Product Design, Manufacturing & Innovation Resources

提升-移动-模型(LMM)

提升-移动-模型

提升-移动-模型(LMM)

目标

与体力搬运任务相关的肌肉骨骼疾病风险评估模型。.

如何使用

优点

缺点

类别

最适合:

The Lifting-Moving-Model (LMM) methodology serves as a valuable tool for industries where manual handling of objects is prevalent, such as warehousing, construction, healthcare, and manufacturing. It is particularly beneficial during the design and assessment phases of task workflows, where ergonomic evaluations can significantly influence modifications that enhance worker safety and productivity. Participants in this process may include ergonomists, safety engineers, production managers, and occupational health specialists who collectively analyze lifting and moving tasks to identify risks associated with musculoskeletal disorders. The methodology encourages data collection on various factors, including load weight, duration of task exposure, and worker posture, enabling quantitative risk assessments that allow organizations to prioritize interventions effectively. LMM can be applied not only for evaluating existing tasks but also when designing new operations or workstations, ensuring that ergonomics is integrated from the beginning of the design process. This results in lowered injury rates, improved compliance with safety regulations, and can lead to potential cost savings by reducing workers’ compensation claims and increasing overall efficiency. Industries adopting LMM can benefit from its comparative risk analysis capabilities, allowing them to evaluate and improve the ergonomics of multiple tasks systematically.

该方法的关键步骤

  1. 确定和定义需要评估的提升和移动任务。.
  2. 确定提升或移动物体的重量。.
  3. 测量升降或移动的水平和垂直距离。.
  4. 评估工人在工作中的姿势,注意关节的角度。.
  5. 评估提升或移动任务的频率和持续时间。.
  6. 使用既定公式计算 "提升-移动-模型 "风险分值。.
  7. 根据计算出的风险分数对任务进行排序,以确定优先次序。.

专业提示

  • 采用实时监控技术,例如 可穿戴 传感器,捕捉起重机械和工人姿势的动态数据,提高 LMM 应用的精确度。.
  • 使用 LMM 进行敏感性分析,以确定哪些变量对风险结果的影响最大,并针对这些变量采取有效的人体工程学干预措施。.
  • Leverage comparative 风险评估 by applying LMM to historical task data, enabling prioritization of high-risk tasks for redesign or training interventions.

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