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Related Concept Videos

Control Systems01:10

Control Systems

2.0K
Control systems are everywhere in contemporary society, influencing diverse applications from aerospace to automated manufacturing. These systems can be found naturally within biological processes, such as blood sugar regulation and heart rate adjustment in response to stress, as well as in man-made systems like elevators and automated vehicles. A control system is essentially a network of subsystems and processes that collaboratively convert specific inputs into desired outputs.
At the heart...
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Open and closed-loop control systems01:17

Open and closed-loop control systems

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Control systems are foundational elements in automation and engineering. They are broadly categorized into open-loop and closed-loop systems. These classifications hinge on the presence or absence of feedback mechanisms, significantly influencing the system's performance, complexity, and application.
An open-loop control system operates without feedback from the output. It consists of two primary elements: the controller and the controlled process. The controller receives an input signal...
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Introduction to Statistical Process Control01:15

Introduction to Statistical Process Control

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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...
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Feedback control systems01:26

Feedback control systems

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Feedback control systems are categorized in various ways based on their design, analysis, and signal types.
Linear feedback systems are theoretical models that simplify analysis and design. These systems operate under the principle that their output is directly proportional to their input within certain ranges. For instance, an amplifier in a control system behaves linearly as long as the input signal remains within a specific range. However, most physical systems exhibit inherent nonlinearity...
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Control Systems: Applications01:25

Control Systems: Applications

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Electrical engineering plays a pivotal role in our daily lives, with control systems at the heart of many applications, from home appliances to sophisticated space shuttles. Control systems manage and regulate the behavior of devices and processes, ensuring they function safely, correctly, and efficiently.
In modern vehicles, control systems manage various functions to enhance performance and safety. The steering wheel and accelerator are primary inputs in a car's control system. The...
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Methods for Controlling Microbial Growth01:29

Methods for Controlling Microbial Growth

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Microbial growth control refers to various methods employed to inhibit, reduce, or eliminate microorganisms to ensure safety and hygiene across different settings. These methods are categorized based on the target environment and the level of microbial control required.Biocides are versatile agents designed to control microorganisms by either inhibiting their growth or outright killing them. These agents work through various physical, chemical, mechanical, or biological mechanisms. The...
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Related Experiment Video

Updated: Mar 3, 2026

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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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

Published on: August 29, 2025

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Case Studies in Modelling, Control in Food Processes.

J Glassey1, A Barone2, G A Montague3

  • 1School of Chemical Engineering and Advanced Materials, Newcastle University, Newcastle upon Tyne, UK. jarka.glassey@ncl.ac.uk.

Advances in Biochemical Engineering/Biotechnology
|April 28, 2017
PubMed
Summary
This summary is machine-generated.

Advanced modeling and control strategies enhance food processing efficiency and product quality. Case studies on potato chips and NIR spectroscopy demonstrate significant economic and consistency benefits.

Keywords:
Bread and confectionery powder mixingFood process modelling and controlNIR spectroscopyPotato crisp/chips quality controlQuality control

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Area of Science:

  • Food Science and Technology
  • Process Engineering
  • Industrial Automation

Background:

  • Food processing faces unique challenges impacting efficiency and product quality.
  • Advanced modeling and control are crucial for optimizing food manufacturing.
  • Latest developments address these industry-specific hurdles.

Purpose of the Study:

  • To highlight the importance of modeling and control in food processing.
  • To discuss various approaches and recent advancements in the field.
  • To demonstrate practical benefits through industrial case studies.

Main Methods:

  • Knowledge elicitation from expert operators for process modeling.
  • Advanced process control focusing on critical parameters like moisture content.
  • Near-Infrared (NIR) spectroscopy for mixture analysis and quality assurance.

Main Results:

  • Improved process control leading to enhanced product consistency in potato chip manufacturing.
  • Economic advantages derived from tighter control over moisture content.
  • Effective validation of dry mixture and paste homogeneity using NIR spectroscopy.

Conclusions:

  • Implementing advanced measurement, modeling, and control significantly benefits food processes.
  • Practical implementation requires consideration of infrastructure and operational tips.
  • These strategies are key to increasing efficiency and ensuring high product quality in the food industry.