Special Issue on Reliability Assessment and Quality Assurance of Industrial Equipment
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
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Currently, there are still some challenges to be studied further in identification of failure modes, efficient uncertainty quantification, rare failure probability assessment for industrial equipment, and measures of enhancing equipment quality and lengthening its life. The purpose of this special issue is to present the latest advancements in the field of reliability assessment and quality assurance of industrial equipment.
Topic Areas
THE SCOPE OF THIS ISSUE INCLUDES BUT IS NOT LIMITED TO:- Reliability evaluation of engine, robot and machine tool
- Model updating and structural health monitoring of engine and vehicle
- Quality assurance of industrial equipment under aleatory-epistemic uncertainty
- Sensitivity analysis and quality control of industrial equipment
- Reliability-based structural control and design optimization of industrial equipment
- Machine learning application in reliability assessment and health monitoring
- Fatigue reliability estimation and quality assurance of aero engine
- Application of digital twin technology in engine, robot and machine tool
- Impact of random environmental factors on equipment quality and life
- Development of predictive maintenance strategies
Submission Instructions
Papers should be submitted electronically to the journal through the ASME Journal Tool. If you already have an account, log in as an author and select Submit Paper. If you do not have an account, you can create one here.Once at the Paper Submittal page, select the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems Part B: Mechanical Engineering, and then under the Special Issue field, select Special Issue on Reliability Assessment and Quality Assurance of Industrial Equipment.
Papers received after the deadline or papers not selected for the Special Issue may be accepted for publication in a regular issue.
Guest Editors
Dixiong Yang, Dalian University of Technology (yangdx@dlut.edu.cn)
Sifeng Bi, University of Southampton (Sifeng.Bi@soton.ac.uk)
Zequn Wang, University of Electronic Science and Technology of China (zequnwang@uestc.edu.cn)
Matthias Faes, TU Dortmund University (matthias.faes@tu-dortmund.de)
Pengfei Wei, Northwestern Polytechnical University (pengfeiwei@nwpu.edu.cn)