基于新的决策方法进行风险评估,使用固定的模糊集
1Industrial Engineering, Yildiz Technical University, Istanbul, Turkey.
PeerJ. Computer science
|September 24, 2025
概括
本研究引入了一种灵活的分决策组方法,用于多个标准的决策,通过新参数 (如人类和机器错误) 增强风险评估. 调查结果强调安全措施对于有效的风险管理至关重要.
科学领域:
- 决策科学 决策科学
- 风险管理 风险管理
- 工业工程 工业工程 工业工程
背景情况:
- 引入了一种新的分决策组 (SDMG) 方法,用于多标准决策 (MCDM).
- 与现有方法相比,SDMG方法提供了更灵活和更动态的结构.
- 提高决策者在复杂决策过程中的专业知识和知识的有效利用.
研究的目的:
- 开发和应用一个创新的决策模型,用于塑料注塑机的风险评估.
- 将新的风险参数,包括人为错误,机器错误和现有的安全措施纳入评估过程.
- 提供一个更全面,更有效的风险评估方法.
主要方法:
- 在间隔值的费尔马特模糊集 (IVFFS) 环境中,整合分析层次过程 (AHP) 和以类似于理想解决方案的顺序偏好技术 (TOPSIS).
- 使用IVFF-AHP来权衡风险参数和确定危险分数.
- 采用TOPSIS来对已识别的危险进行排名,所有方法都模拟在MATLAB_R2024a中.
主要成果:
- 确定了决策过程中每个标准的分别确定决策者的适用性.
- 确定"现有安全措施"是最关键的风险参数,其次是机器和人为错误.
- 确定电力,窒息/有毒气体和热水使用是风险最高的危害,经过灵敏度分析验证.
结论:
- 拟议的SDMG方法,结合了新的风险参数,比传统的风险评估方法提供了显著的优势.
- IVFFS,AHP和TOPSIS的整合为管理风险和不确定性提供了一个强大的框架.
- 该方法产生了一致和合理的结果,证实了其在实际风险评估场景中的有效性.
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