Optimal online soft sensor for product quality monitoring in propylene polymerization process

2015 ◽  
Vol 149 ◽  
pp. 1216-1224 ◽  
Author(s):  
Zhong Cheng ◽  
Xinggao Liu
Keyword(s):  
Product Quality ◽  
Soft Sensor ◽  
Quality Monitoring ◽  
Propylene Polymerization ◽  
Polymerization Process

Moving average PLS soft sensor for online product quality estimation in an industrial batch polymerization process

2009 ◽  
Vol 19 (3) ◽  
pp. 520-529 ◽  
Author(s):  
Pierantonio Facco ◽  
Franco Doplicher ◽  
Fabrizio Bezzo ◽  
Massimiliano Barolo
Keyword(s):  
Product Quality ◽  
Moving Average ◽  
Soft Sensor ◽  
Polymerization Process ◽  
Quality Estimation ◽  
Industrial Batch

scholarly journals Soft Sensor Development Based on Quality-Relevant Slow Feature Analysis and Bayesian Regression with Application to Propylene Polymerization

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Miao Zhang ◽  
Le Zhou ◽  
Jing Jie ◽  
Xiaoli Wu
Keyword(s):  
Soft Sensor ◽  
Bayesian Regression ◽  
Propylene Polymerization ◽  
Polymerization Process ◽  
Feature Analysis ◽  
Quality Indices ◽  
Soft Sensors ◽  
Slow Feature Analysis ◽  
Iterative Maximum Likelihood

Data-driven soft sensors are widely used to predict quality indices in propylene polymerization processes to improve the availability of measurements and efficiency. To deal with the nonlinearity and dynamics in propylene polymerization processes, a novel soft sensor based on quality-relevant slow feature analysis and Bayesian regression is proposed in this paper. The proposed method can handle the dynamics of the process better by extracting quality-relevant slow features, which present both the slowly varying characteristic and the correlations with quality indices. Meanwhile, a Bayesian inference model is developed to predict the quality indices, which takes advantages of a probability framework with iterative maximum likelihood techniques for parameter estimation and a sparse constraint for avoiding overfitting. Finally, a case study is conducted with data sampled from a practical industrial propylene polymerization process to demonstrate the effectiveness and superiority of the proposed method.

scholarly journals Research on a product quality monitoring method based on multi scale PP-YOLO

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Yiting Li ◽  
Haisong Huang ◽  
Qipeng Chen ◽  
Qingsong Fan ◽  
Huafeng Quan
Keyword(s):  
Product Quality ◽  
Quality Monitoring ◽  
Monitoring Method ◽  
Multi Scale

scholarly journals Data-Driven Product Quality Monitoring in Quality-Critical Forming Processes

2021 ◽  
Vol 54 (4) ◽  
pp. 220-225
Author(s):  
M. Krüger ◽  
B. Vogel-Heuser ◽  
I. Weiß ◽  
E. Trunzer
Keyword(s):  
Product Quality ◽  
Quality Monitoring ◽  
Data Driven

scholarly journals A method of coding for aerospace product quality DNA

2018 ◽  
Vol 151 ◽  
pp. 05006
Author(s):  
Yao Jiayu
Keyword(s):  
Quality Assessment ◽  
Product Quality ◽  
Manufacturing Process ◽  
Feedback Mechanism ◽  
Quality Monitoring ◽  
The Core ◽  
Coding Method ◽  
Wall Panels ◽  
Variation Characteristics ◽  
Coding Rules

Aiming at the problem that the manufacturing process of our aerospace products is relatively discrete and the lack of appropriate quality monitoring and feedback mechanism, a method of coding for aerospace product quality DNA was proposed. Based on the structure of biological DNA and the theory of quality assessment, equipment diagnosis and quality traceability, the biological DNA structure was transformed into the structure of aerospace product quality DNA, and the concept of aerospace product quality DNA was defined, including the genetic and variation characteristics of aerospace product quality DNA. The coding rules of aerospace product quality DNA were designed, and the designed encoding rules are applied to the case of welding of wall panels in the manufacturing process of aerospace products. The results show that the coding method can monitor and feedback the core information related to quality in the manufacturing process of aerospace products.

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