Industrial processes are procedures involving electric, electronic, chemical or mechanical methods to perform the manufacture of an item or items, generally on a large scale.

An industrial process is related to the scale or investment required. Production of specific materials may involve more than one type of process as components of heavy industry.

Industrial processes are nowadays directly interconnected with:

¤ Monitoring & Control
¤ Optimazion & Efficiency
¤ Maintenance
¤ IT Information Technology
¤ Energy
¤ Environment
¤ Training & Security


The present main challenges on industrial process are efficiency, energy and environment.






The Portal Process Section provide models of industrial process for the purpose of developing, studying and evaluating process & control technology, trends and R&D, technical information, descriptions of successful energy/efficiency programs, and links to other useful sites directories.

A broad range of processing plants, including those in the industry segments: chemicals; pulp & paper; petroleum, coal & natural gas; plastics; metals; food & beverage; non-metallic minerals; pharmaceuticals; detergents & cleaning compounds; rubber products; protective coatings; thermal utilities; textiles; select secondary manufacturers; process consultancies; plant construction firms; and labs & government institutions.

The portal is designed to keep users informed on the products, technology, events, applications, and news of industry emphasizing the subjects:

¤ Processing Equipment | Equipment trends for the processing industries.
¤ Measurement & Control | Technology and new products of this important instrumentation topic.
¤ Pumps & Fluid Handling | Installing or maintaining process systems.
¤ Environment | Environmental requirements & research
¤ Liquid, Gas & Air Handling | Equipment and instrumentation for liquid and gas handling systems.
¤ Gas Detection & Analysis | Measurement and control of gases process safety.
¤ Hazardous Environments | Requirements of hazardous locations.
¤ Process Control & Automation | Control technologies & the processing industries new levels of productivity.

These themes present methods well suited for a wide variety of studies including both plant-wide control and multivariable control problems, however within a main target for SME – Small and Medium Enterprises.




Control methods are used whenever some measure, such as temperature, pressure or speed, must be provided to perform in some desirable way over time.

Control methods applications make possible the use of electrical or electronic signals to control, and precision resulting more accurate than previously thought possible.

Control is a common concept, since there always are variables and quantities, which must be made to act in some desirable way over time.

In addition to the engineering systems, processes that can be studied by the automatic control methods control variables technological demands extremely challenging and widely varying control problems.





Engineering designs involves a large fraction of automatic control features. Frequently, control operations are implemented in an embedded microprocessor that watches signals from sensors and provides command signals to electromechanical actuators.

The use of computer-aided-design (CAD) software that embodies theoretical design algorithms allows exchange evaluation among various performance measures such as response speed, operating efficiency and sensitivity to uncertainties in the system model. The computer-based simulations are usually applied for testing proposed control designs, especially those for complex and expensive applications.

Control engineering experts operating the latest theoretical developments and meticulous understanding of application areas such as electronic, factory automation, robot dynamics, heating, ventilating and air conditioning set most control systems together.



Understanding the main ideas of control methodology is realizing that carefully observing an automatic control system, which implements in the controller a decision process, also called the control law, that dictates the appropriate control actions to be taken by systems to be maintained within acceptable tolerances.

These decisions are taken based on how different the actual measures are from the desired, called the error, and on the knowledge of the process increases and decreases. This knowledge is typically captured in a mathematical model. Information about the actual measure is fed back to the controller by sensors, and the control decisions are implemented via a device, the actuator, that increases or decreases the flow to the system.




The study of dynamical systems is the core in the control systems area. Control decisions are projected to be derived and accomplished over real time in the control of dynamical systems.

Feedback is a key concept involving the actual sensed values of system variables, sourced back and logic used to control the system. Feedback is used extensively to cope with incertitude about the system and its environment.

Information about the actual system behavior (closed-loop feedback control) establishes the control law decision process based not only on predictions about the plant behavior derived from the system model as in open-loop control.

Firm mathematical foundations establish the theory of control systems, from partial differential equations; topology, differential geometry and abstract algebra are used to study particularly complex phenomena. Including behavior of the system variables typically described by differential or difference equations in the time domains; by Laplace, Z and Fourier transforms in the transform (frequency) domain; there are recognized methods and mathematical theories to study stability and optimality.

The research Control System Theory also involves other areas, such as signal processing, Communications, Automation Engineering and KM – Knowledge Management.




The development of control methodologies to answer the new challenges will require original ideas and interdisciplinary approaches, in addition to additional developing and refining current methods.

The escalating technological requirements, efficiency, energy, impose requests for innovative, more accurate, less expensive and more efficient control solutions to present and further problems.

Characteristically the control complexity is more multifaceted, while less information are available about their dynamical behavior, and flexible structures, including control of emissions, industrial automation, airspace and underwater exploration, and control of communication networks.

The Control challenges requires the ability to address and solve new problems since it assumes sounding foundations in engineering and mathematics, uses extensively Simulation computer software and hardware and in a multiplicity of disciplines, from aeronautical to electronics and petrochemical engineering.





Advances in computer science, and engineering, are influencing developments in control increasing availability of vast computing power, and the Simulation development.

The Control systems are mainly decision-making systems where the decisions are based on potential behavior forecast derived through models of the controlled systems, and on sensor-obtained observations of the actual behavior that are sourced back. The Control decisions are converted into control actions using control actuators.

The control methodology is induced by developments in sensor and actuator technology.
Planning and expert systems are decision processes serving purposes similar to control systems and direct naturally interdisciplinary research and intelligent control methods.

Operations Research disciplines represents significant interest in understanding and controlling manufacturing processes, leading to interdisciplinary research to study the control of discrete-event systems, which cannot be expressed by habitual differential or difference equations; and to the study of hybrid control systems that deal with the control of systems with continuous dynamics by sequential machines.

Other examples of methodologies control that engineers are examining to address the control of very complex systems are Fuzzy control logic and neural networks.





New control systems are able to cope and maintain acceptable performance levels under significant unexpected incertitude and failures, systems that demonstrate considerable grades of autonomy.

Highly automated manufacturing; intelligent robots; highly efficient and fault tolerant networks; reliable electric power generation and distribution; and highly efficient control for a cleaner environment are integrated concentration of essential features in the area of controls that are increasing complex control solutions.

Mainly availability of new software's tools creating predictive models of product properties, production and process events, and models used as virtual sensors, property predictors, and a model-based for industrial process optimization.


Seções Principais Domínios Pesquisa Industrial Tecnologias Projetos Materiais Informações