Physics-of-Failure based Model for Industrial Robot Reliability Prediction
Jiafan Zhang, Wei Song
- 发表年份
- 2020
- 引用次数
- 5
摘要
Millions of industrial robots are being used around the world for diversified applications, like material handling, machine tending, spot-welding, arc-welding and so on. The reliability and quality of industrial robots is becoming more and more highlighted. Over decades, many studies have appeared to address this problem. In this work, a Physics-of-Failure (PoF) based reliability prediction model of industrial robot is initiated. By leveraging the comprehensive knowledge and understanding of the processes and the mechanisms that induce failures quantitatively formulate the contributions of each component and their subcomponents in terms of design parameters, working loads and environmental conditions, thereof enables to predict the reliability of the overall industrial robot.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991