Process Control
Process Control - Related Videos
01:15
Introduction to Statistical Process Control
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2025
Statistical Process Control (SPC) is a method used to monitor and control quality within processes, particularly in manufacturing and service delivery, by employing statistical methods. SPC aims to distinguish between natural (common cause) variation and variation due to specific changes or events (special cause), allowing for timely improvements and sustained quality. The control chart, a pivotal tool in SPC, visually displays data over time alongside a central line of upper and lower control...
09:37
Measurement of Neurophysiological Signals of Ignoring and Attending Processes in Attention Control
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Cited by 5 •
2015
Attention control comprises enhancement of target signals and attenuation of distractor signals. We describe an approach to measure separately but concurrently, the neurophysiology of attending and ignoring in sustained intermodal attention, utilizing a passive control condition during which neither process is continuously engaged.
05:47
Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control
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Cited by 1 •
2025
Here, we present a protocol for the simulation and monitoring of a scaled semi-automated assembly process, through the collaboration of a collaborative robot and verification via a computer vision system for quality control.
07:40
A Gusseted Thermogradient Table to Control Soil Temperatures for Evaluating Plant Growth and Monitoring Soil Processes
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Cited by 5 •
2016
Traditional thermogradient tables create a range of temperatures across the surface. Welding gussets perpendicular to the surface of a thermogradient table will control temperature in depth increasing possible research applications.
06:43
Standardized Processing for Formalin-Fixed, Paraffin-Embedded Cell Pellet Immunohistochemistry Controls
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Cited by 3 •
2022
Presented here is a protocol for generating formalin-fixed, paraffin-embedded cell pellet controls for immunohistochemistry.
FAQs
A feedback loop continuously compares a measured process variable with its desired setpoint. The controller evaluates the difference between them and directs a corrective action through an actuator. This repeated measurement, comparison, and adjustment helps limit deviations in variables such as temperature, pressure, flow, or level, allowing the process to operate more consistently.
Feedback control responds to a measured deviation after the process variable differs from its setpoint. Feedforward control can be combined with feedback in modern systems to support corrective action as part of computerized process management. Using both approaches helps engineers regulate complex operations while improving precision, consistency, and the ability to manage changing process conditions.
These components perform complementary functions. Sensors provide measurements of variables such as temperature, pressure, flow, or level. Controllers compare those measurements with desired values and determine corrective actions, while actuators apply those actions to the process. Together, they create the measurement and adjustment pathway required for safe, efficient, and consistent operation.
Engineers first monitor relevant process variables with sensors, establish desired setpoints, and use controllers to compare actual conditions with those targets. The control system then sends corrective instructions to actuators, while computerized monitoring can help coordinate complex operations. Repeating this sequence enables continuous regulation and supports reliable process performance rather than one-time adjustment.
The approach is applied across chemical plants, manufacturing systems, energy facilities, and environmental operations. In each setting, engineers select process variables that require regulation and use control systems to support stable operation. Its broad use reflects the need to maintain consistent conditions across different industrial environments, even when the monitored variables and operating objectives differ.
Effective regulation can help maintain product quality, reduce waste, improve energy efficiency, and prevent hazardous deviations. These outcomes connect control decisions with both production and safety goals. In environmental operations, the same approach supports consistent management of process conditions, while energy facilities can use it to improve the efficiency and reliability of their operations.