Open AccessEvaluation and Improvement of the Intrinsic Safety Level of Employees
Author(s) -
Jing Zhang,
Xiaonuo Zhang,
Yan Ya
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1756/1/012014
Subject(s) - intrinsic safety , process (computing) , sample (material) , matching (statistics) , computer science , risk analysis (engineering) , order (exchange) , reliability engineering , power (physics) , power grid , process management , business , engineering , mathematics , chemistry , physics , statistics , finance , chromatography , quantum mechanics , operating system
Intrinsic safety is the eternal pursuit of power companies. The intrinsic safety level of front-line employees of technical skills posts is the basic guarantee for the security and stability operation of power systems. In order to help power companies scientifically evaluate and effectively improve the intrinsic safety level of employees, a quantifiable evaluation model is created. Combining with the sample to give a verification process, the validity of the model is confirmed. It shows that this model can be adjust to be much greater targeting for different types of jobs of grid companies and the evaluation efficiency is improved while ensuring the accuracy of the evaluation. In practical applications, the evaluation results have many uses such as providing reference for talent-post matching. This paper also designed a training system that matches the evaluation model, which can provide employees with targeted learning basing on their own weak links and quickly improve the intrinsic safety level.