Utilizing multiple linear regression technique for interential measure of continuous-based process monitoring

Muhammad Ridzuan, Mamat (2013) Utilizing multiple linear regression technique for interential measure of continuous-based process monitoring. Faculty of Chemical & Natural Resources Engineering, Universiti Malaysia Pahang.

[img]
Preview
PDF
(CD8351) MUHAMMAD RIDZUAN BIN MAMAT.pdf

Download (953kB) | Preview

Abstract

The present conventional MSPC has several weaknesses in process fault detection and diagnosis. Some researchers in this filed had commented that the MSPC is a powerful tool for data complexity reduction and fault detection in the significant fault appearance data. The current fault detection and diagnosis method via MSPC is limited to significant faults and does not point put the insignificant ones accurately. In the real time, all variable will be used in monitoring. However in this case only a few of them are truly important. By developed modeling based on multiple linear regressions the relationship between these variables can be figure out. Multiple linear regressions (MLR) is a method used to model the linear relationship between a dependent variable and one or more independent variables. Some assumption should be made in order to obtain an accurate data analysis. The assumptions are variables should normally distribute, a linear relationship between the independent and dependent variables must exist and also the variable should be measure without an error. MLR is probably the most widely used in dendroclimatology for developing models to reconstruct climate variables. Besides they also proposed for control charting methods for lumber manufacturing and profile monitoring applied in public health surveillance. The methods to perform this modeling involve two phases which are Phase I: offline modeling and monitoring and Phase II: online monitoring. As a conclusion, the MLR method is success introduced as a significant improvement compared to the conventional method. On top of those objectives, the original goals of SPC are also been considered as well as carried together, such a way that the productivity of multivariate process monitoring is improved

Item Type: Undergraduates Project Papers
Additional Information: Project paper (Bachelor of Chemical Engineering) -- Universiti Malaysia Pahang - 2013
Uncontrolled Keywords: Chemical engineering Mathematical models
Subjects: T Technology > TP Chemical technology
Faculty/Division: Faculty of Chemical & Natural Resources Engineering
Depositing User: Mr. Syed Mohd Faiz Syed Abdul Aziz
Date Deposited: 15 Oct 2015 06:14
Last Modified: 06 Jul 2021 07:14
URI: http://umpir.ump.edu.my/id/eprint/10793
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item