Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (6): 866-874.

### Reliability Prediction for Factory Casualty using Grey System Theory

Zhiguo Li,bo Hao, and Wengang Yan*

1. College of Mechanical Engineering, Inner Mongolia University of Technology of China, Hohhot, 010051, China
• Submitted on  ;  Revised on  ; Accepted on
• Contact: * E-mail address: 757434408@qq.com
• About author:Zhiguo Li is currently an associate professor at Inner Mongolia University of Technology, China. He received his M.D. from Inner Mongolia Agricultural University in 2007. His main research interests include mechanical optimization design.
Bo Hao is currently a master's candidate at Inner Mongolia University of Technology. His main research interests include mechanical optimization design and reliability prediction.
Wengang Yan is currently a lecturer at Inner Mongolia University of Technology. He received his Ph.D. from Beijing Forestry University in 2012. His main research interests include the utilization and development of biomass energy.
• Supported by:
The research in this paper is supported by the National Natural Science Foundation of China (No. 51765052).

Abstract: To reduce the casualty rate in factories, grey system theory (GST) is used to predict safety targets. First, the reliability-based dynamic model and differential equation of grey model GM(1, 1) are established on the basis of GST. Then, the sequence results are accumulated and inverse accumulated further, thus further revealing the change law. According to the analysis results of relative error q, variance ratio C, and small error probability P, the accuracy test for the prediction model indicates that the GM(1, 1) has high prediction reliability and that the prediction precision is a good rank (P > 0.95, C < 0.35). Finally, the prediction results show that the predicted casualty number was 18.2-48.3 in 2017, 35.1-72 in 2018, and 67.9-107.5 in 2019, and both the casualty rate and casualty number will increase over the next three years. The findings in this paper will help guide the establishment of factory safety targets.