中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (S1): 29-35.doi: 10.16265/j.cnki.issn1003-3033.2026.S1.0005

• 安全科学理论与方法 • 上一篇    下一篇

多产业集团分类安全绩效评价体系构建研究

李兴()   

  1. 国家能源投资集团有限责任公司 安全环保监察部, 北京 100011
  • 收稿日期:2026-02-14 修回日期:2026-04-12 出版日期:2026-06-30
  • 作者简介:

    李 兴 (1989—),男,河南信阳人,硕士,工程师,主要从事安全管理体系、电力安全等方面的研究。E-mail:。

Construction of tiered safety performance evaluation system for multi-industry groups

Li Xing()   

  1. Safety and Environmental Supervision Department, CHN Energy, Beijing 100011, China
  • Received:2026-02-14 Revised:2026-04-12 Published:2026-06-30

摘要:

为提高多产业集团安全管理水平,构建基于子分公司安全管理难度分类评估的安全绩效评价体系。首先,综合分析子分公司行业属性、规模、员工数量等6个关键指标,运用层次分析法(AHP)、熵权法(EWM)确定指标权重,利用K-means聚类算法确定子分公司安全管理难度类别;然后,综合分析组织机构、风险管控、应急管理、事故指标等主要要素,从控制性指标、约束性指标、激励性指标3个维度,构建“子分公司季度自评+集团年度综合评价”的计划、执行、检查和处理(PDCA)绩效评价机制,实现对不同类别子分公司的差异化管理;最后,建立安全风险指数(SRI)监测预警模型,量化评估安全生产过程的关键指标,并进行分级预警和干预。研究结果表明:安全管理难度评价模型能实现对子分公司安全管理难度的量化分级;安全绩效评价体系及其PDCA循环机制,能实现对不同类别子分公司的差异化考核与激励,推动安全绩效的持续改进; SRI监测预警模型可实现对关键指标失效情况的量化评估和分级预警。

关键词: 多产业集团, 安全绩效评价, 安全管理难度, 层次分析法(AHP), 安全风险指数(SRI)

Abstract:

To improve the safety management level of multi-industry groups, a safety performance evaluation system based on the classification and evaluation of the safety management difficulty of subsidiary companies was constructed. First, six key indicators including industry attributes, scale, and employee count were comprehensively analyzed. Indicator weights were determined through the AHP and Entropy Weight Method(EWM). Subsidiary safety management difficulty categories were identified via K-means clustering. Then, such main elements as organizational systems, risk control, emergency management, and accident indicators were comprehensively analyzed. From three dimensions of control indicators, constraint indicators, and incentive indicators, a Plan-Do-Check-Act (PDCA) performance evaluation mechanism of "quarterly self-assessment by subsidiaries + annual comprehensive evaluation by the group" was established to achieve differentiated management for different subsidiaries. Finally, a SRI monitoring and early warning model was developed to quantitatively assess key indicators in the safety production process and enable graded early warnings and interventions. Research results show that the safety management difficulty evaluation model enables the quantitative classification of the safety management difficulty of subsidiaries. The safety performance evaluation system, together with its PDCA cycle mechanism, realizes differentiated assessment and incentives for subsidiaries of different categories, thereby promoting continuous improvement of safety performance. The SRI monitoring and early warning model achieves quantitative evaluation and graded early warning of key indicator failures.

Key words: multi-industry groups, safety performance evaluation, safety management difficulty, analytic hierarchy process (AHP), safety risk index (SRI)

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