2016
DOI: 10.1016/j.ifacol.2016.07.642
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Reducing production cycle time by ergonomic workforce scheduling

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Cited by 16 publications
(9 citation statements)
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“…These studies generally tested their models with random data (Boenzi et al, 2015; Digiesi et al, 2018; Moussavi et al, 2016; Nanthavanij et al, 2010; Yaoyuenyong & Nanthavanij, 2008). However, our paper uses both real‐world data and random data to test the developed models.…”
Section: Discussionmentioning
confidence: 99%
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“…These studies generally tested their models with random data (Boenzi et al, 2015; Digiesi et al, 2018; Moussavi et al, 2016; Nanthavanij et al, 2010; Yaoyuenyong & Nanthavanij, 2008). However, our paper uses both real‐world data and random data to test the developed models.…”
Section: Discussionmentioning
confidence: 99%
“…There are some studies which focus on ergonomic issues in arranging manufacturing operations in the literature. In previous studies on this topic, some researchers have taken into account repetitive actions in assembly‐line balancing by employing the Occupational Repetitive Actions index (Baykasoglu et al, 2017; Moussavi et al, 2016; Sana et al, 2019), whereas others considered the working position in assigning workers to jobs by adopting rapid upper limb assessment (RULA) or rapid entire body assessment (REBA) (Digiesi et al, 2018; Yoon et al, 2016). To the best of our knowledge, there is no published paper that integrates HAV into job rotation schedules in manufacturing companies.…”
Section: Literature Reviewmentioning
confidence: 99%
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“…Song et al [5] presented a job rotation algorithm that minimizes musculoskeletal disorders with decreasing the overall workload. Moussavi, et al [6] developed a rotation program that considers ergonomic risks for a planning period. Yoon, et al [7] proposed a job rotation schedule by using a mathematical model that reduces cumulative workload of the same body region.…”
Section: Introductionmentioning
confidence: 99%
“…The production cycle time reduction by ergonomic workforce scheduling was considered by Moussavi et al, (2016). The coefficient was found in the criteria of the consistence between the employee and bench, height, age, experience and capability.…”
mentioning
confidence: 99%