53 resultados para Minerais industriais


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Due of industrial informatics several attempts have been done to develop notations and semantics, which are used for classifying and describing different kind of system behavior, particularly in the modeling phase. Such attempts provide the infrastructure to resolve some real problems of engineering and construct practical systems that aim at, mainly, to increase the productivity, quality, and security of the process. Despite the many studies that have attempted to develop friendly methods for industrial controller programming, they are still programmed by conventional trial-and-error methods and, in practice, there is little written documentation on these systems. The ideal solution would be to use a computational environment that allows industrial engineers to implement the system using high-level language and that follows international standards. Accordingly, this work proposes a methodology for plant and control modelling of the discrete event systems that include sequential, parallel and timed operations, using a formalism based on Statecharts, denominated Basic Statechart (BSC). The methodology also permits automatic procedures to validate and implement these systems. To validate our methodology, we presented two case studies with typical examples of the manufacturing sector. The first example shows a sequential control for a tagged machine, which is used to illustrated dependences between the devices of the plant. In the second example, we discuss more than one strategy for controlling a manufacturing cell. The model with no control has 72 states (distinct configurations) and, the model with sequential control generated 20 different states, but they only act in 8 distinct configurations. The model with parallel control generated 210 different states, but these 210 configurations act only in 26 distinct configurations, therefore, one strategy control less restrictive than previous. Lastly, we presented one example for highlight the modular characteristic of our methodology, which it is very important to maintenance of applications. In this example, the sensors for identifying pieces in the plant were removed. So, changes in the control model are needed to transmit the information of the input buffer sensor to the others positions of the cell

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Due to the current need of the industry to integrate data of the beginning of production originating from of several sources and of transforming them in useful information for sockets of decisions, a search exists every time larger for systems of visualization of information that come to collaborate with that functionality. On the other hand, a common practice nowadays, due to the high competitiveness of the market, it is the development of industrial systems that possess characteristics of modularity, distribution, flexibility, scalability, adaptation, interoperability, reusability and access through web. Those characteristics provide an extra agility and a larger easiness in adapting to the frequent changes of demand of the market. Based on the arguments exposed above, this work consists of specifying a component-based architecture, with the respective development of a system based on that architecture, for the visualization of industrial data. The system was conceived to be capable to supply on-line information and, optionally, historical information of variables originating from of the beginning of production. In this work it is shown that the component-based architecture developed possesses the necessary requirements for the obtaining of a system robust, reliable and of easy maintenance, being, like this, in agreement with the industrial needs. The use of that architecture allows although components can be added, removed or updated in time of execution, through a manager of components through web, still activating more the adaptation process and updating of the system

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Ensuring the dependability requirements is essential for the industrial applications since faults may cause failures whose consequences result in economic losses, environmental damage or hurting people. Therefore, faced from the relevance of topic, this thesis proposes a methodology for the dependability evaluation of industrial wireless networks (WirelessHART, ISA100.11a, WIA-PA) on early design phase. However, the proposal can be easily adapted to maintenance and expansion stages of network. The proposal uses graph theory and fault tree formalism to create automatically an analytical model from a given wireless industrial network topology, where the dependability can be evaluated. The evaluation metrics supported are the reliability, availability, MTTF (mean time to failure), importance measures of devices, redundancy aspects and common cause failures. It must be emphasized that the proposal is independent of any tool to evaluate quantitatively the target metrics. However, due to validation issues it was used a tool widely accepted on academy for this purpose (SHARPE). In addition, an algorithm to generate the minimal cut sets, originally applied on graph theory, was adapted to fault tree formalism to guarantee the scalability of methodology in wireless industrial network environments (< 100 devices). Finally, the proposed methodology was validate from typical scenarios found in industrial environments, as star, line, cluster and mesh topologies. It was also evaluated scenarios with common cause failures and best practices to guide the design of an industrial wireless network. For guarantee scalability requirements, it was analyzed the performance of methodology in different scenarios where the results shown the applicability of proposal for networks typically found in industrial environments

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This work proposes the specification of a new function block according to Foundation Fieldbus standards. The new block implements an artificial neural network, which may be useful in process control applications. The specification includes the definition of a main algorithm, that implements a neural network, as well as the description of some accessory functions, which provide safety characteristics to the block operation. Besides, it also describes the block attributes emphasizing its parameters, which constitute the block interfaces. Some experimental results, obtained from an artificial neural network implementation using actual standard functional blocks on a laboratorial FF network, are also shown, in order to demonstrate the possibility and also the convenience of integrating a neural network to Fieldbus devices

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This work presents a packet manipulation tool developed to realize tests in industrial devices that implements TCP/IP-based communication protocols. The tool was developed in Python programming language, as a Scapy extension. This tool, named IndPM- Industrial Packet Manipulator, can realize vulnerability tests in devices of industrial networks, industrial protocol compliance tests, receive server replies and utilize the Python interpreter to build tests. The Modbus/TCP protocol was implemented as proof-of-concept. The DNP3 over TCP protocol was also implemented but tests could not be realized because of the lack of resources. The IndPM results with Modbus/TCP protocol show some implementation faults in a Programmable Logic Controller communication module frequently utilized in automation companies

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This paper describes the design, implementation and enforcement of a system for industrial process control based on fuzzy logic and developed using Java, with support for industrial communication protocol through the OPC (Ole for Process Control). Besides the java framework, the software is completely independent from other platforms. It provides friendly and functional tools for modeling, construction and editing of complex fuzzy inference systems, and uses these logical systems in control of a wide variety of industrial processes. The main requirements of the developed system should be flexibility, robustness, reliability and ease of expansion

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The evolution of automation in recent years made possible the continuous monitoring of the processes of industrial plants. With this advance, the amount of information that automation systems are subjected to increased significantly. The alarms generated by the monitoring equipment are a major contributor to this increase, and the equipments are usually deployed in industrial plants without a formal methodology, which entails an increase in the number of alarms generated, thus overloading the alarm system and therefore the operators of such plants. In this context, the works of alarm management comes up with the objective of defining a formal methodology for installation of new equipment and detect problems in existing settings. This thesis aims to propose a set of metrics for the evaluation of alarm systems already deployed, so that you can identify the health of this system by analyzing the proposed indices and comparing them with parameters defined in the technical norms of alarm management. In addition, the metrics will track the work of alarm management, verifying if it is improving the quality of the alarm system. To validate the proposed metrics, data from actual process plants of the petrochemical industry were used

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The present work has as objective to present a method of project and implementation of controllers PID, based on industrial instrumentation. An automatic system of auto-tunning of controllers PID will be presented, for systems of first and second order. The software presented in this work is applied in controlled plants by PID controllers implemented in a CLP. Software is applied to make the auto-tunning of the parameters of controller PID of plants that need this tunning. Software presents two stages, the first one is the stage of identification of the system using the least square recursive algorithm and the second is the stage of project of the parameters of controller PID using the root locus algorithm. An important fact of this work is the use of industrial instrumentation for the accomplishment of the experiments. The experiments had been carried through in controlled real plants for controllers PID implemented in the CLP. Thus has not only one resulted obtained with theoreticians experiments made with computational programs, and yes resulted obtained of real systems. The experiments had shown good results gotten with developed software

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Industrial automation networks is in focus and is gradually replacing older architectures of systems used in automation world. Among existing automation networks, most prominent standard is the Foundation Fieldbus (FF). This particular standard was chosen for the development of this work thanks to its complete application layer specification and its user interface, organized as function blocks and that allows interoperability among different vendors' devices. Nowadays, one of most seeked solutions on industrial automation are the indirect measurements, that consist in infering a value from measures of other sensors. This can be made through implementation of the so-called software sensors. One of the most used tools in this project and in sensor implementation are artificial neural networks. The absence of a standard solution to implement neural networks in FF environment makes impossible the development of a field-indirect-measurement project, besides other projects involving neural networks, unless a closed proprietary solution is used, which dos not guarantee interoperability among network devices, specially if those are from different vendors. In order to keep the interoperability, this work's goal is develop a solution that implements artificial neural networks in Foundation Fieldbus industrial network environment, based on standard function blocks. Along the work, some results of the solution's implementation are also presented

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The main objective of work is to show procedures to implement intelligent control strategies. This strategies are based on fuzzy scheduling of PID controllers, by using only standard function blocks of this technology. Then, the standardization of Foundation Fieldbus is kept. It was developed an environment to do the necessary tests, it validates the propose. This environment is hybrid, it has a real module (the fieldbus) and a simulated module (the process), although the control signals and measurement are real. Then, it is possible to develop controllers projects. In this work, a fuzzy supervisor was developed to schedule a network of PID controller for a non-linear plant. Analyzing its performance results to the control and regulation problem

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The structure of Industrial Automation bases on a hierarchical pyramid, where restricted information islands are created. Those information islands are characterized by systems where hardware and software used are proprietors. In other words, they are supplied for just a manufacturer, doing with that customer is entailed to that supplier. That solution causes great damages to companies. Once the connection and integration with other equipments, that are not of own supplier, it is very complicated. Several times it is impossible of being accomplished, because of high cost of solution or for technical incompatibility. This work consists to specify and to implement the visualization module via Web of GERINF. GERINF is a FINEP/CTPetro project that has the objective of developing a software for information management in industrial processes. GERINF is divided in three modules: visualization via Web, compress and storage and communication module. Are presented results of the utilization of a proposed system to information management of a Natural Gas collected Unit of Guamar´e on the PETROBRAS UN-RNCE.

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The using of supervision systems has become more and more essential in accessing, managing and obtaining data of industrial processes, because of constant and frequent developments in industrial automation. These supervisory systems (SCADA) have been widely used in many industrial environments to store process data and to control the processes in accordance with some adopted strategy. The SCADA s control hardware is the set of equipments that execute this work. The SCADA s supervision software accesses process data through the control hardware and shows them to the users. Currently, many industrial systems adopt supervision softwares developed by the same manufacturer of the control hardware. Usually, these softwares cannot be used with other equipments made by distinct manufacturers. This work proposes an approach for developing supervisory systems able to access process information through different control hardwares. An architecture for supervisory systems is first defined, in order to guarantee efficiency in communication and data exchange. Then, the architecture is applied in a supervisory system to monitor oil wells that use distinct control hardwares. The implementation was modeled and verified by using the formal method of the Petri networks. Finally, experimental results are presented to demonstrate the applicability of the proposed solution

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Operating industrial processes is becoming more complex each day, and one of the factors that contribute to this growth in complexity is the integration of new technologies and smart solutions employed in the industry, such as the decision support systems. In this regard, this dissertation aims to develop a decision support system based on an computational tool called expert system. The main goal is to turn operation more reliable and secure while maximizing the amount of relevant information to each situation by using an expert system based on rules designed for a particular area of expertise. For the modeling of such rules has been proposed a high-level environment, which allows the creation and manipulation of rules in an easier way through visual programming. Despite its wide range of possible applications, this dissertation focuses only in the context of real-time filtering of alarms during the operation, properly validated in a case study based on a real scenario occurred in an industrial plant of an oil and gas refinery

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The control of industrial processes has become increasingly complex due to variety of factory devices, quality requirement and market competition. Such complexity requires a large amount of data to be treated by the three levels of process control: field devices, control systems and management softwares. To use data effectively in each one of these levels is extremely important to industry. Many of today s industrial computer systems consist of distributed software systems written in a wide variety of programming languages and developed for specific platforms, so, even more companies apply a significant investment to maintain or even re-write their systems for different platforms. Furthermore, it is rare that a software system works in complete isolation. In industrial automation is common that, software had to interact with other systems on different machines and even written in different languages. Thus, interoperability is not just a long-term challenge, but also a current context requirement of industrial software production. This work aims to propose a middleware solution for communication over web service and presents an user case applying the solution developed to an integrated system for industrial data capture , allowing such data to be available simplified and platformindependent across the network

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There is a growing need to develop new tools to help end users in tasks related to the design, monitoring, maintenance and commissioning of critical infrastructures. The complexity of the industrial environment, for example, requires that these tools have flexible features in order to provide valuable data for the designers at the design phases. Furthermore, it is known that industrial processes have stringent requirements for dependability, since failures can cause economic losses, environmental damages and danger to people. The lack of tools that enable the evaluation of faults in critical infrastructures could mitigate these problems. Accordingly, the said work presents developing a framework for analyzing of dependability for critical infrastructures. The proposal allows the modeling of critical infrastructure, mapping its components to a Fault Tree. Then the mathematical model generated is used for dependability analysis of infrastructure, relying on the equipment and its interconnections failures. Finally, typical scenarios of industrial environments are used to validate the proposal