基于MICMAC-FCMs的建筑施工风险动态演化及干预模拟研究

熊坚; 彭一鸣; 蔡晶

doi:10.19713/j.cnki.43-1423/u.T20222190

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基于MICMAC-FCMs的建筑施工风险动态演化及干预模拟研究

工程经济•工程管理•规划设计 | 更新时间：2023-12-05

- 基于MICMAC-FCMs的建筑施工风险动态演化及干预模拟研究
- Dynamic evolution and intervention simulation of construction risk based on MICMAC-FCMs
- 铁道科学与工程学报 2023年20卷第11期页码：4356-4366
- 作者机构：
  
  1.昆明理工大学交通工程学院，云南昆明 650500
- 作者简介：
  
  蔡晶(1989—)，女，云南个旧人，讲师，博士，从事交通系统安全与仿真等研究；E-mail：caijing@kust.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(71961012);云南省交通厅科技创新及示范项目(HZ2021X0302A);云南省教育厅科学研究基金项目(2023J0095)
- DOI：10.19713/j.cnki.43-1423/u.T20222190
  中图分类号：
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熊坚,彭一鸣,蔡晶.基于MICMAC-FCMs的建筑施工风险动态演化及干预模拟研究[J].铁道科学与工程学报,2023,20(11):4356-4366.

XIONG Jian,PENG Yiming,CAI Jing.Dynamic evolution and intervention simulation of construction risk based on MICMAC-FCMs[J].Journal of Railway Science and Engineering,2023,20(11):4356-4366.
熊坚,彭一鸣,蔡晶.基于MICMAC-FCMs的建筑施工风险动态演化及干预模拟研究[J].铁道科学与工程学报,2023,20(11):4356-4366. DOI： 10.19713/j.cnki.43-1423/u.T20222190.

XIONG Jian,PENG Yiming,CAI Jing.Dynamic evolution and intervention simulation of construction risk based on MICMAC-FCMs[J].Journal of Railway Science and Engineering,2023,20(11):4356-4366. DOI： 10.19713/j.cnki.43-1423/u.T20222190.

摘要

为了预防和减少安全生产事故的发生，提出一种动态风险分析方法，在有效辨识建筑施工风险关键因素的基础上，定量刻画风险的动态演化趋势，并制定针对性干预策略，为改善建筑企业安全环境提供防控手段。首先，基于文献研究与事故致因理论，从人员、环境、设备、管理4个方面，拓展并建立了包含20个条目的施工风险因素分析框架。其次，结合灰色关联分析(GRA)与解释结构模型(ISM)确定可达矩阵，运用交叉影响矩阵相乘法(MICMAC)筛选施工风险关键因素。最后，基于模糊认知图(FCMs)理论对风险节点权重进行动态推导，通过设置不同单目标的干预场景进行模拟仿真，比较了不同方案对于施工风险的影响程度。研究结果表明：影响施工风险的关键因素包括防护用具使用c,11,，操作行为c,12,，隐患辨识c,13,，安全检查c,43,，安全反馈机制c,44,，现场监管c,46,；项目前期，风险因素权重排序为c,11,>,c,43,>,c,13,>,c,44,>,c,12,>,c,46,；项目推进阶段，c,12,，c,44,，c,46,的权重有所增加，变化速率大小为c,46,>,c,12,>,c,44,，而c,11,，c,13,，c,43,的权重均在减小，变化速率大小为c,11,>,c,43,>,c,13,；项目后期，风险因素权重排序为c,46,>,c,12,>,c,44,>,c,13,>,c,43,>,c,11,；干预效果方面，针对c,11,的干预能在较大程度上影响施工风险水平，以c,46,为对象的干预方案获得的安全收益较差。研究成果揭示了建筑施工风险的动态变化过程，可为企业风险防控策略提供一定的理论依据及决策参考。

Abstract

To prevent and reduce the occurrence of construction safety accidents, a dynamic risk analysis method was proposed. Based on effectively identifying the key factors of construction risk. The dynamic evolution trend of risk was described quantitatively, and targeted intervention strategies were formulated to provide prevention and control means for improving the safety environment of construction enterprises.Firstly, a construction risk factor analysis framework containing 20 items was established based on literature research and accident cause theory from four aspects: personnel, environment, equipment, and management. Secondly, the accessibility matrix was determined by Grey Relationship Analysis (GRA) and Interpretation Structural Model (ISM), and the key factors of construction risk were screened by Matrix Impacts Cross-reference Multiplication Applied to a Classification (MICMAC). Finally, the risk node weight was dynamically derived based on the Fuzzy Cognitive Maps (FCMs) theory, and the intervention scenarios with different single objectives were simulated to compare the impact of different schemes on the construction risk. The results are drawn as follows. The key factors affecting construction risk include the use of protective equipment (c,11,), operant behavior (c,12,), risk identification (c,13,), safety inspection (c,43,), safety feedback system (c,44,), on-site supervision (c,46,). In the initial stage of the construction project, the weight of risk factors was c,11,>,c,43,>,c,13,>,c,44,>,c,12,>,c,46,. During the project promotion stage, the weights of c,12, c,44, and c,46, are increasing. The rate of change is c,46,>,c,12,>,c,44, the weights of c,11, c,13, and c,43, are decreasing, and the rate of change is c,11,>,c,43,>,c,13,. In the later stage of the project, the weight of risk factors is c,46,>,c,12,>,c,44,>,c,13,>,c,43,>,c,11,. In terms of intervention effect, the intervention for c,11, can affect the level of construction risk to a large extent, while the intervention plan for c,46, has poor safety benefits. The findings of the study shed light on the dynamic change process of construction risk, which can serve as a theoretical foundation and decision-making reference for enterprise risk prevention and control strategies.

关键词

安全工程风险分析集成方法趋势预测情景模拟

Keywords

safety engineeringrisk analysisintegration methodtrend predictionscenario simulation

references

董利飞, 陈飞宇, 王苗, 等. 建筑施工安全事故死亡人数预测与影响因素分析[J]. 安全与环境学报, 2022, 22(3): 1430-1435.

DONG Lifei, CHEN Feiyu, WANG Miao, et al. Analysis on the forecast of construction death and its influence factors[J]. Journal of Safety and Environment, 2022, 22(3): 1430-1435.

ALBERT A, PANDIT B, PATIL Y, et al. Does the potential safety risk affect whether particular construction hazards are recognized or not?[J]. Journal of Safety Research, 2020, 75: 241-250.

XU Qingwei, XU Kaili. Analysis of the characteristics of fatal accidents in the construction industry in China based on statistical data[J]. International Journal of Environmental Research and Public Health, 2021, 18(4): 2162.

CHAPMAN C B, COOPER D F. Risk engineering: basic controlled interval and memory models[J]. Journal of the Operational Research Society, 1983, 34(1): 51-60.

JEONG J, JEONG J. Quantitative risk evaluation of fatal incidents in construction based on frequency and probability analysis[J]. Journal of Management in Engineering, 2022, 38(2): 04021089.

CHEN Hongyu, ZHANG Limao, WU Xianguo. Performance risk assessment in public-private partnership projects based on adaptive fuzzy cognitive map[J]. Applied Soft Computing, 2020, 93: 106413.

陈蓉芳, 姜安民, 董彦辰, 等. 装配式建筑施工质量风险评估模型的构建与应用研究[J]. 铁道科学与工程学报, 2021, 18(10): 2788-2796.

CHEN Rongfang, JIANG Anmin, DONG Yanchen, et al. Construction and application of risk assessment model for assembled building construction quality[J]. Journal of Railway Science and Engineering, 2021, 18(10): 2788-2796.

李明柱, 王文东, 张智超. 基于ISM与MICMAC的建筑施工风险因素研究[J]. 安全与环境学报, 2022, 22(1): 22-28.

LI Mingzhu, WANG Wendong, ZHANG Zhichao. Study on construction risk factors based on ISM and MICMAC[J]. Journal of Safety and Environment, 2022, 22(1): 22-28.

周红波, 杨奇, 杨振国, 等. 基于复杂网络和N-K模型的塔吊安全风险因素分析与控制[J]. 安全与环境学报, 2020, 20(3): 816-823.

ZHOU Hongbo, YANG Qi, YANG Zhenguo, et al. Analysis of the risk involved factors and safety control of the tower crane based on the complex network and N-K model[J]. Journal of Safety and Environment, 2020, 20(3): 816-823.

李瑚均, 陈辉华, 曾晓叶, 等. 建筑工程施工安全氛围的因子结构模型: 基于长沙建筑市场的调查[J]. 铁道科学与工程学报, 2021, 18(7): 1935-1942.

LI Hujun, CHEN Huihua, ZENG Xiaoye, et al. Determining the factor structure of construction safety climate in building engineering: a case study in Changsha[J]. Journal of Railway Science and Engineering, 2021, 18(7): 1935-1942.

LIN Songshun, ZHANG Ning, ZHOU Annan, et al. Risk evaluation of excavation based on fuzzy decision-making model[J]. Automation in Construction, 2022, 136: 104143.

XU Na, MA Ling, LIU Qing, et al. An improved text mining approach to extract safety risk factors from construction accident reports[J]. Safety Science, 2021, 138: 105216.

刘辉, 郑向莞, 张智超, 等. 定量改进JHA法的建筑施工高危作业风险分析[J]. 中国安全科学学报, 2019, 29(4): 146-151.

LIU Hui, ZHENG Xiangwan, ZHANG Zhichao, et al. Risk analysis of high-risk operations in construction by a quantitatively improved JHA method[J]. China Safety Science Journal, 2019, 29(4): 146-151.

HULME A, STANTON N A, WALKER G H, et al. What do applications of systems thinking accident analysis methods tell us about accident causation? a systematic review of applications between 1990 and 2018[J]. Safety Science, 2019, 117: 164-183.

张伟, 朱双娜, 张潇, 等. 建筑施工安全事故致因系统模型与实证分析[J]. 中国安全科学学报, 2019, 29(6): 56-62.

ZHANG Wei, ZHU Shuangna, ZHANG Xiao, et al. Systematic model of construction accident causation and its empirical analysis[J]. China Safety Science Journal, 2019, 29(6): 56-62.

HATEFI S M, TAMOŠAITIENĖ J. An integrated fuzzy dematel-fuzzy anp model for evaluating construction projects by considering interrelationships among risk factors[J]. Journal of Civil Engineering and Management, 2019, 25(2): 114-131.

中华人民共和国交通运输部. 公路工程施工安全技术规范: JTG F90—2015[S]. 北京: 人民交通出版社, 2015.

Ministry of Transport of the People’s Republic of China. Safety technical specifications for highway engineering construction: JTG F90—2015[S]. Beijing: China Communications Press, 2015.

中华人民共和国住房和城乡建设部. 建筑施工安全检查标准: JGJ 59—2011[S]. 北京: 中国建筑工业出版社, 2012.

Ministry of Housing and Urban-Rural Development of the People’s Republic of China. Standard of construction safety inspection: JGJ 59—2011[S]. Beijing: China Architecture & Building Press, 2012.

AZADEH A, ZARRIN M, ABDOLLAHI M, et al. Leanness assessment and optimization by fuzzy cognitive map and multivariate analysis[J]. Expert Systems with Applications, 2015, 42(15/16): 6050-6064.

BAKHTAVAR E, VALIPOUR M, YOUSEFI S, et al. Fuzzy cognitive maps in systems risk analysis: a comprehensive review[J]. Complex & Intelligent Systems, 2021, 7(2): 621-637.

CRONBACH L J. Coefficient alpha and the internal structure of tests[J]. Psychometrika, 1951, 16(3): 297-334.

TAHERDOOST H, SAHIBUDDIN S, JALALIYOON N. Exploratory factor analysis: concepts and theory[J]. Advances in Applied and Pure Mathematics, 2022, 27: 375-382.

AMMAD S, ALALOUL W S, SAAD S, et al. Personal protective equipment (PPE) usage in construction projects: a scientometric approach[J]. Journal of Building Engineering, 2021, 35: 102086.

DASANDARA S P M, DISSANAYAKE P. Limiting reasons for use of personal protective equipment among construction workers: case studies in Sri Lanka[J]. Safety Science, 2021, 143: 105440.

WONG T K M, MAN S S, CHAN A H S. Critical factors for the use or non-use of personal protective equipment amongst construction workers[J]. Safety Science, 2020, 126: 104663.

NAMIAN M, ALBERT A, ZULUAGA C M, et al. Role of safety training: impact on hazard recognition and safety risk perception[J]. Journal of Construction Engineering and Management, 2016, 142(12): 04016073.

WANG Chen, WANG Jiakun, WANG Xinhua, et al. Exploring the impacts of factors contributing to unsafe behavior of coal miners[J]. Safety Science, 2019, 115: 339-348.

FANG D, WU Chunlin, WU Haojie. Impact of the supervisor on worker safety behavior in construction projects[J]. Journal of Management in Engineering, 2015, 31: 04015001.

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