Machine learning–based automated image processing for quality management in industrial Internet of Things

Abstract

The aim of this article is to automate quality control once a product, essentially a central processing unit system, is manufactured. Creating a model that helps in quality control, increases efficiency and speed of production by rejecting abnormal products automatically is vital. A widely used technology for this is to use industrial image processing that is based on the use of special cameras or imaging systems installed within the production line. In this article, we propose a highly efficient model to automate central processing unit system production lines in an industry such that images of the production lines are scanned and any abnormalities in their assembly are pointed out by the model and information about this is transferred to the system administrator via a cyber-physical cloud system network. A machine learning-based approach is used for proper classification. This model not only focuses on just the abnormalities but also helps in configuring the angles from which images of the production are taken, and our methods show 92% accuracy.

Expectile Regression on Distributed Large-Scale Data

“…where (•) is defined by (1). Note that ( ) is the loss function evaluated at by using the local data stored in the th machine ℳ , and…”

“…The dataset comes from the Superconducting Material Database maintained by Japan's National Institute for Materials Science (NIMS) and is also available from the UCI Machine Learning Repository. 1 The goal here is to predict the critical temperature based on the features extracted from the superconductor's chemical formula. Readers may refer to Hamidieh [30] for a detailed description of this dataset.…”

“…In recent years, machine learning techniques based on largescale data have been widely used in inspection systems, correct classification and Internet of Things, as well as in social networks and smart cities [1]- [3]. As for the largescale data, the problem is not only the size of the data, but in fact the data is usually stored in multiple locations.…”

Deep Learning aplicado a inspeção visual da presença de um componente de conjunto de eixo

“…Na indústria, é dito que a quarta revolução industrial ou Indústria 4.0 vai nos levar ao próximo nível de manufatura onde as máquinas irão se redefinir na forma como se comunicam e executam funções individuais [1]. Nesse contexto, muitas empresas recorrem à automação para superar desafios como problemas de qualidade, eficiência e custos [2]. Quando se trata da detecção de problemas de qualidade, tem sido cada vez mais comum o uso de tecnologias que envolvem processamento de imagens e Inteligência Artificial (Artificial Intelligence -AI) [2] [3].…”

“…Nesse contexto, muitas empresas recorrem à automação para superar desafios como problemas de qualidade, eficiência e custos [2]. Quando se trata da detecção de problemas de qualidade, tem sido cada vez mais comum o uso de tecnologias que envolvem processamento de imagens e Inteligência Artificial (Artificial Intelligence -AI) [2] [3].…”