地铁列车检修任务优化设计策略研究

Optimization Design Strategy of Subway Train Maintenance Tasks

中文关键词: 地铁列车  检修任务  人-机-环境  压力应对  检修人员

英文关键词: subway train  maintenance tasks  man-machine-environment  stress response  maintenance personnel

中文摘要:

      目的 为优化我国城市地铁列车检修作业过程，降低检修人员压力，对我国地铁列车检修人员的工作环境与作业状况进行研究并提出优化设计策略。方法 分析“人-机-环境”系统中的检修任务及其操作过程，进而发现问题并探索优化方法。通过实地调研与收集相关文献、检修修程，推导构建人(列车检修人员)-机(待检列车、工具/设备)-环境(检修环境及其影响)的检修系统模型，以此探讨和找到检修任务中检修人员压力的来源，并结合应对压力的心理学理论，整理归纳出压力源改造、压力反应优化、支持或辅助三类策略。结果 从检修人员角度出发，建议可从人机适配、交互逻辑、认知辅助三条途径，对列车检修任务实施设计优化。结论 运用系统性分析探索现有列车检修系统下检修人员的压力来源，然后借助压力应对策略与优化途径，可以有效辅助提升列车检修人员工作质量。

英文摘要:

      In order to optimize the maintenance process of urban subway trains in China and reduce the stress of maintenance personnel, the work aims to study the working environment and working condition of subway train maintenance personnel in China and put forward the optimization design strategy. The maintenance task and operation process in man-machine-environment system were analyzed, and then the problems were found and the optimization methods were explored. Through field investigation and collection of relevant literature and maintenance process, the maintenance system model of man (train maintenance personnel) - machine (train to be inspected, tools/equipment) - environment (maintenance environment and its impact) was deduced and constructed, so as to explore and find the stress source of maintenance personnel stress during maintenance tasks. Combined with psychological theories of coping with stress, three strategies for managing stress were summarized, including remould stressors, stress response optimization, support or assistance. From the perspective of maintenance personnel, it was suggested that design optimization of train maintenance tasks could be implemented in three ways such as human-machine adaptation, interactive logic and Cognitive aid. The work quality of train maintenance personnel can be effectively improved by conducting systematic analysis to explore the sources of stress for maintenance personnel under the existing train maintenance system and utilizing stress response strategies and optimization approaches.