. For a sequence of 100 runs, MOGWO approach had compared and analyzed with the grey wolf optimizer (GWO), the single-objective version. In the computational simulation, the determination coefficient values and mean square error had used to analyze the quality of the models obtained. In the results, MOGWO showed superior to GWO to the differences between the order of magnitude of the system outputs. The implementation shows that MOGWO and other multi-objective metaheuristics can be an alternative method to solve problems of identification processes of multivariable systems.

Keywords: Diagnosis, Prognosis and System Identification, Industry Applications
Abstract: Modern industrial processes are hierarchically controlled in two levels. A continuous time control logic, such as Proportional integral derivative (PID) control, is implemented at the lower level to assure that the system behavior attains specifications of transient and permanent regimes, while at the higher level, a supervisory control ensures safety specifications for routine and non-routine operations. In general, both control strategies are projected without considering that the system components can suffer faults that can modify their expected behavior. Thus, a fault diagnosis strategy is fundamental to quickly indicate a fault event occurrence that can cause a deviation from the expected system behavior. In this paper, a discrete event diagnosis strategy is exploited for a two-level controlled tank liquid level system. To do so, we consider that a fault event can occur in the valve, which causes the valve to be stuck closed. We propose a modeling strategy for the valve that considers the fault consequences and its interaction with the remaining components. We show that this approach does not interfere with the control project, which allows the diagnoser synthesis to be achieved and implemented in an already-running controlled system.

Keywords: Diagnosis, Prognosis and System Identification, Machine Learning
Abstract: The technological growth has intensified the need for effective production processes, among them, the milling process using CNC machines, in order to guarantee precision and quality of the finished product. However, interrupted cutting processes have, in addition to the natural vibrational regime, unwanted vibrations known as Chatter, which result, among other factors, in excessive noise, premature tool wear, and low final quality. Thus, this study presents a comparison between Hotelling’s T2 method and Regression Algorithms for Chatter detection during the milling process. The results showed that the application of statistical technique is more feasible in terms of accuracy, surpassing by about 13,5% the accuracy of regression models, considering the samples in which the model was trained and, where the model was only tested, surpassed by about 34%.

Keywords: Diagnosis, Prognosis and System Identification, Power Electronics, Industry Applications
Abstract: Electric machines are commonly used to drive loads in industrial environments. Thus, load emulation is a viable and low-cost approach to assess whether the use of a machine is recommended for a given requirement, as it allows the emulation of various types of mechanical torques. Therefore, this article presents a design of a load emulation structure using a DC generator driven by a three-phase induction motor. In this way, the switching control technique was applied in the field circuit of the DC machine through a thyristor rectifier, allowing the draining and manipulation of the armature current. Through this work, analyzes are made with the results of emulations of constant, linear, quadratic and hyperbolic loads. Then, the behavior of the emulation structure is evaluated through data obtained from the drained armature current and mechanical torque, both experimentally and via simulation.

Keywords: Diagnosis, Prognosis and System Identification, Industry Applications
Abstract: This paper explores the application of system identification to a lubrication system found in heavy-duty diesel engines. These engines are equipped with a variable oil pump and a cooling piston jet. The objective is to establish a dynamic model that accurately captures the relationship between the duty cycle of the valves and the resulting pressure values under normal road operating conditions to be used as a digital twin of the system. Additionally, the study aims to determine whether a simple recursive model can sufficiently describe the system with enough precision. Different linear and nonlinear models were evaluated and validated to identify the best fit for the system. Ultimately, the system was described using a Hammerstein-Wiener model, resulting in an 83.86% Normalized Root Mean Squared Error (NRMSE) for main gallery pressure and 82.69% for piston cooling jet gallery pressure.

Keywords: Industry Applications, Power and Eneergy Systems, Electrical Machines and Drives
Abstract: A crescente preocupação com as alterações climáticas devido às emissões de gases de efeito estufa (GEE) tem fundamentado esforços globais para redução. As ações de eficiência energética (AEE) são interessantes em suas utilizações mais sustentáveis e vêm se expandido ao longo dos anos no setor industrial. A substituição de motores elétricos de baixo rendimento (BR) por motores de alto rendimento (AR) é uma AEE muito comum neste setor. Entretanto, motores AR ainda apresentam um elevado custo, tornando necessário uma análise técnico-econômica a fim de determinar a viabilidade da ação. Para isto, a análise dos custos do ciclo de vida (ACCV) tem se mostrado uma excelente alternativa para verificação de viabilidade econômica de AEE devido sua metodologia que considera as despesas durante todo o ciclo de vida do projeto ou equipamento. Considerando tomadas de decisões que envolvem otimização, o objetivo deste trabalho é apresentar uma metodologia para calcular o valor residual presente ao final do ciclo de vida, e como este se relaciona com o tempo de serviço dos motores e o período de estudo escolhido para o projeto. Na análise realizada, foram simulados dois estudos de caso envolvendo situações teóricas previstas e foi observado o impacto dos tempos de serviço na substituição de um motor de 50cv, 4 polos, presente em uma indústria local. O Net Savings é afetado pelo tempo de estudo, apenas quando a troca é realizada com a redução da potência do motor AR, gerando tempos de serviço diferentes entre o motor BR e o motor AR. Entretanto, é confirmada a ACCV como um bom método para predição do valor residual e evidências mostram que há tempos de estudo diferentes para maximizar o Net Savings e o custo Residual em um mesmo caso.

Keywords: Diagnosis, Prognosis and System Identification
Abstract: The presence of full-discharges in power transformers, which can be characterized by dielectric degradation between turns, is usually found in the stages preceding the total failure of the machine. Although several non-destructive techniques for monitoring these faults are applied, the Acoustic Emission technique stands out due to its low cost and ease of application. This paper uses a piezoelectric transducer to validate acoustic emission as a means to perform full-discharge evolution characterization, attaching it to a power transformer wall and applying different levels of full discharges on it. In order to validate the failure evolution, the apparent charge emitted by the flaw was calculated using a High Frequency Current Transformer (HFCT). The results presented in this article attest that acoustic emission has great potential to evaluate evolution of full-discharges in power transformers since it was found that the energy levels of the acoustic emission increase with the apparent charge.

Keywords: Resource Efficienty & Circular Economy Tracking
Abstract: The present work explores the use of interval extensions to reduce the carbon footprint of computer simulation. We present a method for estimating the amount of energy expended based on the number of operations performed and we demonstrate how different numerical representations of the same system can lead to a considerable reduction in the number of operations and, consequently, energy consumption. We have applied our technique on three scenarios for discrete simulation of the well-known Chua’s circuit. The results show a saving of approximately 22.50% in the values of emitted CO2 and consumed energy when using two different forms of representation of the same system. A simple rewrite of a differential equation could lead to a decrease in the number of operations, mainly the number of multiplications adopted in the representation of Chua’s circuit, resulting in reliable and more efficient simulations.

Keywords: Industry Applications, Automation and Process Control, Industry Data Science Applications
Abstract: This research contextualizes the problem of lack of usability and situational awareness provided by conventional supervision systems (SCADA), its relationship with synoptic screens, alarm systems, and industrial accidents. A standard is introduced to lead conventional systems to the “high performance” concept. All basic knowledge of this concept is shown to demonstrate the bases of the standard. And, finally, how to apply the standard to an industrial plant supervision project.

Keywords: Industrial Ultrasound Theory and Application, Industry Applications, Diagnosis, Prognosis and System Identification
Abstract: Pervious concrete is a construction and building material composed of cement, aggregate and water. It is an extremely porous material, with high permeability and sufficient mechanical characteristics that make it suitable for use in pavements with minor structural responsibility. It has been taken much attention during the past decades for “green city applications”, in order to minimize flooding, as well as city urban noise and heat. To design, build an maintainpervious concrete, there is a critical balance between mechanical strength and porosity (or hydraulic permeability) which is needed to satisfy. Nondestructive testing methods are therefore highly coveted to characterize such a complex material. Ultrasonic propagation techniques have been successfully tested to characterize pervious concrete. In this work, we present the experimental measurements of porosity, permeability, and propagation velocity for a set of pervious concrete samples. The porosity ranges from 15% to 35%, in this case the propagation speed ranges from 3000 m/s to 4150 m/s. Our goal is to fit a model to allow estimating porosity and permeability from experimental ultrasound measurements. The fit obtained in this work is compared with literature results, showing the large variability that exists in this material. Finally, a bi-dimensional numerical simulations shows the same general trend, in which ultrasonic wave speed decreases as porosity increases.

Keywords: Industrial Ultrasound Theory and Application
Abstract: This work aims to present the determination of the bandwidth of a capacitive ultrasound transducer with concentric V-shaped cavities. The finite element method (FEM) was used to determine the resonance frequency and bandwidth of the transducer. The finite element transducer model considered the air inside the grooves with triangular geometry and a polymeric membrane over the cavity. An electrostatic analysis was performed to obtain the distribution of electrostatic forces along the membrane. A static mechanical analysis was conducted to determine membrane deformation resulting from electrostatic force. Modal and harmonic analyses were performed to obtain the frequency response and consequently bandwidth. Subsequently, the experimental verification was carried out.

Keywords: Artificial Intelligence, Deep Learning and Machine Learning, Diagnosis, Prognosis and System Identification
Abstract: The goal of the study is to analyze the Ordinal Logistic Regression model to predict the classification classes associated with the risk of fire attribute. For the study provided, it was considered the data of the dataset related to the Programa Queimadas of Instituto Nacional de Pesquisas Espaciais(INPE), and also the data from the Instituto Nacional de Meteorologia (INMET), both of them with the data for the Parque acional do Araguaia(TO), Brazil. The idea was to validate a classification model capable of creating meaningful insights for the community, or reserve parks, making it easier to get the information associated with the risk of fire. The results of the study resulted in an accuracy of 82.13%, by comparing the classification results with the dataset associated with the test. An important consideration to be done for future studies is that the dataset analyzed was unbalanced, impacting considerably the results presented.

Keywords: Machine Learning, Industry Applications
Abstract: We apply SHapley Additive exPlanations (SHAP) feature selection method to improve fault detection models in an industrial production context. An illustrative synthetic process and the benchmark Tennessee Eastman Chemical Plant Simulator (TES) were used for the experiments. The principal hypothesis of this work is that the proposed SHAP feature selection methodology produces a subset of features with better discriminatory information, or at least approximately the same, than the original feature set. For the synthetic data experiment, the subset obtained achieved approximately the same results while reducing the number of features. For the experiment using the Tennessee Eastman simulation, the method- ology produced a reduced feature subset that was able to obtain, overall, better values of the F1-score and the Fault Detection Rate (FDR, aka. recall) compared to the original feature set. The set obtained using the proposed SHAP feature selection resulted in an average F1-score of 82.36% and an average FDR of 78.03% for all the faults. These results represent an increase of 2.77% and 1.84% of the F1-score and FDR, respectively, when compared to the original feature set while using an average of six features, a reduction of the cardinality by approximately 97.12%.

Keywords: Deep Learning and Machine Learning, Machine Learning, Smart Grids
Abstract: Este estudo analisa os fatores de sobrevivência das micro e pequenas empresas brasileiras de março a novembro de 2020, primeiro ano da pandemia de COVID-19. A pesquisa tem como foco analisar o impacto da pandemia em 66.005 empresas brasileiras por meio do banco de dados do Serviço Brasileiro de Apoio às Micro e Pequenas Empresas. A análise emprega métodos estatísticos inferenciais e usa um modelo de regressão linear para prever a variação do faturamento das empresas. Os resultados da investigação levaram à criação de um ranking de variáveis numéricas e categóricas mais críticas, revelando que os três fatores com maior significância estatística para a sobrevivência das empresas nesse período foram a manutenção de suas operações, pertencer a um ramo de atuação específico e ter uma plataforma de venda online pré-existente.

Keywords: Optimization Heuristics and Methods, Power and Eneergy Systems, Power Electronics
Abstract: Os sistemas elétricos de potência estão sujeitos a diversos fenômenos que causam efeitos indesejáveis, como a distorção harmônica. Uma forma eficaz de mitigar a distorção harmônica é através da instalação de filtros ativos. Sendo assim, torna-se importante a determinação dos melhores locais para instalação e o correto dimensionamento destes filtros. Desta forma, tem-se o problema de alocação ótima de equipamentos. Este é um problema de otimização complexo, sendo que diversas técnicas tem sido propostas para sua solução, com destaque para as meta-heurísticas. Neste sentido, este artigo apresenta uma aplicação de alocação ótima de filtro ativo shunt em sistemas de distribuição de energia elétrica utilizando o algoritmo de busca gravitacional, de modo a minimizar a taxa de distorção harmônica presente no circuito. Um sistema teste de 13 barras foi selecionado para a validação do método e a partir de simulações realizadas através dos softwares OpenDSS e Matlab, foi possível verificar a eficiência do algoritmo bem como obter bons resultados preliminares para alocação ótima do filtro ativo.

Keywords: Machine Learning, Resource Efficienty & Circular Economy Tracking, Optimization Heuristics and Methods
Abstract: Computer simulation, a powerful tool used in various scientific and engineering fields, boasts strong mathematical and data processing capabilities. However, its environmental impact, particularly carbon emissions and contribution to global climate change, has been largely overlooked. This study aims to improve code efficiency in simulation runs to reduce C02 emissions associated with computational simulation. We apply Horner's method to the NARMAX model, examining three classic chaotic systems: Lorenz, Rössler, and Mackey-Glass. Results reveal a substantial decrease of 27.86% in CO2 emissions, all while maintaining model accuracy. The proposed scheme provides a feasible and sustainable solution for reducing the carbon footprint associated with computational simulation.

Keywords: Artificial Intelligence, Automation and Process Control, Deep Learning and Machine Learning
Abstract: The data recorded by a steel company that uses lances in the steel refining process, indicate that the current method of removing lances from operation and maintenance is performed in a subjective and visual manner, leading to premature or delayed removal of equipment. In order to mitigate the impact of maintenance activities on the equipment's lifespan and operator safety, the use of measurements of the wear region on the lance nozzles as a proper index/indicator. In this study, a wear analysis was conducted on lance nozzles that were removed from operation due to nozzle wear. The study utilized the real-time instance segmentation method, employing the Yolact model to detect the wear region and an algorithm to measure vertical deviations in the wear on the metal surface of the equipment. The findings suggest that measuring the wear region on the lances is an effective strategy to minimize the impact on the maintenance plan of the sector, and can increase equipment lifespan and operator safety. The research results were satisfactory, highlighting the importance of objective and precise analysis of wear on the surface of lance tips to ensure equipment efficiency and durability.

Keywords: Industry Data Science Applications, Automation and Process Control, Industry Applications
Abstract: In this paper, specialized classifiers are trained using features selected via SHAP method for the purpose of diagnosing multiple faults in industrial processes. The multi-class problem of fault diagnosis is decomposed via One-vs-All scheme. Tennessee Eastman process is considered, and for each fault, a Random Forest classifier is trained using features selected via SHAP method. Four feature selection techniques are compared with respect to their performance and the cardinality of the selected feature set.SHAP method presented approximately 89% of the F1-score, used as the performance index, with similar values of the other methods. However,the SHAP feature selection selects fewer features to achieve this result,about four features less in comparison to Recursive Feature Elimination (RFE)which selected eight in average. The study suggests that SHAP can reduce the dimensionality of the dataset with a good F1-score performance.

Keywords: Blockchain Technology, Industry Applications
Abstract: The current global trade wars, rising logistics costs, and the impact of the Covid-19 pandemic have compelled companies to re-evaluate their production strategies. An increasingly popular approach to address these issues is decentralized production, which involves manufacturing products near to the customers to reduce logistics and warehousing expenses, improve lead times, and decrease carbon emissions. However, the decentralized nature of the production network necessitates a secure communication platform for stakeholders to access authentic data in real-time. In this regard, blockchain technology is identified as a promising solution due to its characteristics, which make it suitable for product data management across its lifecycle, especially in a decentralized production network. Therefore, this work proposes a conceptual framework for a blockchain-based product lifecycle management (PLM) system to ensure data provenance, security, authenticity, and trusted traceability in a decentralized production network. Moreover, this study highlights that there is currently no such practical model available for decentralized production scenario. Consequently, we argue that successful deployment of a blockchain-based network would require a collaborative approach that involves close interaction and cooperation among all stakeholders in the network.

Keywords: Cyber Physical Systems, Digital Twins and Knowledge Systems, Industry 4.0, Industry Applications
Abstract: O artigo propõe uma plataforma de Gêmeo Digital capaz de auxiliar no monitoramento de plantas industriais e seus processos físicos. O objetivo da plataforma é de criar um ambiente virtual capaz de simular operações e procedimentos vinculados ao processo industrial, possibilitando a realização de testes de diferentes configurações de operação sem a alteração do maquinário físico e sem expor os operadores e o ativo a risco. O artigo apresenta um exemplo real de aplicação da plataforma na simulação do processo físico de uma planta de manufatura com parametrização configurável pelo operador. Os experimentos realizados confirmaram a capacidade da plataforma de reproduzir o processo físico e executar testes no ambiente de realidade virtual sem danificar o equipamento ou interromper a produção da planta real.

Keywords: Internet of Things, Industry 4.0, Industry Applications
Abstract: Considerando a demanda por soluções sustentáveis na indústria siderúrgica como o uso de carvão vegetal em detrimento do carvão mineral, este artigo descreve a especificação e desenvolvimento de um sistema de Internet das Coisas (IoT) para monitoramento de estufas destinadas ao plantio de mudas para uso como termo redutor no processo produtivo da empresa Gerdau. O projeto foi realizado em 10 semanas por uma equipe de alunos de primeiro ano da graduação do Instituto de Tecnologia e Liderança (Inteli). O método RM-ODP foi utilizado para a especificação e modelagem do sistema. Uma prova de conceito funcional composta por interface de usuário, banco de dados, API (Application Programming Interface) e um protótipo impermeável de dispositivo IoT foram desenvolvidos com sucesso. O código-fonte do projeto e manual de instruções estão disponíveis sob uma licença de código aberto.

Keywords: Internet of Things, Industry 4.0, Big Data in Industry Applications
Abstract: The Internet of Things (IoT) market is moving from proofs of concept and pilots to more comprehensive production environments, achieving a plateau of sustainability in consumer applications. The success of IoT applications is highly dependent on the quality of the data received, transmitted, and processed. This article presents a scoping review of how data quality (DQ) management and manifestations of DQ problems have been addressed in the IoT context from 2016 to 2022, collecting methods, datasets, standards, and use case segments. First, a landscape is presented, dividing it into two groups: massive device applications and mission-critical applications, each with its own quality demand. Then, after screening more than 3,200 articles from two distinct databases, 124 full-text articles were selected to collect data and insights. Within the criteria, 70% of the selected articles were published in the year 2022 and almost 60% addressed the dimension of credibility (integrity). The findings are expected to help researchers direct their future efforts and present opportunities that may be addressed, such as not mentioned DQ dimensions, new methods using emerging technologies, or new use cases that are underexploited.

Keywords: Virtualization, Simulation Techniques and Augmented Reality, Diagnosis, Prognosis and System Identification
Abstract: The current conjuncture of the International System is driven by Revolution 4.0. Constructive simulation is part of the context of this revolution. The purpose of this article is to present a Case of the use of tactical simulation on the COMBATER platform, its application in the teaching-learning process of Brazilian Army captains and the implementation of simulation as a teaching tool, highlighting the possibility of using it for operational research. From the year 2022, the use of the COMBATER software began to be applied to the analysis of the lines of action developed by School for the Improvement of Officers (Escola de Aperfeiçoamento de Oficiais - EsAO) students. This type of job aims to put the Student-Captain's planning to the test, making him develop alternative lines of action that can be tested and improved with the use of COMBATER. This case study was based on the planning of an operation performed by a student of the Infantry Course at EsAO. Two different troop compositions were compared and tested (CoA 1 – with artillery and CoA 2 – without artillery). Comparing CoA 1 and CoA 2 indicators, and based on Commander’s Directive, the result shows better indicators for CoA 1 (Student t test, p=0,021, Effect Size (Cohen’s d) = -0,506). It can be concluded that COMBATER system has plenty of conditions to be utilized to enhance the learning of Brazilian army officers at the tactical level.

Keywords: Virtualization, Simulation Techniques and Augmented Reality, Autonomous Vehicles and Drones, Electrical Machines and Drives
Abstract: This work aims to describe a dynamic simulation model of a wheelchair subjected to external disturbances arising from the misalignment of the castor wheels with the direction of movement. It is known that when starting its trajectory, the wheelchair may have initial conditions that cause disturbances to its movement. Of these initial conditions, the one that causes the most prominent effect is the misalignment of the castor wheels, as it causes a high resistant torque on one side of the vehicle, generating a situation of momentary instability of the trajectory, causing an error that propagates throughout the movement. subsequent. Therefore, this work proposes to model this effect through the kinematic determination of the steering angle of the front wheels, as well as the use of the MFeval® solver, based on Pacejka’s formula, to determine the lateral forces.

Keywords: Virtualization, Simulation Techniques and Augmented Reality, Industry 4.0, Automation and Process Control
Abstract: Abstract— This paper presents the study of process` improvement in an industry that uses die sets to stamp products manufactured in steel. The process includes one hydraulic press latest generation which has the assistance of dedicated automation and robotics, who feed the raw material, execute the transference between the working stations within the press, and finally perform inspection of 100% of the products. The market is demanding to mitigate the production costs. Therefore, there is a pressure for faster processes with proved effectiveness. The subject of this study is to maximize the production of several die sets throughout simulations on virtual environment by means of applicative Delmia®, from Dassault Systemes, and DigiSim®, from Schuler AG. The overall results of the process were analyzed and reworked utilizing the tools of the Lean Manufacturing, like Gant Chart, Value Stream Mapping and indicators, like Overall Equipment Effectiveness (OEE), Lead Time, non-value adding (NVA), value-adding (VA) and Defect Ratio. They revealed increased OEE from 63% to 92%, eliminated several wastes and optimized process cycle time.

Keywords: Power Electronics, Smart Grids, Renewable Energy
Abstract: Grid-forming inverters is getting special attention of industries and academia due to their important role in the realization of microgrids. A crucial feature of them is to have an accurate voltage control. This paper proposes a digital phase lead-and-lag voltage control based on frequency response approach for single-phase half-bridge DC-AC converters. Initially, the system is modeled through the small-signal technique. Then, the controller is designed based on the frequency response approach. The discretization through Tustin and Backward methods are presented and compared. Moreover, designing the controller in discrete-time domain by conventional methods using the fictitious w-domain is also presented. The system is tested in a Controller Hardware-in-Loop setup, where the power topology runs in the HIL402 device and the digital voltage controller runs in the TMS320FF28335 digital signal controllers. Scenarios like initialization, nonlinear load and oscillation at the DC voltage are performed. Results show the efficacy of the methodology proposed in this paper.

Keywords: Power Electronics, Power and Eneergy Systems, Renewable Energy
Abstract: The present work aims at performing the design of a high-efficiency interlinking converter for DC distribution systems and to evaluate the impact of the design parameters on the converter efficiency curve. The design method employed the PSIM Thermal Module to estimate the power losses of the switches and a MATLAB inductor sizing routine was built for inductor design and power loss calculation. To evaluate and decide on the best design parameters, the entire load/generation curve was taken into account leading to a converter with efficiency above 98%. To achieve this, it was observed that low switching frequency, dc link voltage at 500V, thermal design with lower junction temperature, and EMI and output filter designs with low current ripple were necessary to improve the efficiency of the proposed converter.

Keywords: Power Electronics, Power Quality, Smart Grids
Abstract: This work studies the effects of delay compensation on the Optimal Switching Vector Model Predictive Control (OSV-MPC) strategy applied to a grid-forming inverter in an islanded microgrid. The main objective is to compare the power quality of the output voltage synthesized by the controller in three scenarios: standard OSV-MPC, OSV-MPC with delay compensation and OSVMPC with delay compensation and Lagrange extrapolation on the output voltage reference signal. A processor-in-the-loop simulation scheme is implemented, with a Texas Instruments F-28379D microcontroller holding the control algorithm and MATLAB/Simulink being used to model the power system. Five different load conditions are considered: no load, capacitive, inductive, non-linear and unbalanced loads. The total harmonic distortion (THD), mean absolute error (MAE) and total frequency spread (TFS) are calculated for each case, as well as the processing time of each OSV-MPC variation is measured.

Keywords: Power Electronics, Power and Eneergy Systems, Renewable Energy
Abstract: In this paper, a comparative analysis of different coupled-inductor designs applied to Y-Source DC-DC converters is presented. Many works in the literature discuss the impedance source networks but few analyze the implications of the coupled-inductor design on the converter operation, considering the impact of equivalent series resistances or core losses. Hence, this paper aims to evaluate the impact of three different coupled-inductor designs on the Y-Source DC-DC converter efficiency and core temperature, considering the strategy of equivalent series reduction by Litz wires with different wires number or core stacking, to reduce core reluctance. Using a DC-DC Y-Source converter with 230 W rated power, the different design strategies are outlined such that the operational requirements are met. Through simulation and experimental results, it can be observed that the adoption of a greater number of wires in the Litz arrangement is more effective to increase efficiency when compared to core stacking. However, lower temperatures are achieved only with the core stack, and leakage inductance issues arise due to loose windings with a reduction of effective voltage gain. The results of this work help to understand the relevance of different designs of coupled inductors and how they reflect on the efficiency of the converter and the core temperature. Furthermore, it can be used to improve the design of Y-source converters and advance the technological status of this power converter topology.

Keywords: Power Electronics, Power and Eneergy Systems, Renewable Energy
Abstract: The modular multilevel converter (MMC) became attractive for photovoltaic solar energy applications due to its intrinsic characteristics such as modular structure and flexible operation, achieving high efficiency compared to other multilevel converter topologies. In this way, being able to adapt the converter in topologies derived from the MMC, in which the number of components varies, isolated dc-dc stage, common DC bus or with separate sources, high-frequency transformers instead of inductors and modifications of other passive elements; to improve energy production or to balance the energy generated between the arms. In this paper, a new topology for an MMC-based PV system is proposed, in which, the PV panels are used to energize an isolated DC-DC converter which in turn is connected to a submodule, a redundant submodule (rSM) is also placed in each arm to balance the possible power mismatch in each phase of the MMC, each isolated DC-DC converter is controlled individually and a local MPPT (Maximum power point of tracking) is also included which optimizes the energy extraction in each PV submodule. Finally, the dq−reference frame control is used for the output current control and the electrical grid connection to validate the proposed system. The time-domain simulations are performed using the Simulink/Matlab software.

Keywords: Bioprocessess Applied to Industry, Micro & Nano Manufacturing, Industry Applications
Abstract: A biomimética é uma área de pesquisa interdisciplinar que navega em diversos campos, como engenharia, arquitetura, design entre tantos outros. Suas aplicações são amplamente utilizadas no processo de design de produtos, sendo uma poderosa ferramenta de inovação. Este estudo teve como objetivo desenvolver uma metodologia para análise de produtos com características biomiméticas. A metodologia proposta foi aplicada em um estudo de caso, onde foi analisado o princípio ativo biomimético SYN®-AKE, utilizado no combate ao envelhecimento da pele, que é um peptídeo sintético desenvolvido com base na atividade do peptídeo natural, Waglerin-1, encontrado no veneno da cobra víbora (Tropidolaemus Wagleri). A metodologia foi constituída por três etapas de avaliação do produto, sendo elas a análise da forma e função natural, os benefícios apresentados e sua relação com o meio ambiente. O estudo de caso comprovou a aplicabilidade da metodologia. Além disso, este projeto identificou que são necessárias mais pesquisas na área de biomimética, com o propósito de criar metodologias simples e acessíveis, além de disseminar a ciência e o seu poder de inovação.

Keywords: Industry Applications, Industry 4.0, Power Electronics
Abstract: The performance of different automotive vehicles can be compared based on measurements of their real conditions parameters recorded over time, such as position, acceleration, battery consumption, engine speed, fuel type, transmission, odometry, and engine cooling temperature, among others. These parameters are essential for a true picture of the cars' situation, helping to reduce maintenance, e.g., fuel waste, toxic gas emissions, and predictive maintenance. It is important to note that in the literature, several pieces of equipment are inserted in the vehicle's network and exported information to the user online. However, products that access vehicle data and store it for an extended period are not easily available on the market. In most cases, the user only has access to products that show the vehicle's data while the device is connected. When the car is turned off, the data is lost. This work presents a product that fills these gaps, giving the owner a long-term history of the vehicle's information, showing it as easy to understand on a developed interface, and using accessible products to build the device. The tests indicated the product's effectiveness in getting long-term vehicle data for more than six months only using 1,5% of its storage capacity. For last, research contemplating 100 possible customers was also implemented to validate product price and interest on the market.

Keywords: Life Support Systems & Techniques, Industry Applications, Power Electronics
Abstract: Repouse is indispensable for the human body, one of its main functions being to replenish energy. During sleep, the body’s important restorative activities are performed by the organism, which is a basic human need. With awareness of the dimension that sleep represents and the need to improve its quality, the importance of monitoring in real time becomes evident. Based on this, a technique capable of obtaining characteristics of a signal, such as its frequency, as well as being able to be applied to sleep waves, is the Fast Fourier Transform. However, to have a good use, a considerable number of sample cycles is necessary, which demands a certain computational effort. In this sense, we sought to apply the Phase-Locked Loop technique in this work. Thus, a Fourier-based synchronization algorithm is proposed in order to track low-frequency brain waves during sleep. It is also worth noting that this method is capable of performing the estimates in just one cycle. Therefore, the objective is to obtain the estimated curve referring to the frequency and an efficient synchronization algorithm that is able to track deep sleep in real time.

Keywords: Industry Applications, Power Quality, Power and Eneergy Systems
Abstract: An adequate power factor is a parameter of fundamental importance for both end users and utilities, given the negative impacts that a low power factor represents in terms of capacity reduction in electrical installations, equipment, as well as in transmission systems. In cases where capacitor banks are estimated from energy bills, there is a risk of oversizing when considering the billed demand because it does not always reflect the lower power factor. This paper evaluates three capacitor bank estimation methods based on the bill and continuous metering systems applied in a case study of a medium voltage consumer in Brazil. The results show that the monitoring systems result in fairly accurate estimates of the capacity of the banks, being compared with the values estimated from the bill in consumers without such systems, the results were implemented to verify the methodology.

Keywords: Power and Eneergy Systems, Industry Applications
Abstract: This work presents a protection scheme based on Short-Time Fourier Transform for fault detection in an MMC-Based VSC-HVDC system. To perform these tasks only local signals are used and communication links are not required. A robust scheme based on DC current spectrum is evaluated. The proposed method has been tested for different fault locations and resistances in a two-terminal HVDC system with a monopole DC line. The adopted HVDC system was modeled in PSCAD, while the proposed algorithm was developed in Matlab. The results show that the proposed scheme is able to detect faults within a few milliseconds correctly.

Keywords: Industry Applications, Optimization Heuristics and Methods, Virtualization, Simulation Techniques and Augmented Reality
Abstract: Control of natural frequencies in structural design is a challenging issue for engineers. Local modes can prevent the solution from reaching the optimum point, especially in discrete problems. This paper presents a topology optimization method with simulated annealing to minimize and control the first natural frequency of a structure with binary elements. The algorithm generates new solutions by adding or removing solid elements in a design domain and evaluates the new solutions by the Metropolis-Hastings algorithm. The algorithm was applied successfully to a clamped square plate as the design domain and with solid mass at the center. The results show a smooth convergence to the optimum solution with reasonable computational costs. The design reaches a specific small first natural frequency in the non-convex topology optimization problem. The algorithm can be used efficiently in the design of structures with specific natural frequencies and constraints.

Keywords: Industry Applications, Industry 4.0, Automation and Process Control
Abstract: This paper presents as a contribution an Industrial Internet system that enables the distributed execution of assembly and counting of industrial parts, using Function Blocks of Standard IEC 61499, which normally occurs in a centralized way. The Function Blocks run on microcontrollers that communicate via the OPC UA (Open Platform Communications Unified Architecture) protocol with the FACTORY I/O simulation software for manufacturing plants operating on an end device. Experiments were carried out to measure the latency obtained with the OPC UA and the results confirm that the solution does not add delays that affect the application's operation.

Keywords: Industry Applications, Power Quality, Power and Eneergy Systems
Abstract: Os transformadores de potência são equipamentos fundamentais nos sistemas elétricos atuais. Desempenham papel importante nos vários níveis da rede e devem ser protegidos contra eventuais falhas e eventos que por ventura possam surgir. Vários esquemas de proteção foram e são desenvolvidos até hoje a fim de manterem a integridade de tais equipamentos. Para transformadores de maior porte a proteção diferencial se destaca pela rápida detecção de falhas, sendo discutida e apresentada durante este trabalho. Alguns eventos e manobras que impactam diretamente no desempenho da função diferencial também são discutidos neste trabalho. Na energização de transformadores, por exemplo, o surgimento do fenômeno de inrush pode fazer com que a proteção atue de forma equivocada, e assim, é apresentado o método mais comum adotado para contornar tal problema que diferencia o inrush de uma falha na qual a proteção deve realmente atuar. Para isso, utiliza-se o software ATPdraw nas simulações de situações que podem impactar na proteção.

Keywords: Optimization Heuristics and Methods, Power and Eneergy Systems, Power Electronics
Abstract: O uso de equipamentos FACTS (Flexible AC Transmission System) pode trazer diversos benefícios para os sistemas elétricos de potência, permitindo o ajuste do fluxo de potência e a otimização no uso destes sistemas. Para tal fim, torna-se importante a determinação dos melhores locais e das melhores configurações para a instalação destes equipamentos. Neste contexto, este artigo apresenta a aplicação do algoritmo de busca gravitacional para a alocação ótima de compensador série síncrono estático em sistemas elétricos com o objetivo de minimização de perdas ativas no sistema. A metodologia desenvolvida foi validada através de simulações realizadas com um sistema de potência teste de nove barras e resultados preliminares promissores foram obtidos.

Keywords: Deep Learning and Machine Learning, Big Data in Industry Applications, Diagnosis, Prognosis and System Identification
Abstract: While reward-based crowdfunding plat- forms centered like Kickstarter in the United States, allow entrepreneurs or well-off investors like industrial owners to gather assets and seek patron support, they have evolved into an option for generating funds via an internet platform. Conversely, these crowdfunding initiatives pose innovation challenges due to the uncertainty of receiving support and success. Both project developers and supporters may benefit from it for better knowledge and more accurate forecasting of project success. Analyzing a completed project information, this study aims to identify critical success characteristics of crowdfunding. It investigates the effectiveness of wide-and-deep learning in predicting models. These findings can help fundraisers understand the likelihood of successful fundraising initiatives.

Keywords: Optimization Heuristics and Methods
Abstract: The Net Present Value method is classically one of the most used in investment analysis. Nevertheless, it is a static approach and does not incorporate flexibilities throughout the life cycle of projects, such as postponement, and other events. The aim of this work was to evaluate a developed heuristic method based on the pair displacement technique applied to a set of theoretical investment projects collected in specialized literature and a set of non-financial investment projects implemented by a multinational automaker installed in Brazil. Conceptually, the developed model combines the fundamentals of Real Options Theory with local search heuristics. Despite the relevance of the topic, there is a lack of work on investment project sequencing in the literature. The results show that the developed heuristic can reduce costs by up to 15% when all necessary capital is available at the beginning of the project period.

Keywords: Machine Learning, Industry Data Science Applications, Industry 4.0
Abstract: Near infrared spectroscopy (NIRS) is an analytical technique that is gaining popularity in the food industry due to its low operating costs, rapid analysis and non-destructive sample technique. Numerous studies have shown the relevance of NIR spectra analysis to determine certain quality attributes of food. This makes it attractive for use in quality control and continuous monitoring of food processing. However, the calibration process of NIR is difficult and time-consuming. Depending on the configuration of the NIR instrument, the sample to be analyzed and the attribute to be predicted, the analysis methods and techniques vary. This makes calibration a challenge for many manufacturers. This article aims to develop a decision support tool to assess food properties based on the analysis of selected features of NIR spectra. It intends to provide support to calibrate a predictive model based on NIR spectra. The methodology-based decision support tool was evaluated on cocoa bean samples. The tool suggested using the SG filter technique and PLSR machine learning model to predict the moisture and fat content of cocoa beans. The PLSR model with 4 components trained from 63 wavelengths obtained excellent results for the prediction of moisture content with an R2CV of 0.9 and an RMSEP of 0.28. While the PLSR model with 8 components trained from 166 wavelengths obtained satisfactory results for the prediction of fat content with an R2CV of 0.93 and an RMSEP of 1.52.

Keywords: Artificial Intelligence, Power and Eneergy Systems, Deep Learning and Machine Learning
Abstract: This research presents a machine learning-based application developed to improve the energy restoration process in distribution systems. Based on energy outage events generated by consumer complaints, the proposed method automatically analyzes data patterns to identify collective events, i.e., outages that affect several consumers simultaneously. In this way, operators can prioritize service in occurrences with a higher amount of affected customers and as a consequence, improve the quality of service. The method has been applied in an energy utility bringing practical experiences in the dispatch process of maintenance teams. The results contemplate improvements of up to 20% in the classification of occurrences, a reduction in the identification time of collective occurrences from a few hours to a few minutes and significant improvement in the reliability indicators.

Keywords: Machine Learning, Diagnosis, Prognosis and System Identification, Power and Eneergy Systems
Abstract: Nowadays, machine learning methods have been widely used in the detection, diagnosis, and localization of Partial Discharges (PDs) in power transformers, such a fact that allows early identification of failures in the insulating system and the proper scheduling of maintenance activities. Before the classifiers training stage, however, features extraction and selection from the PDs signals is a fundamental step, procedures directly related to the models' validation performance, and that can avoid their overfitting. Therefore, in this paper, methods for features extraction and selection are investigated, regarding the PDs location between layers and sections of the transformers windings. For this purpose, features extracted from the PDs' high-frequency current signals were selected by the Stepwise, SVM-RFE, and CasCor methods, being the resulting subsets applied in the training of SVM classifiers constituting a localization system. The results show that the features subset arising from the CasCor selection method provides SVM models with better performance for locating PDs, either between layers or sections of the winding.

Keywords: Artificial Intelligence, Deep Learning and Machine Learning, Machine Learning
Abstract: While time-lapse imaging is desirable for recording dynamic development processes, such as cell division and cell migration, the image quality suffers from the fluorescent blending and phototoxicity. Theoretically, the confocal microscopy can collect images with high resolution if the livability is not the priority. In this work, we leverage the image quality of time-lapse images by formulating the transformation from time-lapse image to single-point image as an adversarial learning task, which bypasses the lack of pairwise images for training. Compared with other non-blind image denoising algorithms, our method shows compelling performance in restoring imaging targets.

Keywords: Industry 4.0, Internet of Things, Cyber Physical Systems, Digital Twins and Knowledge Systems
Abstract: Industrial communication plays a crucial role in modern automation by enabling control, monitoring, quality assessment, maintenance, and integration of management systems in production and manufacturing processes. OPC UA has emerged as one of the most widely utilized protocols in recent years, as evidenced by its growing number of applications, and is considered to be one of the most promising protocols for the future. Given its significance, this work aims to provide an overview that characterizes the current state of the protocol. To accomplish this, a systematic review of 238 relevant studies was conducted to extract relevant data. The results obtained provide an up-to-date overview of the field, as well as identify several potential research directions, challenges, and opportunities for further research on OPC UA.

Keywords: Additive Manufaturing, Machine Learning, Industry 4.0
Abstract: Additive manufacturing (AM) strengthens mass-customized components manufacturing because of its high flexibility, even for metals like Laser Powder Bed Fusion (LPBF). Nevertheless, the need to improve the surface quality with other operations after LPBF and some predictability issues concerning the product’s final properties parameters are still hindering this technology. In this way, machine learning applications are gaining even more attention in dealing with manufacturing management. So, this study investigated ways to predict the roughness of additively manufactured maraging steel upon milling using regression techniques. The linear regression traditionally used for prediction in the Design of Experiments was compared with the gradient boosting (GBR) and multilayer perceptron (MLPR) regressors. After tuning the model hyperparameters, the MLPR approach outperformed the other two techniques in modeling surface roughness. Also, it was possible to reach a coefficient of determination higher than 0.95 with acceptable error metrics during Ra predictions. Hence, the obtained findings can be useful for developing data-driven control systems in the scope of Industry 4.0

Keywords: Additive Manufaturing, Machine Learning, Artificial Intelligence
Abstract: Additive manufacturing is a technology of Industry 4.0 widely used for various purposes. In the context of low-cost 3D printers, printing failures often manifest as a recurrent concern. These failures are typically diagnosed after a considerable amount of time has elapsed since the printing procedure, or upon its completion. This work proposes a method for the intelligent detection of failures in 3D printing, based on a low-cost accelerometer for vibration analysis. For each printing operating condition, the parameters were investigated, such as the printing speed, 3D printer bed leveling, filament extrusion temperature and bed temperature. A dataset was created based on data collected employing a widely used low-cost 3D printer. Two different algorithms for analyzing and classifying the samples were investigated, the Multilayer Perceptron (MLP) and Support Vector Machine (SVM). Intelligent fault diagnosis system developed presented good results, reaching until 92.3% of accuracy.

Keywords: Additive Manufaturing
Abstract: As Superfícies Mínimas Triplamente Periódicas (TPMS) têm ganhado atenção no contexto da manufatura avançada devido às suas propriedades mecânicas, permitindo a produção de estruturas leves com alta resistência mecânica e grande capacidade de absorção de energia. Dentro desse contexto, diferentes estruturas Gyroids foram fabricadas por meio da Modelagem por Fusão e Deposição (FDM), variando-se o número de células e a densidade gradual da estrutura para a investigação dos efeitos destas variações sobre as propriedades mecânicas. As análises demonstraram que a variação da densidade gradual e do número de células dessas estruturas modificaram as propriedades mecânicas e, assim, parâmetros ótimos de projeto puderam ser delineados.

Keywords: Industry 4.0, Virtualization, Simulation Techniques and Augmented Reality, Internet of Things
Abstract: A indústria está, atualmente, passando pela quarta revolução industrial, ou Indústria 4.0 (I4.0), com tecnologias voltadas para tornar as manufaturas mais inteligentes e conectadas. Para isso, é fundamental comprender o comportamento dos processos industriais, aumentar a eficiência da linha de produção e fornecer os insumos necessários para a tomada de decisão. Nesse contexto, várias tecnologias digitais têm sido utilizadas para aprimorar a interação com os processos industriais. A finalidade do trabalho é desenvolver uma solução digital para monitorar e organizar o acesso aos dados de uma planta piloto em linha com a Indústria 4.0. A solução inclui um aplicativo móvel que permite rastrear os dados usando realidade aumentada, além de incorporar funcionalidades como o painel de informações disponibilizado na HMI, acesso remoto a toda a documentação e consulta à base de dados.

Keywords: Internet of Things, Smart Grids, Power and Eneergy Systems
Abstract: In this paper we present a performance analysis of the broadband power line communication (BPL) technology for underground medium voltage (MV) power grids with ring topology. The evaluated ring topology optimizes the BPL communication network in terms of resiliency, a fundamental requirement of Smart Grids. Exploiting an experimental small-scale prototype, we obtained satisfactory results on the powerline communication (PLC) interface of the modems for both uplink and downlink, even when a power line link failure occurs.

We achieved transmission rates at the physical and ethernet communication interfaces between 70 and 75 Mbps when there is a direct connection; and 60 to 67 Mbps when link failures are introduced in the ring topology. This experimental analysis paves the way towards resilient underground BPL deployments.

Keywords: Internet of Things, Power and Eneergy Systems, Power Quality
Abstract: A adoção de medidas que tornam campus universitários em smart campus traz diversos benefícios ao funcionamento do campus e a todos seus integrantes – alunos, professores e demais funcionários. Uma das principais estratégias para a implementação dessas medidas é a integração dos dados das diferentes aplicações existentes, permitindo o desenvolvimento de metodologias de análise para o uso inteligente dos dados e recursos disponíveis. Estruturas e aplicações de smart campus têm sido muito exploradas na literatura, porém com pouco detalhamento do ponto de vista dos dispositivos de hardware e software ou sobre como é realizada a integração dos dados gerados pelo campus. Nesse sentido, este artigo se propõe a descrever e discutir a arquitetura baseada em IoT (Internet das Coisas, do inglês Internet of Things) que vem sendo desenvolvida no Instituto de Ciência e Tecnologia - Campus Sorocaba (ICTS), UNESP, com foco especial nos desafios para sua implementação. O artigo explora três assuntos principais: uma revisão bibliográfica de outros modelos de smart campus existentes na literatura, a definição da arquitetura IoT e, finalmente, o detalhamento sobre a integração dos diferentes dados disponíveis. Por meio da adoção da arquitetura IoT apresentada neste trabalho, obteve-se um sistema escalável e replicável, para aquisição e armazenamento de dados do consumo de água e do consumo energético desagregado em diversos pontos do quadro de distribuição de energia elétrica do ICTS.

Keywords: Automation and Process Control, Internet of Things, Industry Applications
Abstract: The number of breweries in Brazil has been rapidly increasing in recent years, especially with the creation of new microbreweries, which are typically small and medium-sized companies that focus on product innovation but still have a manual production process. In this context, this work aims to identify the profile of these breweries in the Brazilian market, understanding their main KPIs and level of automation. From this point, it suggests an architecture for digital transformation, which provides transparency in the operation of the industrial process and generates data that could be used to add value to the microbreweries, enabling them to enhance their operations and elevate the standard of their products.

Keywords: Power Electronics, Power and Eneergy Systems, Renewable Energy
Abstract: This paper presents an auxiliary circuit for the current-fed half-bridge (CFHB) converter, aiming to clamp the high voltage spikes across the main switches caused by the energy stored in the leakage inductance of the power transformer and recover the energy present in the clamping capacitor. The proposed auxiliary circuit employs only one active switch in the same ground reference of the main switches. The proposed converter operates with zero-current switching (ZCS) at turn-on and zero-voltage switching (ZVS) at turn-off of the main switches. Besides that, it also provides ZCS at the turn-on of the auxiliary switch and turn-off of the auxiliary diode. The energy is recovered to the load without losing galvanic isolation due to coupled inductors in the auxiliary circuit. A 360 W prototype was built to validate the analysis and design proposed.

Keywords: Power Electronics, Electrical Machines and Drives
Abstract: This work shows rotor field oriented indirect vector control for the single-phase induction motor. Inner current control is implemented using three methods: hysteresis, synchronous PI and predictive. The main purpose of this study is to realize a model simulation of the single-phase induction motor, vector control and current control using the Matlab, Simulink development platform. Simulation results shows advantages of predictive control in comparison with conventional methods considering as reference parameters: harmonic distortion and switching frequency. Controllers performance is evaluated with the motor running with mechanical load. The behavior of stator and rotor currents, electromagnetic torque, rotor flux and mechanical rotor speed are shown. Values obtained are presented in conjunction with graphical views of analyzed magnitudes.

Keywords: Power Electronics, Renewable Energy, Power and Eneergy Systems
Abstract: This paper presents a controller design procedure for a digital virtual synchronous generator (VSG) strategy applied to grid-forming distributed generation (DG) systems. The main contribution of the design methodology is to support researchers who are implementing DG systems with VSG-based power flow control strategies in a digital environment. For this purpose, an impedance model describes the DG power flow dynamic characteristics. Then, the digital VSG controllers parameters design uses the root-locus method (RLM) to achieve the desired dynamic performance. A case study demonstrates the effectiveness of the DG system with a VSG control strategy designed based on the proposed design method. Furthermore, the results evaluate the VSG controller's dynamic performance under the system's equivalent impedance variations.

Keywords: Power Electronics, Industrial Lighting
Abstract: This work presents a comparison study concerning two topologies of low frequency off-line LED (light-emitting diodes) drivers, based on the boost pre-regulator, and one high frequency off-line LED Driver Based on the DCM SEPIC PFC (power-factor correction) converter. The converters were devised to supply a conventional street lighting LED luminaire. The study took into account the main electrical characteristics of those converters and also some constructive attributes of the prototypes. The implemented LED drivers were devised to supply an LED lamp consisting of 96 series-associated high-power LEDs. The LED drivers were evaluated in laboratory being fed by a 220V, 60 Hz, low distortion ac power supply, and presented an input power of about 200 W, which is a typical power level for street lighting LED luminaires. These LED drivers presented a high power-factor (PF) and a low total harmonic distortion (THD). The results concerning all drivers were organized in the form of tables. The study allowed highlighting the main advantages and drawbacks of each design approach, i.e., the high-frequency concept against the low-frequency strategy.

Keywords: Power Electronics
Abstract: In recent years, there is a growing need to develop and evaluate power converters for use in many areas. Therefore, it is very important to study and design controllers to regulate these. Then, this article proposes the modeling and control applied to a bidirectional three-phase interleaved boost converter. Also, the mathematical modeling of the converter used is introduced in this work, presenting the switched, average and average linearized models. The control system is developed from the previous modeling, and was divided into classic and discrete controls. Finally, the proposal is validated by simulations results obtained into simulation environment PSIM-Matlab. For this, two tests were simulated, one for each type of control, changing the load value, in order to demonstrate the effectiveness of these.

Keywords: Power Electronics, Industrial Lighting
Abstract: This work presents the study of an off-line LED driver based on the LC series resonant converter operating with variable frequency. An approach called Active Ripple Compensation (ARC) has been used for minimizing the converter bulk capacitance, improving the driver lifespan and reducing its volume. This technique is based on the low-frequency large-signal modulation of the switching frequency, which allows for reduction of the filtering capacitance and can increase or reduce the harmonic content of the input current. In addition, design abacuses are proposed in order to assist the sizing of the converter elements from the choice of the average value and ripple level of the LED current. By means of the design procedure presented in this work, the amount of capacitance reduction and input current distortion can be fully controlled and theoretically predicted. Simulation results considering a 96-W LED lamp supplied from a 127-V 60-Hz grid were carried out. The results attested the superior performance of the proposed methodology, with a capacitance reduction of 66.6%.

Keywords: Power Electronics, Smart Grids, Renewable Energy
Abstract: O crescimento na utilização de inversores vem sendo impulsionado pela geração distribuída de energia elétrica e pela eletrificação dos meios de transporte. Desta forma, muitos grupos de pesquisa est ̃ao desenvolvendo estratégias de controle para estes dispositivos. Porém, em muitos casos, a validação experimental não é feita por conta da dificuldade de se projetar e construir um inversor. E, quando um inversor experimental ́e utilizado, raramente são disponibilizadas as informações do projeto para que o inversor em si possa ser replicado. Assim, este trabalho busca disponibilizar um inversor full-bridge em projeto aberto de modo a propiciar que grupos de pesquisa tenham a possibilidade de aplicar suas estratégias desenvolvidas e obter resultados experimentais sem a necessidade de conceber um projeto do inversor.

Keywords: Resource Efficienty & Circular Economy Tracking, Industry Applications, Additive Manufaturing
Abstract: Os centros urbanos evoluem para novos patamares a partir da influência da tecnologia implementada na sociedade para melhor a qualidade de vida. Deste modo, a criação de regulamentos torna importante ferramenta para obter uma visão geral das cidades no investimento da sociedade em setores essenciais, como: energia, transporte, saúde, segurança, economia e outros. Sendo assim, cidades universitárias se tornam laboratórios vivos para observar os impactos das tecnologias na população e estimular a implementação de ações sustentáveis com o meio ambiente. A Cidade Universitária Professor José da Silveira Netto localizada em Belém é o objeto de estudo para verificar a sua evolução em nível de cidade inteligente utilizando a Norma Brasileira ABNT NBR ISO 37122:2020 que contém critérios internacionais sobre o assunto. A partir de gráficos de radar, as análises comparativas mostram evoluções relevantes devido a iniciativas da própria instituição e através dos laboratórios responsáveis pelos projetos de pesquisa. Portanto, o investimento em pesquisa e desenvolvimento na cidade universitária transporta a população para o futuro em relação à própria região metropolitana que a circunda.

Keywords: Industrial Ultrasound Theory and Application, Diagnosis, Prognosis and System Identification, Electrical Machines and Drives
Abstract: The development of an acquisition system that remotely captures echo signals to make three-dimensional ultrasound images of objects immersed in water is presented. The acquisition system is based on an STM32 microcontroller, which pulses a 500-kHz piezoceramic disc emitter, and so digitizes sixteen echo signals captured by two-dimensional array of sensors made of 1-3 piezocomposite. The digitized raw signals are transmitted to a personal computer (PC) via an Ethernet cable. The acquisition system was simplified by using the Power over Ethernet (PoE) technology, that integrates the power supply and data communication via the Ethernet cable itself. The beamforming is calculated on the PC, where the ultrasound images are displayed. Three-dimensional ultrasound images of objects immersed in water up to 1 meter away suggest that the proposed acquisition system can be improved for underwater purposes such as inspection of static underwater structures like bridges, pipeline occlusion and so on.

Keywords: Renewable Energy, Industry Applications
Abstract: Many countries worldwide have made efforts to decrease greenhouse gas emissions and to develop environmental, social and governance practices. Given its abundant natural resources, the industry in Brazil is expected to benefit from the growth in the renewable energy sector. This article aims to present the alternatives provided by the Brazilian electricity market to large consumers, and to analyze the viability and risks of Power Purchase Agreement (PPA) long-term contract and Self-Production by Own Investment (SPOI) project using solar photovoltaic (PV) source. In the PPA scenario, uncertainties are considered using Monte Carlo simulations in tandem with the Geometric Brownian Motion to manage risk. In the SPOI scenario, uncertainties in estimating costs of O&M, production, and short-term settlement prices of PV systems are considered. The two scenarios are evaluated for a wholesale electricity customer, providing parameters that can improve a company decision-making capability. It has been found that the most likely Net Present Value for the SPOI alternative gives a saving of 34.09% when compared to the PPA contract. Additionally, the observed Internal Rate of Return (IRR) for all scenarios demonstrated feasibility for investment in SPOI. Although the SPOI arrangement has shown advantages, it is important to assess the impact of investment expenditures (CAPEX) on the business.

Keywords: Industry Applications, Electrical Machines and Drives, Automation and Process Control
Abstract: The use of communication protocols and the choice of variables to be monitored allows the entire system to be in a safer environment, in which an operator has alarms, indicators and a representation of the entire system in real time, avoiding unnecessary exposure in the field, whether in the industrial field or in electrical power systems. In this context, this work intends to contribute to practical teaching in engineering, meeting the new curricular guidelines, with the development of a monitoring system for two didactic substations via Modbus protocol communicating with CLP's. The general supervisory intends to simulate a remote Operations Center, which is composed of two local SCADA supervisory systems that act as a gateway to the general system. These local systems are also responsible for acquiring the state of the breakers of the two didactic plants, through the inputs and outputs of the CLP's and distributing this information to the Operations Center remotely. For the general monitoring system, DNP Master drivers were used to acquire local information, as well as creating screens for monitoring and also integration to a SQL database so that events can be stored and analyzed by an operator present at the Monitoring Center Operations.

Keywords: Cutting & Packing
Abstract: En la fabricación de envases flexibles bilaminados se producen bobinas de polietileno a través de una serie de etapas interconectadas (i.e. extrusión, impresión, laminación y refilado). Dado que cada etapa tiene capacidades y limitaciones operativas diferentes, a través del proceso productivo puede resultar inevitable empalmar diferentes bobinas, técnica indeseable debido a las pérdidas de material y tiempo que supone. En el presente trabajo se presenta un modelo matemático del proceso de producción de envases flexibles que permite minimizar el número de empalmes requeridos. Al implementar el problema MINLP obtenido, el programa resultante permite el cálculo de algunas de las variables más influyentes del proceso, como son el número de lotes, la determinación de los largos de las bobinas y su elección de estas dentro de stock disponible. Se presentan los resultados de diferentes instancias del problema, para mostrar cómo ciertos factores seleccionados influyen en el número de empalmes totales. Se encontró que el número de empalmes de laminación disminuyen con el tamaño de los pedidos, suceso opuesto a lo sucedido con los empalmes de imprenta. Estos últimos se reducen al utilizar bobinas de stock de mayor tamaño.

Keywords: Industry Applications, Diagnosis, Prognosis and System Identification, Micro & Nano Manufacturing
Abstract: Today, composite materials are widely used in many industrial applications due to their advanced properties such as a higher strength-to-weight ratio. However, low-velocity impact failure in composites poses maintenance issues since it may result in unseen damage. This work provides a detailed overview of impact drop testing of composite laminate plates. The principal objective of this work is to comprehend the impact damage behaviour and failure mechanism in composite laminates. The paper also provides examining new techniques for making composite laminates and how these techniques might affect the impact performance of composite materials.

Keywords: Industry Applications, Automation and Process Control
Abstract: A distinguishing sensor is a formal mechanism that details the occurrence of certain events in a Discrete EventSystem (DES) according to the context they originate from, which aims to simplify design tasks. Sometimes, however, a distinction by a sensor may depend on another distinction, provided by another sensor, in a context dependency chain. In this case, the sensor itself becomes complex to be designed, affecting the entire control synthesis and the correct-by-construction controllers programming. This paper shows how multiple interdependent distinguishing sensors can be designed and integrated within the same DES scope. The approach is illustrated by a real process that corresponds to the dispatch flow of a poultry company. Two interdependent sensors are added to the shipping lines to automate the context-based separation of packaging. Such a solution would be unfeasible to be programmed manually, considering its chained combination of events.

Keywords: Robotics and Mechatronics, Autonomous Vehicles and Drones, Personalized Products
Abstract: Due to the ability to perform various maritime activities flexibly and reduce human life risks, Remotely Operated Underwater Vehicles (ROVs) are increasingly used in most offshore applications. The demand for more complex missions has increased the capabilities of ROVs in their operations. Because it is a robust and rigid system, this type of robot may not be effective in certain missions where monitoring in narrow and difficult-to-access places is required. The idea is to create a more flexible and compact three-degrees-of-freedom robot. This robot can help the offshore industry, marine biologists, and researchers in marine life investigation. The reason is that the prototype is more similar to a fish, which would avoid scaring the other specimens, thus not harming the environment. Therefore, this research project intends to develop a low-cost underwater robot modeling applied to an embedded system capable of monitoring information on the seafloor. The results are still preliminary, but they already indicate the possibility of inserting the system in a test environment closer to the real one.

Keywords: Robotics and Mechatronics
Abstract: Over time, individuals may face mobility issues in specific body parts, especially the lower limbs, due to accidents or other circumstances. However, the rapid evolution of technology has introduced robotic devices such as exoskeletons and virtual reality for patient rehabilitation. This article systematically reviews research on exoskeletons and virtual reality for lower limb motor rehabilitation. The objective is to create a comprehensive table of relevant information and enhance future researchers’ ability to communicate effectively on this topic. Using the Prisma methodology, 27 investigations were meticulously selected from multiple databases. The findings highlight diverse exoskeletons contributing to lower limb rehabilitation while recognizing areas requiring further improvements, such as virtual reality utilization.

Keywords: Life Support Systems & Techniques, Robotics and Mechatronics
Abstract: This study presents a novel and practical solution for physiotherapy by introducing a low-complexity prototype system that utilizes electronics and robotics to monitor and analyze upper-limb movements accurately. The system is designed to be applied in real-time physiotherapy sessions, aiding patients with mobility problems in their telerehabilitation process. The prototype system consists of three HMC5883L. Moreover, three M5 Stick C Plus devices are also used, each equipped with inertial measurement units (IMUs) and ESP32-PICO-D4 chips inside of them. These components are crucial in capturing and processing the upper-limb movement data. An ESP32 DevKitC-V4 is integrated into the setup to receive the data via Wi-Fi from the modules attached to the patient's body. By leveraging this hardware configuration, the prototype system can be capable of performing precise and instant readings of upper-limb movements during physiotherapy sessions. The real-time data acquisition allows therapists to monitor patients remotely and provide feedback, which is invaluable for optimizing telerehabilitation.

Keywords: Robotics and Mechatronics, Automation and Process Control, Autonomous Vehicles and Drones
Abstract: In this work the Generalized Predictive Control (GPC) is revisited in order to assess its capabilities in handling colored noise disturbances using a novel design procedure. The proposed method is investigated in a simulated case study of spacecraft emulation. Such emulation is proposed by combining a network-controlled quadcopter and a set of computer-based control algorithms that impose approximated spacecraft dynamics to the aerial system. The corresponding model was built upon real registered flight data. The contribution of this paper is twofold: first, we propose a novel GPC design in the colored noise case. Second, we assess the use of quadcopters to investigate spacecraft guidance and control algorithms. Simulation results confirmed the proposed methodology as a possible low-budget spacecraft-emulation alternative for a future experimental setup. One of the main findings of the current investigation is that no significant enhancements coming from the use of GPC in minimizing the chattering of the control signal under the colored noise disturbance case could be observed. An important discussion on this matter and possible solutions are presented for future investigations.

Keywords: Renewable Energy, Life Support Systems & Techniques, Industry Applications
Abstract: Créditos de carbono (CCR) foram criados em 1997, pelo Protocolo de Kyoto, como instrumento de compensação para mitigar eventuais limites à emissão de gases poluentes por ações antropogênicas. Este estudo avalia se este instrumento ainda é eficaz, identifica porque o mercado de CCR ainda não vigorou e, se há condições, passados 25 anos, de fazer uso deste instrumento de compensação para o combate ao aquecimento global visando a implantação de uma economia neutra em carbono no mundo e, em particular, no Brasil. Foram analisadas as propostas para o combate a poluição atmosférica e das propostas atuais para evitar o aquecimento global catastrófico sob o ponto de vista da economia. É avaliado o potencial atual de uso das fontes renováveis de energia como bens substitutos dos combustíveis fósseis. É discutida a possível contribuição de um mercado de CCR na aceleração da transição energética. Os resultados parciais apontam que, devido a sua excepcional condição geográfica, de sua vocação natural para desenvolver uma matriz energética não fóssil, e da grande área ocupada pelo bioma amazônico que é um sumidouro natural de carbono, o Brasil pode se beneficiar muito de uma polıtica mundial ”cap and trade” para limitar emissões de GEE.

Keywords: Smart Grids, Power and Eneergy Systems, Artificial Intelligence
Abstract: Neste estudo é elaborado um modelo de previsão de faltas climáticas na rede de distribuição de energia no estado do Espírito Santo, revelando regiões que tem mais possibilidades de serem afetadas. Para isso, serão utilizados dados históricos de falhas, previsão numérica do tempo, cobertura terrestre e infraestrutura da rede. Essas informações são combinadas em regiões com o sistema de geocódigo Geohash e por dia, servido assim de entrada para os modelos de aprendizado de máquina que tem como base diferentes técnicas, assim ajudando a garantir a eficiência e a confiabilidade do sistema de energia elétrica. Os resultados indicaram que a abordagem proposta apresentou uma precisão significativa na identificação da localização de falta, apresentando uma acurácia de 0.708 e com o F1 de 0.710.

Keywords: Internet of Things, Industry 4.0, Automation and Process Control
Abstract: The present work deals with the development of an embedded Internet of Things (IoT) system for monitoring the temperature of a photovoltaic system at different points, to enable the analysis of the efficiency of the solar system based on the thermal effect, considering the characteristics climate in the Amazon region. The module created was built and installed in a photovoltaic solar plant located at the Federal University of Pará. For the analyses, the regions of interest for monitoring the panels were considered, which are: the surface of the generator module in contact with the sun; the shaded area of the panel and the ambient temperature. Satisfactory results were obtained regarding the operation of the embedded system, which proved to be ideal for monitoring solar panels due to the ease of updating, communication, and data visualization.