Evaluation of Fatigue and Workload among Workers Conducting Complex Manual Assembly in Manufacturing

Torres, Yaniel; Nadeau, Sylvie; Landau, Kurt

doi:10.1080/24725838.2021.1997835

Cited by 5 publications

(4 citation statements)

References 77 publications

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“…Most previous studies have only demonstrated the relationship between sleep and fatigue ( 47 , 48 ), or fatigue and mental workload ( 42 , 49 ), or sleep and mental workload ( 31 , 50 ). A recent study ( 51 ) investigated the fatigue, sleep and mental workload of shift night workers. But it still just addressed the relationship between fatigue and mental workload instead of all the three.…”

Section: Discussionmentioning

confidence: 99%

Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study

et al. 2022

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BackgroundA better understanding of the factors and their correlation with clinical first-line nurses’ sleep, fatigue and mental workload is of great significance to personnel scheduling strategies and rapid responses to anti-pandemic tasks in the post-COVID-19 pandemic era.ObjectiveThis multicenter and cross-sectional study aimed to investigate the nurses’ sleep, fatigue and mental workload and contributing factors to each, and to determine the correlation among them.MethodsA total of 1,004 eligible nurses (46 males, 958 females) from three tertiary hospitals participated in this cluster sampling survey. The Questionnaire Star online tool was used to collect the sociodemographic and study target data: Sleep quality, fatigue, and mental workload. Multi-statistical methods were used for data analysis using SPSS 25.0 and Amos 21.0.ResultsThe average sleep quality score was 10.545 ± 3.399 (insomnia prevalence: 80.2%); the average fatigue score was 55.81 ± 10.405 (fatigue prevalence: 100%); and the weighted mental workload score was 56.772 ± 17.26. Poor sleep was associated with mental workload (r = 0.303, P < 0.05) and fatigue (r = 0.727, P < 0.01). Fatigue was associated with mental workload (r = 0.321, P < 0.05). COVID-19 has caused both fatigue and mental workload. As 49% of nurses claimed their mental workload has been severely affected by COVID-19, while it has done slight harm to 68.9% of nurses’ sleep quality.ConclusionIn the post-COVID-19 pandemic era, the high prevalence of sleep disorders and fatigue emphasizes the importance of paying enough attention to the mental health of nurses in first-class tertiary hospitals. Efficient nursing strategies should focus on the interaction of sleep, fatigue and mental workload in clinical nurses. In that case, further research on solutions to the phenomenon stated above proves to be of great significance and necessity.Clinical trial registration[https://clinicaltrials.gov/], identifier [ChiCTR2100053133].

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Section: Discussionmentioning

confidence: 99%

Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study

et al. 2022

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“…An evaluation of fatigue and workload among a group of 14 assemblers was done over a 2‐week period. It showed that high fatigue levels were reported in one‐third of the shifts evaluated (Torres et al, 2021b). The main predictors of high fatigue were workload estimates, working evening shifts, and baseline fatigue.…”

Section: Methodsmentioning

confidence: 99%

“…Various methods of data collection and analysis were employed: statistical analysis of quality data, field observations (systematic and walkthrough), nonstructured interviews with workers and other stakeholders, group discussions, search in the company records (quality data, assembly instructions, working times), questionnaires for the evaluation of perceived fatigue and workload, HRA for the identification and quantification of error modes and the use of a mathematical model to evaluate shiftwork practices. Results of the project can be found in scientific journal papers and conference chapters (Torres & Nadeau, 2020; Torres et al, 2021a, 2021b, 2021c). The institutional ethics committee approved all research interventions involving human participants.…”

Section: Methodsmentioning

confidence: 99%

“…This examination favors the collection of data in real settings (Yin, 2012). of the project can be found in scientific journal papers and conference chapters (Torres & Nadeau, 2020;Torres et al, 2021aTorres et al, , 2021bTorres et al, , 2021c. The institutional ethics committee approved all research interventions involving human participants.…”

Section: General Approachmentioning

confidence: 99%

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Applying AcciMap and STAMP to the analysis of human error in complex manual assembly

Torres

Nadeau

Landau

2022

Hum Ftrs & Erg Mfg Svc

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In sectors such as aerospace manufacturing, human errors in the assembly of complex products can negatively impact quality, productivity, and safety. Until now, the analysis of assembly errors has focused more on the immediate human‐system interface and less on broader organizational factors. This article presents a case study‐based analysis of assembly errors in the aeronautical industry using the systemic methods AcciMap and Systems‐Theoretic Accident Model and Processes (STAMP). We seek to provide the company with elements to build a quality improvement strategy that considers human factors and ergonomics from a systemic perspective. The data and information necessary to conduct the analysis came from a project carried out at an aerospace manufacturing facility over a period of 12 months. The team had direct and recurrent access to primary data sources and communication with various stakeholders. A total of 31 influencing factors were identified with AcciMap at different levels within the manufacturing system. STAMP made it possible to model the sociotechnical control structure of the assembly process and identify several control flaws leading to hazards. The analysis shows that systemic methods require a high level of understanding of the manufacturing system and access to relatively high amounts of data and information. Therefore, direct contact with the field and stakeholders is crucial. Training quality specialists on systemic methods could support its use and help to close the gap between theory and practice. Globally, the field of quality in manufacturing could benefit from using systemic methods when deemed necessary.

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A systematic review on digital human models in assembly process planning

Yin

2023

Int J Adv Manuf Technol

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Evaluation of Fatigue and Workload among Workers Conducting Complex Manual Assembly in Manufacturing

Cited by 5 publications

References 77 publications

Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study

Factoring and correlation in sleep, fatigue and mental workload of clinical first-line nurses in the post-pandemic era of COVID-19: A multi-center cross-sectional study

Applying AcciMap and STAMP to the analysis of human error in complex manual assembly

A systematic review on digital human models in assembly process planning

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