Title
Advanced Process Defect Monitoring Model and Prediction Improvement by Artificial Neural Network in Kitchen Manufacturing Industry: a Case of Study
Abstract
This paper analyzes a methodological approach based on p control charts able to control defects into a new production line of kitchen manufacturing and to monitor the proportion of nonconforming units of the specific cutting process. The control is enabled by measuring the defects of different samples of pieces of kitchens. The proposed approach is improved by artificial neural networks -ANN- predicting defect entity by defining a new model to improve quality and production control. The ANN algorithm is suitable for predictive maintenance of kitchen production lines and for product quality prediction. The study is completed by the correlation matrix analysis, thus providing an alternative approach to interpret defect causes. The proposed model has been developed within the framework of a research industry project.
Year
DOI
Venue
2019
10.1109/METROI4.2019.8792872
2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT)
Keywords
Field
DocType
process monitoring,process mapping,process innovation,XmR charts,predictive maintenance,artificial neural network,correlation matrix,data mining
Data mining,Manufacturing,Production control,Computer science,Control chart,Production line,Process control,Covariance matrix,Artificial neural network,Predictive maintenance
Conference
ISBN
Citations 
PageRank 
978-1-7281-0430-0
0
0.34
References 
Authors
2
4
Name
Order
Citations
PageRank
Alessandro S. Massaro1187.91
Ivano Manfredonia200.34
Angelo Galiano321.79
Benny Xhahysa411.04