基于大数据的安全风险管理模型研究

发布时间：2018-11-01 14:48

【摘要】：现阶段,我国安全生产的管理工作趋于复杂化,对于遏制重特大事故与控制削弱潜在安全风险的目标造成新的挑战。目前大多数的风险管理工作主要还是依靠人力,通过相关专业人员的专业知识去发现生产活动中存在的安全隐患,这种形式容易受到人为主观因素的影响,并且容易使安全与危险状态模糊界定,所得到的结果可靠性差。因此依靠传统的安全生产管理理念和方式很难实现“四个全面”的要求。需要一种全新的模式去改变这一安全生产现状。大数据作为一种全新的技术和独特的思维方式在安全生产过程中的应用,其最基本的功能价值就是从海量的安全生产活动所生成的数据中分析出安全生产的潜在规律,从而预测未来以消除潜在的安全隐患,以有效遏制事故发生的可能性。同时,大数据在降低隐患排查成本、提高事故预防效率和增强监管工作针对性提升安全监管能力方面也可发挥重要作用。本论文主要进行了以下研究。首先,对安全生产与大数据进行关联分析研究,结合大数据的相关理论和4V特征,从数据结构、数据来源、数据类型三个维度进行综合考虑提出了安全生产大数据的概念,并应用5W1H的科学分析方法分析了安全生产大数据的理论基础、应用和受益主体、主要实现功能、应用环节以及如何利用安全生产大数据等基础理论问题。其次,进行了基于大数据的安全风险管理模型研究,给出了基于大数据的安全风险管理模型建立的原则以及大数据方面的技术基础,应用系统霍尔三维模型思维方法,针对风险管理的三大步骤,分别建立了基于大数据的风险辨识模型、风险评价分级模型、风险预警预控模型,并详细说明了大数据的应用对风险管理中的风险辨识、风险评价分级、风险预警预控所带来的思维变革、运行模式变革以及流程的变革。最后,以建筑施工项目为例,分析研究了华润置地北京大区首开华润城安全生产环境以及安全管理现状,并就基于大数据的安全风险管理应用于现场安全管理进行了可行性和展望性分析。
[Abstract]:At present, the management of safety production in our country tends to be complicated, which poses a new challenge to the goal of containing serious and serious accidents and controlling and weakening the potential safety risks. At present, most of the risk management work mainly relies on manpower, through the professional knowledge of relevant professionals to discover the hidden dangers of safety in production activities, this form is vulnerable to the influence of human subjective factors. And it is easy to make the fuzzy definition of safety and dangerous state, and the reliability of the result is poor. Therefore, it is difficult to realize the "four-round" requirements by relying on the traditional concept and method of production safety management. A new model is needed to change this safe production situation. Big data, as a new technology and unique mode of thinking in the process of production safety application, its most basic functional value is to analyze the potential laws of safety production from the mass of data generated by production safety activities. In order to predict the future to eliminate the potential safety risks, in order to effectively contain the possibility of accidents. At the same time, big data can also play an important role in reducing the cost of hidden trouble detection, improving the efficiency of accident prevention and enhancing the safety supervision ability. This thesis mainly carries on the following research. First of all, the paper analyzes the relationship between safety production and big data, and puts forward the concept of big data of safe production from three dimensions of data structure, data source and data type, combined with the relevant theory and 4V characteristics of big data. By using the scientific analysis method of 5W1H, this paper analyzes the basic theory of big data, the main body of application and benefit, the main function, the application link and the basic theoretical problems such as how to make use of big data in safe production and so on. Secondly, the security risk management model based on big data is studied, and the principle of building the security risk management model based on big data and the technical foundation of big data are given, and the thinking method of Hall three-dimensional model is applied. Aiming at the three steps of risk management, the paper establishes the risk identification model based on big data, the risk evaluation classification model and the risk forewarning and pre-control model, and explains in detail the risk identification in risk management by the application of big data. The change of thinking, operation mode and process brought by risk assessment classification, risk early warning and pre-control. Finally, taking the construction project as an example, the paper analyzes and studies the safety production environment and safety management status of the first China Resources City in Beijing. The feasibility and prospect of the application of safety risk management based on big data in site safety management are analyzed.
【学位授予单位】：中国地质大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：X92

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