Advances in Data Analytics for Manufacturing Quality Assurance
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 2910
Special Issue Editors
Interests: quality assurance; data analytics in advanced manufacturing; non-destructive evaluation; Bayesian analysis; engineering and natural science applications of statistics and machine learning; health risk prediction and prevention
Interests: statistical machine learning; data fusion; precision medicine; population health
Interests: machine learning; multi-modal data and missing data in healthcare; medical image analysis; anomaly detection in semiconductor industry; traffic and car crash predictions
Special Issue Information
Dear Colleagues,
Data analytics, statistics, and machine learning play crucial roles in advanced manufacturing. In this Special Issue, we are looking for high-quality research papers relevant to data analytics for manufacturing quality assurance, including process monitoring, anomaly/defect detection, variation quantification, system/process optimization, and reliability analysis. Articles that establish new methodologies in these topics or provide interesting and innovative applications are immensely welcome. Reviews will also be considered, mainly those that may provide commentaries that lead to open perspectives of new methodologies and applications.
Submissions must be rigorous, clear, well-written in professional English, and accessible and appealing to a broad audience. There is no restriction on the length of the papers, nor the use of color figures and diagrams. However, if thought to be adequate, electronic files with software or computer codes, full details of calculations, and full descriptions of experimental procedures, lengthy datasets, or detailed proof that may be judged to be too lengthy to be inserted in the body of the paper may be added in the Appendix and/or supplementary materials.
Dr. Qing Li
Dr. Bing Si
Dr. Renjie Hu
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. 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 evaluation