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基于工人偏好和能力的防止肌肉骨骼疾病的工作轮换计划设计的博弈论方法。

A Game-Theory Method to Design Job Rotation Schedules to Prevent Musculoskeletal Disorders Based on Workers' Preferences and Competencies.

机构信息

Instituto de Tecnologías de la Información y Comunicaciones (ITACA), Universitat Politècnica de València, Camino de Vera s/n, 46022 València, Spain.

Instituto Universitario de Áutomática e Informática Industrial, Universitat Politècnica de València, Camino de Vera s/n, 46022 València, Spain.

出版信息

Int J Environ Res Public Health. 2019 Nov 22;16(23):4666. doi: 10.3390/ijerph16234666.

DOI:10.3390/ijerph16234666
PMID:31771124
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6926966/
Abstract

Job rotation is an organizational strategy based on the systematic exchange of workers between jobs in a planned manner according to specific criteria. This study presents the GS-Rot method, a method based on Game Theory, in order to design job rotation schedules by considering not only workers' job preferences, but also the competencies required for different jobs. With this approach, we promote workers' active participation in the design of the rotation plan. It also let us deal with restrictions in assigning workers to job positions according to their disabilities (temporal or permanent). The GS-Rot method has been implemented online and applied to a case in a work environment characterized by the presence of a high repetition of movements, which is a significant risk factor associated with work-related musculoskeletal disorders (WMSDs). A total of 17 workstations and 17 workers were involved in the rotation, four of them with physical/psychological limitations. Feasible job rotation schedules were obtained in a short time (average time 27.4 milliseconds). The results indicate that in the rotations driven by preference priorities, almost all the workers (94.11%) were assigned to one of their top five preferences. Likewise, 48.52% of job positions were assigned to workers in their top five of their competence lists. When jobs were assigned according to competence, 58.82% of workers got an assignment among their top five competence lists. Furthermore, 55.87% of the workers achieved jobs in their top five preferences. In both rotation scenarios, the workers varied performed jobs, and fatigue accumulation was balanced among them. The GS-Rot method achieved feasible and uniform solutions regarding the workers' exposure to job repetitiveness.

摘要

工作轮换是一种组织策略,它根据特定标准有计划地在工作之间系统地交换工人。本研究提出了 GS-Rot 方法,这是一种基于博弈论的方法,旨在设计工作轮换计划,不仅要考虑工人的工作偏好,还要考虑不同工作所需的能力。通过这种方法,我们促进了工人积极参与轮换计划的设计。它还使我们能够根据工人的残疾(暂时或永久)来处理将工人分配到工作岗位的限制。GS-Rot 方法已经在线实施,并应用于一个工作环境中的案例,该环境的特点是动作高度重复,这是与工作相关的肌肉骨骼疾病(WMSD)相关的一个重要风险因素。共有 17 个工作站和 17 名工人参与了轮换,其中 4 人有身体/心理障碍。在短时间内(平均时间 27.4 毫秒)获得了可行的工作轮换计划。结果表明,在基于偏好优先级的轮换中,几乎所有工人(94.11%)都被分配到他们的前五名偏好之一。同样,48.52%的工作岗位被分配给了能力列表中排名前五的工人。当根据能力分配工作时,58.82%的工人在他们的前五名能力列表中得到了分配。此外,55.87%的工人获得了他们前五名偏好中的工作。在这两种轮换方案中,工人都轮流执行不同的工作,并且他们之间的疲劳积累得到了平衡。GS-Rot 方法在工人对工作重复性的暴露方面实现了可行且统一的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/cd7cd23ec5a7/ijerph-16-04666-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/d6e43f14fbcc/ijerph-16-04666-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/e275bfb6e386/ijerph-16-04666-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/cc516e35f25b/ijerph-16-04666-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/598902c1b0c3/ijerph-16-04666-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/2fadeaf50cee/ijerph-16-04666-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/abe1053e3d77/ijerph-16-04666-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/2f6fc0bd3d94/ijerph-16-04666-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/243c2cfbd4f5/ijerph-16-04666-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/cd7cd23ec5a7/ijerph-16-04666-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/d6e43f14fbcc/ijerph-16-04666-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/e275bfb6e386/ijerph-16-04666-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/cc516e35f25b/ijerph-16-04666-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/598902c1b0c3/ijerph-16-04666-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/2fadeaf50cee/ijerph-16-04666-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/abe1053e3d77/ijerph-16-04666-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/2f6fc0bd3d94/ijerph-16-04666-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/243c2cfbd4f5/ijerph-16-04666-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e1df/6926966/cd7cd23ec5a7/ijerph-16-04666-g009.jpg

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