A review of machine learning for the optimization of production processes
Due to the advances in the digitalization process of the manufacturing industry and the
resulting available data, there is tremendous progress and large interest in integrating …
resulting available data, there is tremendous progress and large interest in integrating …
Data mining in manufacturing: a review
The paper reviews applications of data mining in manufacturing engineering, in particular
production processes, operations, fault detection, maintenance, decision support, and …
production processes, operations, fault detection, maintenance, decision support, and …
Defining a data-driven maintenance policy: an application to an oil refinery plant
Purpose The purpose of this paper is developing a data-driven maintenance policy through
the analysis of vast amount of data and its application to an oil refinery plant. The …
the analysis of vast amount of data and its application to an oil refinery plant. The …
Applying data mining techniques to address critical process optimization needs in advanced manufacturing
Advanced manufacturing such as aerospace, semi-conductor, and flat display device often
involves complex production processes, and generates large volume of production data. In …
involves complex production processes, and generates large volume of production data. In …
Striving for zero defect production: intelligent manufacturing control through data mining in continuous rolling mill processes
B Konrad, D Lieber, J Deuse - … of the CIRP Sponsored Conference RoMaC …, 2013 - Springer
Steel production processes are renowned for being energy and material demanding.
Moreover, due to organizational and technological restrictions in flow production processes …
Moreover, due to organizational and technological restrictions in flow production processes …
FIU-Miner (a fast, integrated, and user-friendly system for data mining) and its applications
Abstract The advent of Big Data era drives data analysts from different domains to use data
mining techniques for data analysis. However, performing data analysis in a specific domain …
mining techniques for data analysis. However, performing data analysis in a specific domain …
Process control in a press hardening production line with numerous process variables and quality criteria
A Stoll, N Pierschel, K Wenzel, T Langer - Machine Learning for Cyber …, 2018 - Springer
Today, the optimization of the press hardening process is still a complex and challenging
task. This report describes the combination of linear regression with least squares …
task. This report describes the combination of linear regression with least squares …
[PDF][PDF] Mining industrial engineered data of apparel industry: a proposed methodology
MS Rahim, M Rahman, AE Chowdhury - International Journal of …, 2017 - academia.edu
Data mining and knowledge discovery play a significant role in the field of industrial
engineering as the vast amount of generated data help to reveal previously unknown …
engineering as the vast amount of generated data help to reveal previously unknown …
Optimizing the formation of the quality improvement teams through a data mining–based methodology
B Al-Salim - Quality Engineering, 2006 - Taylor & Francis
A data mining–based methodology is proposed for optimizing the process of designing and
allocating the quality improvement teams to investigate and eliminate the quality problems …
allocating the quality improvement teams to investigate and eliminate the quality problems …
Data-driven approaches to maintenance policy definition: general framework and applications
S Antomarioni - 2021 - iris.univpm.it
The competitiveness characterizing the current industrial scenario requires high levels of
process reliability. This aspect is particularly relevant for complex plants since many …
process reliability. This aspect is particularly relevant for complex plants since many …