A review of data mining applications for quality improvement in manufacturing industry
Many quality improvement (QI) programs including six sigma, design for six sigma, and
kaizen require collection and analysis of data to solve quality problems. Due to advances in …
kaizen require collection and analysis of data to solve quality problems. Due to advances in …
Customer churn in mobile markets a comparison of techniques
M Hassouna, A Tarhini, T Elyas… - arXiv preprint arXiv …, 2016 - arxiv.org
The high increase in the number of companies competing in mature markets makes
customer retention an important factor for any company to survive. Thus, many …
customer retention an important factor for any company to survive. Thus, many …
[HTML][HTML] Risk based uncertainty quantification to improve robustness of manufacturing operations
C Giannetti, RS Ransing - Computers & Industrial Engineering, 2016 - Elsevier
The cyber-physical systems of Industry 4.0 are expected to generate vast amount of in-
process data and revolutionise the way data, knowledge and wisdom is captured and …
process data and revolutionise the way data, knowledge and wisdom is captured and …
Deep multistage multi-task learning for quality prediction of multistage manufacturing systems
In multistage manufacturing systems, modeling multiple quality indices based on the
process sensing variables is important. However, the classic modeling technique predicts …
process sensing variables is important. However, the classic modeling technique predicts …
An empirical study on customer churn behaviours prediction using arabic twitter mining approach
With the rising growth of the telecommunication industry, the customer churn problem has
grown in significance as well. One of the most critical challenges in the data and voice …
grown in significance as well. One of the most critical challenges in the data and voice …
Firefighter perception of risk: A multinational analysis
M Martinez-Fiestas, I Rodríguez-Garzón… - Safety science, 2020 - Elsevier
This study addresses the question of risk perception among firefighters of four Spanish-
speaking countries (Argentina, Chile, Ecuador and Spain). It identifies (i) the conditions that …
speaking countries (Argentina, Chile, Ecuador and Spain). It identifies (i) the conditions that …
Data mining driven DMAIC framework for improving foundry quality–a case study
Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) methodology has been
widely used across industries as the best systematic and data driven problem solving …
widely used across industries as the best systematic and data driven problem solving …
Inspection of sandblasting defect in investment castings by deep convolutional neural network
Investment castings often have surface impurities, and pieces of shell moulds can remain on
the surface after sandblasting. Identification of defects involves time-consuming manual …
the surface after sandblasting. Identification of defects involves time-consuming manual …
Machine learning for quality prediction in abrasion-resistant material manufacturing process
P Mohammadi, ZJ Wang - 2016 IEEE Canadian Conference on …, 2016 - ieeexplore.ieee.org
Quality monitoring and prediction plays a key role in improving product quality and
achieving automated quality control in manufacturing processes such as the abrasion …
achieving automated quality control in manufacturing processes such as the abrasion …
Intelligent rework process management system under smart factory environment
DS Jo, TW Kim, JW Kim - Sustainability, 2020 - mdpi.com
Rework for defective items is very common in practical shopfloors; however, it generally
causes unnecessary energy consumptions and operational costs. In order to address this …
causes unnecessary energy consumptions and operational costs. In order to address this …