Department of Industrial Engineering, Iran University of Science & Technology, Iran.
Department of Civil Engineering, Iran University of Science & Technology, Iran.
Int J Occup Saf Ergon. 2023 Sep;29(3):1182-1195. doi: 10.1080/10803548.2022.2115227. Epub 2022 Sep 26.
Numerous labourers lose their lives or suffer from injuries and disabilities yearly due to the lack of safety enforcement in construction projects and accidents caused by excavation collapses. The identification and ranking of human errors have always been a central concern in civil engineering. Previous studies on excavation work and related risks have focused on retaining structure methods, while human errors may be a significant contributor to accidents and near misses. This study identified human errors in deep excavation projects using hierarchical task analysis (HTA) and a systematic human error reduction and prediction approach (SHERPA). The fuzzy Bayesian human error assessment and reduction technique (HEART)-5M method was implemented to determine the human error probability (HEP) for all case-study tasks. Critical tasks were obtained as 'drainage system execution', 'water and wastewater pipes', 'gas pipes', 'checking cracks in surrounding buildings' and 'checking soil slippage' with probability levels of 0.46, 0.44, 0.44, 0.37 and 0.37, respectively. Finally, remedial measures were presented for crucial tasks. Six unbiased experts approved the model's desirability. The suggested approach can serve as a valuable guide for all project stakeholders in identifying, evaluating and taking corrective actions in similar projects.
由于建筑项目安全执法不力以及挖掘坍塌导致的事故,每年都有大量工人失去生命或受伤致残。在土木工程中,识别和对人为错误进行排序一直是关注的重点。以前的关于挖掘工作和相关风险的研究主要集中在支护结构方法上,而人为错误可能是事故和险兆事件的一个重要原因。本研究使用层次任务分析(HTA)和系统人为失误减少和预测方法(SHERPA)对深基坑工程中的人为错误进行了识别和排序。采用模糊贝叶斯人为失误评估和减少技术(HEART)-5M 方法确定所有案例研究任务的人为失误概率(HEP)。关键任务分别为“排水系统执行”、“水和污水管道”、“煤气管道”、“检查周围建筑物裂缝”和“检查土壤滑移”,概率水平分别为 0.46、0.44、0.44、0.37 和 0.37。最后,针对关键任务提出了补救措施。六位无偏见的专家认可了该模型的可取性。该方法可以为所有项目利益相关者在类似项目中识别、评估和采取纠正措施提供有价值的指导。