Multisensor Data Fusion Methods in Advanced Manufacturing

  in Special Issue   Posted on December 30, 2020

Information for the Special Issue

Submission Deadline: Fri 15 Jan 2021
Journal Impact Factor : 3.275
Journal Name : Sensors
Journal Publisher:
Website for the Special Issue: https://www.mdpi.com/journal/sensors/special_issues/multisensor_data_fusion
Journal & Submission Website: https://www.mdpi.com/journal/sensors

Special Issue Call for Papers:

Dear Colleagues,

In the current Industry 4.0 framework, the use of integrated and multiple sensors is becoming increasingly available for a wide range of applications. On the one hand, continuous technological advances are making real-time data processing and analysis from multiple sources a viable solution to achieving novel and smart manufacturing capabilities. On the other hand, new production paradigms—like additive manufacturing—are enabling novel in-process and multisensor data-gathering capabilities. Nevertheless, in most industrial applications, each single signal is commonly processed and treated as an individual source of information, and there are still few demonstrations of the actual potential enabled by merging and jointly exploiting the available multisource information content.

Therefore, we invite applicants to highlight the benefits of multisensor data fusion methods with respect to common industrial practices by presenting recent developments and innovative solutions applied to smart and advanced manufacturing processes.

Topics of interest include but are not limited to the following:

Multisensor data modeling;
Multisensor data reduction;
Multisensor data fusion via machine learning and artificial intelligence;
Multisensor fusion of image and video-image data;
Statistical process monitoring and quality control via multisensor data;
Multisensor fault detection and diagnostics;
Multisensor health condition monitoring;
Multisensor data fusion for predictive maintenance;
Multisensor/multifidelity data fusion in metrology;
Multisensor alignment, synchronization, and calibration;
Data fusion with redundant data;
Reliability enhancement via multisensor data and sensor validation.

Dr. Marco Grasso
Guest Editor

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