Application of the PSO–SVM model for recognition of control chart patterns
Control chart patterns are important statistical process control tools for determining whether
a process is run in its intended mode or in the presence of unnatural patterns. Accurate …
a process is run in its intended mode or in the presence of unnatural patterns. Accurate …
Control chart recognition based on the parallel model of CNN and LSTM with GA optimization
Y Yu, M Zhang - Expert Systems with Applications, 2021 - Elsevier
Quality control process has become one of the most critical issues in intelligent
manufacturing. As the most practical and prevalent tools for continuously monitoring, control …
manufacturing. As the most practical and prevalent tools for continuously monitoring, control …
Recognition of control chart patterns using fuzzy SVM with a hybrid kernel function
X Zhou, P Jiang, X Wang - Journal of Intelligent Manufacturing, 2018 - Springer
Accurate control chart patterns recognition (CCPR) plays an essential role in the
implementation of control charts. However, it is a challenging problem since nonrandom …
implementation of control charts. However, it is a challenging problem since nonrandom …
Control chart pattern recognition using K-MICA clustering and neural networks
Automatic recognition of abnormal patterns in control charts has seen increasing demands
nowadays in manufacturing processes. This paper presents a novel hybrid intelligent …
nowadays in manufacturing processes. This paper presents a novel hybrid intelligent …
Control chart patterns recognition using ANFIS with new training algorithm and intelligent utilization of shape and statistical features
S Babouei - ISA transactions, 2020 - Elsevier
This paper presents a new method for recognition of nine control chart patterns (CCPs)
based on the intelligent use of shape and statistical features and optimized fuzzy system …
based on the intelligent use of shape and statistical features and optimized fuzzy system …
Control chart pattern recognition using a novel hybrid intelligent method
V Ranaee, A Ebrahimzadeh - Applied Soft Computing, 2011 - Elsevier
Control chart patterns (CCPs) are important statistical process control tools for determining
whether a process is run in its intended mode or in the presence of unnatural patterns …
whether a process is run in its intended mode or in the presence of unnatural patterns …
Control chart pattern recognition using an optimized neural network and efficient features
A Ebrahimzadeh, V Ranaee - ISA transactions, 2010 - Elsevier
Automatic recognition of abnormal patterns in control charts has seen increasing demands
nowadays in manufacturing processes. This study investigates the design of an accurate …
nowadays in manufacturing processes. This study investigates the design of an accurate …
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Manufacturing processes have become highly accurate and precise in recent years,
particularly in the chemical, aerospace, and electronics industries. This has attracted …
particularly in the chemical, aerospace, and electronics industries. This has attracted …
[PDF][PDF] Control chart patterns detection using COA based trained MLP neural network and shape features
A Addeh, BM Maghsoudi - Computational Research Progress in …, 2016 - jms.procedia.org
Statistical process control (SPC) is widely applied as a potent tool to measure, recognize,
analyze and interpret process data to enhance the quality of products and service by …
analyze and interpret process data to enhance the quality of products and service by …
Control chart pattern recognition using adaptive back-propagation artificial Neural networks and efficient features
J Addeh, A Ebrahimzadeh… - The 2nd International …, 2011 - ieeexplore.ieee.org
Control chart patterns are important statistical process control tools for determining whether
a process is running in its intended mode or in the presence of unnatural patterns. Accurate …
a process is running in its intended mode or in the presence of unnatural patterns. Accurate …