基于MMEM-PDCA融合视角的高校体育实验室安全风险识别与过程化治理研究

Safety Risk Identification and Process-Oriented Governance in University Sports Laboratories: An Integrated MMEM-PDCA Perspective

摘要: 高校体育实验室兼具人体运动测试、精密仪器操作、运动器械使用和开放性教学科研空间等特征，其安全风险与传统理工类实验室相比具有明显的场景差异。针对当前高校体育实验室安全管理中存在的人员准入粗放、设备维护滞后、环境风险识别不足和治理流程缺乏闭环等问题，本文基于“人–机–环境–管理”(MMEM)理论和“计划–执行–检查–改进”(PDCA)循环，构建高校体育实验室安全风险识别与闭环治理框架。研究从人员行为、运动测试设备、实验空间环境和管理制度四个维度分析体育实验室安全风险，并将PDCA循环嵌入风险清单建立、分级管控、整改跟踪和持续改进过程之中，形成面向体育实验室场景的安全管理路径。本文认为，MMEM-PDCA融合框架能够为高校体育实验室安全管理提供系统化分析思路和过程化治理方法，但其实际应用效果仍需结合具体案例和数据进一步验证。

Abstract: University sports laboratories are characterized by human performance testing, the operation of precision instruments, the use of exercise equipment, and open-access teaching and research spaces. Consequently, their safety risks exhibit distinct context-specific features compared with those of conventional science and engineering laboratories. To address existing problems in safety management, including insufficiently differentiated personnel access control, delayed equipment maintenance, inadequate identification of environmental hazards, and the absence of closed-loop governance processes, this study develops a framework for safety risk identification and closed-loop governance in university sports laboratories based on the Man-Machine-Environment-Management (MMEM) theory and the Plan-Do-Check-Act (PDCA) cycle. Safety risks are examined across four dimensions: human behavior, exercise testing equipment, the laboratory spatial environment, and management systems. The PDCA cycle is then embedded into the processes of risk register development, tiered risk control, corrective-action tracking, and continuous improvement, thereby establishing a context-specific safety management approach for university sports laboratories. This study argues that the integrated MMEM-PDCA framework provides a systematic analytical perspective and a process-oriented governance approach for safety management in university sports laboratories. However, its practical effectiveness requires further validation through empirical data and case-based applications.