Physical Workload Analysis in Processing Operations: Metal Processing Manufacturing

Roja, Zenija; Kalkis, Henrijs; Babris, Sandis; Roja, Inara; Bokse, Kristine; Ventins, Ansis

doi:10.1007/978-3-030-20142-5_2

Cited by 2 publications

(3 citation statements)

References 10 publications

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“…The fact that the top three workers with the highest PWL were in the same department indicated that the results produced by the proposed approach were also logical. In the literature, it is indicated that if workers are subjected to heavy manual work and load on muscles, they perceive a higher PWL and have a higher risk of developing work-related musculoskeletal disorders (Roja et al, 2019). Another study in the literature shows that, as the frequency of manual work activities with awkward postures increases, workers are more likely to become tired early and develop occupational musculoskeletal disorders (Sekkay et al, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…Åkerstedt et al (2019) investigated whether psychosocial work demands and PWL changed within an 8-year aging period, whether occupational groups showed different change developments, and if these changes were reflected in sleeping patterns or fatigue. Roja et al (2019) performed PWL evaluation in the metalprocessing industry for assembly operators, packaging operators, and inspection staff considering heart rate and muscle fatigue. Manjarres et al (2020) addressed workload computation by integrating human activity recognition and heart rate measurements to establish a scalable framework for health at work and fitness-related applications using two wearable sensors, one tracking motion, and another measuring heart rate.…”

Section: Literature Reviewmentioning

confidence: 99%

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A novel aggregated multiple criteria decision‐making approach to evaluate the physical workload of workers

Ekinci

Can

2021

Hum Ftrs & Erg Mfg Svc

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Physical workload (PWL) is a measure of the physical resources consumed by a worker while performing a task. Analyzing the PWL of workers can aid experts in identifying workers whose working conditions should be improved. Identifying workers who are exposed to the highest PWL is essential for task continuity and occupational health. In this study, a new approach is proposed to prioritize workers according to their PWL levels. In the proposed approach, multiple criteria decisionmaking techniques are used because different factors can affect PWL levels. Eight criteria, that is, standard time, frequency of working posture, heart rate, the risk level of posture, noise level, lighting intensity, rest period, and perceived workload level are considered. In the evaluation process, criteria weights are computed using entropy considering measurements of the eight criteria for each worker. Using

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Section: Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A novel aggregated multiple criteria decision‐making approach to evaluate the physical workload of workers

Ekinci

Can

2021

Hum Ftrs & Erg Mfg Svc

View full text Add to dashboard Cite

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“…Physiological criteria are often used to evaluate physical workloads are energy consumption (EE) during the load application and oxygen [18]. During medium physical activities, there is a linear correlation between HR and oxygen consumption [19]; therefore, oxygen consumption and HR are often used to measure physical [20].…”

Section: Physical Workloadmentioning

confidence: 99%

Predicting Human Reliability based on Individual’s Resting Period: Effect of Physical Workload Rate

Wahyuning

Atiko

2022

J. Optimasi Sist. Ind.

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When a person is exposed to a prolonged workload, he/she enters a fatigue phase, the indication is the decline of cognitive performance that leading to human error. As an integral part of a system, human contributes to system reliability; therefore, it plays an important role in potential failure. Those, it is necessary to investigate how human reliability relates to physical workload rate, in order to predict maximum work duration to eliminate potential failure. A physical experiment involving 20 participants was conducted to generate medium workload, followed by Stroop test to observe selective attention and cognitive control as a form of cognitive performance. The physical workload was observed through energy expenditure and oxygen consumption during physical activity, and cognitive performance through response error time on the Stroop test. The usage of Weibull distribution was aimed to obtain reliabilities for each participant. There was a decline in reliability for all participants from one test to the other. Based on scale and form parameters, the prediction of resting time was based on mean time to human error (MTTHE), and from this experiment, varied MTTHE from each participant were obtained. The variation was created by differences in physical performance, cognitive capabilities, and other contributing factors such as environment and time of the implementation of the experiment. From this research, it was evident that human reliability can be utilized to predict potential failure in humans, which then implies a preventive action is necessitated to prevent failure from manifesting in the shape of taking a break/rest or reducing work rhythm. The application of human reliability in human resource management can be directed towards fatigue management and operator-related operational management.

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Physical Workload Analysis in Processing Operations: Metal Processing Manufacturing

Cited by 2 publications

References 10 publications

A novel aggregated multiple criteria decision‐making approach to evaluate the physical workload of workers

A novel aggregated multiple criteria decision‐making approach to evaluate the physical workload of workers

Predicting Human Reliability based on Individual’s Resting Period: Effect of Physical Workload Rate

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