Time Between Events Monitoring for Imperfect Maintained Systems with Application to a Robotic System-Reference-Cited by-同舟云学术

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Time Between Events Monitoring for Imperfect Maintained Systems with Application to a Robotic System

Published:2021-10-27 Issue: Volume: Page:1-26
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Maged Ahmed¹²^ORCID,Haridy Salah²³^ORCID,Khoo Michael B. C.⁴^ORCID,Shamsuzzaman Mohammad³^ORCID

Affiliation:

1. Department of Advanced Design and Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong

2. Department of Mechanical Engineering, Benha Faculty of Engineering, Benha University, Benha, Egypt

3. Department of Industrial Engineering and Engineering Management, College of Engineering, University of Sharjah, Sharjah, United Arab Emirates

4. School of Mathematical Science, Universiti Sains Malaysia, Malaysia

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2021.1993224

Reference42 articles.

1. Time-variant reliability analysis of a continuous system with strength deterioration based on subset simulation

2. Optimization of the joint selective maintenance and repairperson assignment problem under imperfect maintenance

3. Availability analysis of a general time distribution system with the consideration of maintenance and spares

4. A review on condition-based maintenance optimization models for stochastically deteriorating system

5. Maintenance scheduling of a protection system subject to imperfect inspection and replacement

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Joint design of VSI Tr control chart and equipment maintenance in high quality process;Journal of Process Control;2024-04

2. Recognition of abnormal patterns in industrial processes with variable window size via convolutional neural networks and AdaBoost;Journal of Intelligent Manufacturing;2022-01-20

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