Title :
Online monitoring for multiple mode processes based on Gaussian Mixture Model
Author :
Tan Shuai ; Chang Yuqing ; Wang Fuli ; Peng Jun ; Wang Shu
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeast Univ., Shenyang, China
fDate :
May 31 2014-June 2 2014
Abstract :
Recently, with the urgent requirement of multi-type and high-quality products of the market, the efficient production process of multiple products become emphasis in many industries. It is challenging to conduct statistical analysis and online monitoring for multi-mode processes considering the process high dimensionality and multi-operation. In this paper, process monitoring model for different modes are built using Gaussian Mixture Model, especially focusing on several key points, such as, data classification, excluding noise, mode identification for online monitoring and so on. A large number of simulations in real process show the feasibility and effectiveness of the proposed method.
Keywords :
Gaussian processes; process monitoring; production management; statistical analysis; Gaussian mixture model; data classification; high-quality products; mode identification; multiple mode processes; multiple product; multitype products; online monitoring; process monitoring model; production process; statistical analysis; Data models; Furnaces; Gaussian mixture model; Monitoring; Production; Temperature; Continuous Annealing Line; Mode Identification; Multiple Mode Processes; Online Monitoring;
Conference_Titel :
Control and Decision Conference (2014 CCDC), The 26th Chinese
Conference_Location :
Changsha
Print_ISBN :
978-1-4799-3707-3
DOI :
10.1109/CCDC.2014.6852838