智慧图书馆设备故障规避的HFACS等级相关分析

大数据人工智能时代下图书馆各项新技术设备的应用为智慧图书馆的发展提供了高效智能化的技术支持,实现了智慧服务的自动化,帮助用户更加便捷地获取、利用、分享图书馆的各项资源;但随着内外环境的变化影响,设备故障问题也日益突出,如何有效规避智慧设备故障隐患,降低故障风险成为亟待解决的新课题。笔者通过自身工作实际结合相关文献资料,统计发现影响设备故障主要分为四类因素,其中人为因素占了很大比例,进一步深入分析得出含制度设计、流程执行等16种因子的四层改进型HFACS框架。通过设备故障样本集数据集计算Spearman和Kendall Tau—b相关系数得出各层等级相关度,逐步挖掘出各层内在相关逻辑因子,探究出设备故障致因链进行分析,总结归纳启示性建议为图书馆相关智慧管理和服务提供科学依据。

HFACS Level Correlation Analysis of Smart Library Equipment Fault Avoidance

The application of new technologies and equipments in the era of big data artificial intelligence provides efficient and intelligent technical support for the development of smart libraries,realizes the automation of smart services,and helps users to more easily acquire,utilize and share libraries.Various resources;however,with the changes of internal and external environment,the problem of equipment failure has become increasingly prominent.How to effectively avoid the hidden troubles of smart equipment and reduce the risk of failure has become a new problem to be solved.The author actually combines the relevant literature with his own work.The statistics show that the equipment failures are mainly divided into four types of factors,of which human factors account for a large proportion.Further in-depth analysis results in four layers of improvement including 16 factors including system design and process execution.Type HFACS framework.The Spearman and Kendall Tau-b correlation coefficients are calculated from the equipment fault sample set data set to obtain the hierarchical correlation degree of each layer,and the relevant internal logic factors are gradually explored to explore the cause chain of the equipment failure analysis.Library-based wisdom management and services provide a scientific basis.