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Integration of multivariate statistical process control and engineering process control: a novel framework
by
Siddiqui, Yasir A.
, Rahim, Abdur
, Elshafei, Moustafa
, Saif, Abdul-Wahid A.
, Cheded, Lahouari
in
Air conditioners
/ Air conditioning
/ CAE) and Design
/ Computer-Aided Engineering (CAD
/ Control charts
/ Control systems
/ Engineering
/ Fault detection
/ Feedback control
/ Industrial and Production Engineering
/ Mechanical Engineering
/ Media Management
/ Multivariate analysis
/ Original Article
/ Process controls
/ Statistical process control
/ Ventilation
2015
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Integration of multivariate statistical process control and engineering process control: a novel framework
by
Siddiqui, Yasir A.
, Rahim, Abdur
, Elshafei, Moustafa
, Saif, Abdul-Wahid A.
, Cheded, Lahouari
in
Air conditioners
/ Air conditioning
/ CAE) and Design
/ Computer-Aided Engineering (CAD
/ Control charts
/ Control systems
/ Engineering
/ Fault detection
/ Feedback control
/ Industrial and Production Engineering
/ Mechanical Engineering
/ Media Management
/ Multivariate analysis
/ Original Article
/ Process controls
/ Statistical process control
/ Ventilation
2015
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Integration of multivariate statistical process control and engineering process control: a novel framework
by
Siddiqui, Yasir A.
, Rahim, Abdur
, Elshafei, Moustafa
, Saif, Abdul-Wahid A.
, Cheded, Lahouari
in
Air conditioners
/ Air conditioning
/ CAE) and Design
/ Computer-Aided Engineering (CAD
/ Control charts
/ Control systems
/ Engineering
/ Fault detection
/ Feedback control
/ Industrial and Production Engineering
/ Mechanical Engineering
/ Media Management
/ Multivariate analysis
/ Original Article
/ Process controls
/ Statistical process control
/ Ventilation
2015
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Integration of multivariate statistical process control and engineering process control: a novel framework
Journal Article
Integration of multivariate statistical process control and engineering process control: a novel framework
2015
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Overview
Statistical process control is being used along with classical feedback control systems (which are also termed as Engineering Process Control, EPC) for the purposes of detecting faults and avoiding over adjustment of the processes. This paper evaluates the effectiveness of integrating SPC with EPC for both fault detection and control. A novel framework for fault detection using Multivariate Statistical Process Control (MSPC) is proposed here and illustrated with a case study. The simultaneous application of MSPC control charts to process inputs and outputs or in other words “joint monitoring” of process inputs and outputs is shown here to provide efficient fault detection capabilities. An example of Heating Ventilation and Air Conditioning (HVAC) systems is simulated here and used as a case study to demonstrate the detection capabilities of the proposed framework. Moreover, the capabilities of the proposed framework were enhanced by inclusion of a corrective action scheme, thus leading to a complete control system with fault detection and correction.
Publisher
Springer London,Springer Nature B.V
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