Advanced Statistical Control and Predictive Maintenance Models for Industry 4.0
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Mathematics and Computer Science".
Deadline for manuscript submissions: 31 October 2024 | Viewed by 3202
Special Issue Editors
Interests: predictive maintenance; prognostics and health management; machine learning; Industry 4.0
Special Issue Information
Dear Colleagues,
The production processes of the future (Industry 4.0) are intelligent systems composed of several cyber-physical modules (CPMs). A CPM can be an integration of a machine (physical part) with its intelligent sensors (IoT: Internet of Things) and actuators to enable it to automatically collect information about the machine’s condition and also the product quality. This information is very useful for maintenance planning and quality control of these production processes. Correct implementation of both maintenance and quality control can help to avoid machine failures and improve processes’ performances. However, the collected data about a production process are complex and usually recognized as big data. The exploitation of these data is then very challenging. For this reason, this Special Issue collects papers with the aim to develop advanced models based on machine learning/deep learning for predictive maintenance planning and statistical control of the future production processes. We expect that these advanced models will be a theoretical basis for improving the performance of the industrial processes and support the zero-failure and zero-defect concepts of Industry 4.0.
Dr. Hai-Canh VU
Dr. Nassim Boudaoud
Guest Editors
Manuscript Submission Information
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