Sensors and Signal Processing in Manufacturing Processes
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".
Deadline for manuscript submissions: 30 March 2025 | Viewed by 1847
Special Issue Editors
Interests: manufacturing process; signal processing; diagnosis and monitoring; artificial intelligence
Interests: machining; friction stir; welding; titanium; incremental sheet metal forming; metals; process monitoring; patents; cutting tools
Interests: manufacturing engineering; machining
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Manufacturing processes play a critical role in industrial manufacturing. Optimizing these processes is vital for improving the industry’s efficiency, quality, and productivity. In this context, sensors and signal processing play a crucial role. Sensors are used to measure different physical variables and capture real-time information about the manufacturing process, such as cutting forces, temperature, vibrations, and displacements. These sensors can be integrated into machine tools or specific cutting tools.
Signal processing is the stage where sensor data is analyzed, filtered, and interpreted to extract relevant information about the manufacturing process. While focusing on manufacturing, this field also explores the potential integration of sensors and signal processing in other manufacturing processes. The main objective is to extract features and patterns from the signals to evaluate manufacturing quality, detect anomalies, optimize cutting parameters, predict tool wear, and control process stability.
The use of sensors and signal processing in manufacturing processes provides numerous advantages. It enables real-time monitoring of the process status, facilitating early detection of issues and reducing downtime. It also helps improve the precision and quality of end products by optimizing manufacturing parameters. Additionally, it contributes to workplace safety by providing information about hazardous conditions or abnormal situations.
In summary, “Sensors and Signal Processing in Manufacturing Processes” focuses on applying sensor technologies and signal analysis to optimize and control manufacturing processes. This research and development area aims to enhance the industry’s efficiency, quality, and productivity while ensuring the safety and optimal performance of manufacturing processes.
Prof. Dr. Alain Gil Del Val
Guest Editor
Dr. Mariluz Penalva
Dr. Fernando Veiga
Co-Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- manufacturing processes (cutting, joining, welding, additive, etc.)
- CNC machine tools
- cyber-physical systems
- digital twins
- big data management and analytics
- automation
- interoperability
- digital thread
- multisensor data fusion
- data acquisition
- smart monitoring and control
- precision machining
- intelligent process planning
- digital manufacturing
- additive manufacturing sensor integration
- human–machine interfaces
- adaptive interfaces
- human tracking and monitoring
- virtual reality, augmented reality and mixed reality
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