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Reliability Analysis and Evaluation

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: closed (20 February 2023) | Viewed by 1418

Special Issue Editor


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Guest Editor
School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China
Interests: equipment quality reliability monitoring evaluation and optimization; reliability modeling and statistical analysis; statistical quality control

Special Issue Information

Dear Colleagues,

Reliability modeling and evaluation involve using a reliability block diagram and mathematical model to describe the functional logic relationship of each unit of the system and then evaluating the reliability of the product. Reliability modeling is a basic concept and the premise of all reliability activities. In the project design stage of products, it aims to allocate and predict the reliability; in the manufacturing stage, it is used for fault analysis (reliability analysis); after the product is manufactured, the inherent reliability of the product is evaluated through the reliability model. In recent years, computer technology has provided new methods able to cope with the complexity of reliability parameters, system complexity and task complexity, providing numerous analysis methods and processing methods, and advances in machine learning and artificial intelligence have provided new solutions for reliability data analysis. The main objective of this Special Issue is to present the opportunities, challenges, emerging solutions and latest applications of reliability modeling and evaluation.

Prof. Dr. Jun Yang
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. Applied Sciences 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 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

  • reliability modeling
  • reliability evaluation
  • system reliability
  • degradation
  • stochastic processes

Published Papers (1 paper)

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Research

22 pages, 3513 KiB  
Article
Integrity Detection and Supplementary Experimental Design of Semi-Physical Simulation Data on Aircraft Landing Points
by Bin Suo, Mengna Wang, Feimeng Yuan, Huapin Geng and Ying Yan
Appl. Sci. 2023, 13(5), 2889; https://doi.org/10.3390/app13052889 - 23 Feb 2023
Cited by 1 | Viewed by 1083
Abstract
For the semi-physical simulation test process of the coordinates of aircraft landing points, the concept of a completeness test for landing point simulation data is proposed, and a completeness test criterion based on field test data and expert estimation information is established. An [...] Read more.
For the semi-physical simulation test process of the coordinates of aircraft landing points, the concept of a completeness test for landing point simulation data is proposed, and a completeness test criterion based on field test data and expert estimation information is established. An integrity detection method for semi-physical simulation data, including data dimensionality reduction, data expansion, and regularization, drawing the envelope of the confidence region and establishing the completeness test criterion steps, is proposed. For landing points that do not satisfy the requirements of completeness, a surrogate model of the semi-physical simulation system was constructed based on a backpropagation neural network method, and the test conditions for data of this point were supplemented. Finally, application verification was carried out. Through the field and semi-physical simulation test research of a 534A aircraft, it was verified that the method can well realize the inspection of the completeness of the semi-physical simulation test data and the design of supplementary test conditions. It lays a good foundation for the fusion of subsequent semi-physical simulations and field test data. Full article
(This article belongs to the Special Issue Reliability Analysis and Evaluation)
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