Statistics, Data Analytics, and Machine Learning in Manufacturing
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 10 January 2026 | Viewed by 23
Special Issue Editor
Interests: statistical quality assurance; statistics, data analytics, and machine learning in advanced manufacturing; non-destructive evaluation, healthcare, and other engineering and natural science applications
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Statistics, data analytics, and machine learning play a pivotal role in driving innovation and enhancing performance in advanced manufacturing systems. This Special Issue encourages the submission of high-quality research papers that explore the integration of data-driven approaches in manufacturing processes. Topics of interest include, but are not limited to, the following:
- Process monitoring;
- Anomaly and defect detection;
- Variation quantification;
- System and process optimization;
- Uncertainty quantification and propagation;
- Digital twin technologies;
- Reliability analysis.
We particularly seek contributions that present novel methodologies or discuss innovative and impactful applications within these domains. Review articles are also welcome, especially those that provide critical insights and elucidate emerging directions for future research in data analytics for manufacturing.
All submissions should be rigorously researched, clearly structured, and written in professional English, with the goal of being accessible and engaging to a broad interdisciplinary audience. There are no restrictions on paper length or the use of color figures and diagrams.
Authors are encouraged to include supplementary materials such as software code, detailed derivations, extensive datasets, or comprehensive descriptions of experimental procedures and computations. If these materials are too lengthy for inclusion in the main text, they may be submitted as appendices or supplementary files.
Dr. Qing Li
Guest Editor
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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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
- process monitoring/prognosis
- anomaly/defect detection
- uncertainty quantification
- system/process optimization
- reliability analysis
- statistics
- machine learning/deep learning
- data fusion
- measurements
- quality assurance
- uncertainty propagation
- digital twin
- geometry compensation
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