Process control in the context of "Analog computer"

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⭐ Core Definition: Process control

Industrial process control (IPC) or simply process control is a system used in modern manufacturing which uses the principles of control theory and physical industrial control systems to monitor, control and optimize continuous industrial production processes using control algorithms. This ensures that the industrial machines run smoothly and safely in factories and efficiently use energy to transform raw materials into high-quality finished products with reliable consistency while reducing energy waste and economic costs, something which could not be achieved purely by human manual control.

In IPC, control theory provides the theoretical framework to understand system dynamics, predict outcomes and design control strategies to ensure predetermined objectives, utilizing concepts like feedback loops, stability analysis and controller design. On the other hand, the physical apparatus of IPC, based on automation technologies, consists of several components. Firstly, a network of sensors continuously measure various process variables (such as temperature, pressure, etc.) and product quality variables. A programmable logic controller (PLC, for smaller, less complex processes) or a distributed control system (DCS, for large-scale or geographically dispersed processes) analyzes this sensor data transmitted to it, compares it to predefined setpoints using a set of instructions or a mathematical model called the control algorithm and then, in case of any deviation from these setpoints (e.g., temperature exceeding setpoint), makes quick corrective adjustments through actuators such as valves (e.g. cooling valve for temperature control), motors or heaters to guide the process back to the desired operational range. This creates a continuous closed-loop cycle of measurement, comparison, control action, and re-evaluation which guarantees that the process remains within established parameters. The HMI (Human-Machine Interface) acts as the "control panel" for the IPC system where small number of human operators can monitor the process and make informed decisions regarding adjustments. IPCs can range from controlling the temperature and level of a single process vessel (controlled environment tank for mixing, separating, reacting, or storing materials in industrial processes.) to a complete chemical processing plant with several thousand control feedback loops.

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👉 Process control in the context of Analog computer

An analog computer or analogue computer is a type of computation machine (computer) that uses physical phenomena such as electrical, mechanical, or hydraulic quantities behaving according to the mathematical principles in question (analog signals) to model the problem being solved. In contrast, digital computers represent varying quantities symbolically and by discrete values of both time and amplitude (digital signals).

Analog computers can have a very wide range of complexity. Slide rules and nomograms are the simplest, while naval gunfire control computers and large hybrid digital/analog computers were among the most complicated. Complex mechanisms for process control and protective relays used analog computation to perform control and protective functions. The common property of all of them is that they don't use algorithms to determine the fashion of how the computer works. They rather use a structure analogous to the system to be solved (a so called analogon, model or analogy) which is also eponymous to the term analog computer, because they represent a model.

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Process control in the context of Root cause analysis

In science and reliability engineering, root-cause analysis (RCA) is a method of problem solving used for identifying the root causes of faults or problems. It is widely used in IT operations, manufacturing, telecommunications, industrial process control, accident analysis (e.g., in aviation, rail transport, or nuclear plants), medical diagnosis, the healthcare industry (e.g., for epidemiology). Root-cause analysis is a form of inductive inference (first create a theory, or root, based on empirical evidence, or causes) and deductive inference (test the theory, i.e., the underlying causal mechanisms, with empirical data).

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Process control in the context of Velocimetry

Velocimetry is the measurement of the velocity of fluids. This is a task often taken for granted, and involves far more complex processes than one might expect. It is often used to solve fluid dynamics problems, study fluid networks, in industrial and process control applications, as well as in the creation of new kinds of fluid flow sensors. Methods of velocimetry include particle image velocimetry and particle tracking velocimetry, Molecular tagging velocimetry, laser-based interferometry, ultrasonic Doppler methods, Doppler sensors, and new signal processing methodologies.

In general, velocity measurements are made in the Lagrangian or Eulerian frames of reference (see Lagrangian and Eulerian coordinates). Lagrangian methods assign a velocity to a volume of fluid at a given time, whereas Eulerian methods assign a velocity to a volume of the measurement domain at a given time. A classic example of the distinction is particle tracking velocimetry, where the idea is to find the velocity of individual flow tracer particles (Lagrangian) and particle image velocimetry, where the objective is to find the average velocity within a sub-region of the field of view (Eulerian).

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Process control in the context of IBM System/360 Model 44

The IBM System/360 Model 44 is a specialized member of the IBM System/360 family, with a variant of the System/360 computer architecture, designed for scientific computing, real-time computing, process control and numerical control (NC).

The Model 44 was announced August 16, 1965 and withdrawn September 24, 1973.

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