Process monitoring on AFPT pilot plant by using statistical process control

Statistical Process Control (SPC) technique has been widely develops for fault detection, diagnosis and control tool. Today, the industries have to keep sustainable production and operate as fault free as possible because faults that present in a process operation increase the operating cost due to...

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Main Author: Mohamed Afizal, Mohamed Amin
Format: Undergraduates Project Papers
Language:English
Published: 2009
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Online Access:http://umpir.ump.edu.my/id/eprint/835/1/Mohamed_Afizal_Mohamed_Amin.pdf
http://umpir.ump.edu.my/id/eprint/835/
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spelling my.ump.umpir.8352021-06-16T07:41:04Z http://umpir.ump.edu.my/id/eprint/835/ Process monitoring on AFPT pilot plant by using statistical process control Mohamed Afizal, Mohamed Amin TP Chemical technology Statistical Process Control (SPC) technique has been widely develops for fault detection, diagnosis and control tool. Today, the industries have to keep sustainable production and operate as fault free as possible because faults that present in a process operation increase the operating cost due to products with undesired specifications, malfunction of plant equipment and instrumentation. Therefore, this study is conducted to introduce Statistical Process Control method for detecting fault early enough, so that the corrective action can be taken before the process is upset or out of control. For this research, the historical data at normal operating condition is collected by using Air Flow Pressure Temperature (AFPT) Pilot Plant. The generate data then will be ensure distribute normally before further analysis is carried out. Shewhart individual chart and Shewhart range chart are use to facilitate the fault detected. Based on the result, the Shewhart individual capabilities is more precise estimate of the process standard deviation compare to Shewhart range because it has a smaller uncertainty. Besides that, the computation of Shewhart individual involves all the measurements in each sample, while the computation of Shewhart range involves only two measurements (the largest and the smallest). Based on the result obtained, it shows that both Shewhart range and Shewhart individual chart, can detect fault for both process variables (Temperature and Pressure) and quality variables (Density). After the correlation coefficient is determined it show that the gap between UCL and LCL with CL become wider and make the usage of this technique in Shewhart chart for fault detection gives the best for it has the highest fault detection efficiency.-Author- 2009-05 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/835/1/Mohamed_Afizal_Mohamed_Amin.pdf Mohamed Afizal, Mohamed Amin (2009) Process monitoring on AFPT pilot plant by using statistical process control. Faculty of Chemical & Natural Resources Engineering, Universiti Malaysia Pahang.
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
Mohamed Afizal, Mohamed Amin
Process monitoring on AFPT pilot plant by using statistical process control
description Statistical Process Control (SPC) technique has been widely develops for fault detection, diagnosis and control tool. Today, the industries have to keep sustainable production and operate as fault free as possible because faults that present in a process operation increase the operating cost due to products with undesired specifications, malfunction of plant equipment and instrumentation. Therefore, this study is conducted to introduce Statistical Process Control method for detecting fault early enough, so that the corrective action can be taken before the process is upset or out of control. For this research, the historical data at normal operating condition is collected by using Air Flow Pressure Temperature (AFPT) Pilot Plant. The generate data then will be ensure distribute normally before further analysis is carried out. Shewhart individual chart and Shewhart range chart are use to facilitate the fault detected. Based on the result, the Shewhart individual capabilities is more precise estimate of the process standard deviation compare to Shewhart range because it has a smaller uncertainty. Besides that, the computation of Shewhart individual involves all the measurements in each sample, while the computation of Shewhart range involves only two measurements (the largest and the smallest). Based on the result obtained, it shows that both Shewhart range and Shewhart individual chart, can detect fault for both process variables (Temperature and Pressure) and quality variables (Density). After the correlation coefficient is determined it show that the gap between UCL and LCL with CL become wider and make the usage of this technique in Shewhart chart for fault detection gives the best for it has the highest fault detection efficiency.-Author-
format Undergraduates Project Papers
author Mohamed Afizal, Mohamed Amin
author_facet Mohamed Afizal, Mohamed Amin
author_sort Mohamed Afizal, Mohamed Amin
title Process monitoring on AFPT pilot plant by using statistical process control
title_short Process monitoring on AFPT pilot plant by using statistical process control
title_full Process monitoring on AFPT pilot plant by using statistical process control
title_fullStr Process monitoring on AFPT pilot plant by using statistical process control
title_full_unstemmed Process monitoring on AFPT pilot plant by using statistical process control
title_sort process monitoring on afpt pilot plant by using statistical process control
publishDate 2009
url http://umpir.ump.edu.my/id/eprint/835/1/Mohamed_Afizal_Mohamed_Amin.pdf
http://umpir.ump.edu.my/id/eprint/835/
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score 13.160551