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Considering workers’ features in manufacturing systems: a new job-rotation scheduling model

机译:考虑制造系统中的工人功能:一个新的工作旋转调度模型

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The European manufacturing industry is entering a new era in which working populations are ageing. The E.U. had set itself strategy objectives to increase the labour market participation of older workers. However, practical limits arise, and a complete re-thinking of operation management strategies and manufacturing systems design and management is needed. As underlined in several works, older workers have not the same physical capacity as the younger ones. Consequently, they are more subjected to develop work-related musculoskeletal disorders despite younger colleagues. On the other hand, they might present higher skill levels in doing some specific tasks due to their considerable experience. Thus, they can be employed in teaching or training younger or unskilled workers. Starting from these initial considerations, in this paper, we develop a new age-oriented job rotation scheduling model. Both physical capacity and experience level aspects are included in the mathematical model aiming to maximize daily productivity. We quantify physical fatigue by using the energy expenditure rate and the maximum acceptable energy expenditure. Then, the rest allowance concept is evaluated according to the workers’ age and the shift work duration. Variable execution times of each job according to the workers’ experience level and mandatory training activities for unskilled workers are also taken into consideration. Finally, a numerical case derived by a real application is proposed to validate the model and demonstrate benefits we can achieve by applying it.
机译:欧洲制造业正在进入一个新的时代,其中工作人群正在老化。 E.U.已经设定了自己的战略目标,以提高老年工人的劳动力市场参与。但是,出现了实际限制,需要完全重新思考操作管理策略和制造系统设计和管理。如在几种作品中强调,老年工人与年轻人没有相同的身体容量。因此,尽管年轻的同事,他们更受培养与工作相关的肌肉骨骼疾病。另一方面,由于其相当大的经验,它们可能在做一些具体任务方面提高技能水平。因此,它们可以在教学或培训年轻或不熟练的工人方面使用。从这些初步考虑开始,在本文中,我们开发了一种新的面向时期的作业旋转调度模型。物理能力和体验级别方面都包含在旨在最大限度地提高日常生产率的数学模型中。我们通过使用能源支出率和最大可接受的能源支出来量化物理疲劳。然后,根据工人年龄和换档工作持续时间评估其余津贴概念。还考虑了根据工人经验水平和强制性培训活动的每项工作的可变执行时间。最后,提出了一种由真实应用程序导出的数值案例来验证模型,并展示我们通过应用它可以实现的效益。

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