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Mental Workload Assessment in Construction Industry with Fuzzy NASA-TLX Method

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Proceedings of the Sixteenth International Conference on Management Science and Engineering Management – Volume 2 (ICMSEM 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 145))

Abstract

The construction industry is a sector where human resources are used intensively, and work accidents related to falling from height occur mostly. In the construction industry, studies are generally carried out to determine and prevent the physical workload of the work done. However, it is necessary to measure mental workload and make improvements to keep this workload at an optimum level to prevent work accidents and performance losses. In literature, NASA-TLX (National Aeronautics and Space Administration Task Load Index) method is widely used to evaluate the mental workload of workers. Uncertainty arises in the calculation process of NASA-TLX since this method is subjective, and the rating values of workload dimensions included are expressed in linguistic terms. For this reason, to eliminate uncertainties and obtain more accurate results, fuzzy set theory can be used. In this study, the Fuzzy NASA-TLX method is proposed to determine the mental workload of construction workers working at height in a construction site. In addition, to demonstrate the effectiveness of the proposed model and understand the effect of weights, the results of the proposed model are compared with the results of the Fuzzy NASA-RTLX (Raw Task Load Index) method in this study. According to the results of Fuzzy NASA-TLX and Fuzzy NASA-RTLX, the levels of overall mental workloads are 0.624 (62.4%) and 0.612 (61.2%), respectively. Besides, the most important workload dimension for the workers working at height is temporal demand in both models. It is determined that this study will contribute to reducing work accidents that result from the excessive mental workload and protecting workers’ health.

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Faculty of Engineering, Gazi University, Ankara, Turkey

    Ezgi Aktas Potur & Mehmet Kabak

  2. Department of Industrial Engineering, Faculty of Engineering, Eskisehir Technical University, Eskisehir, Turkey

    Şura Toptancı

Authors
  1. Ezgi Aktas Potur
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  2. Şura Toptancı
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  3. Mehmet Kabak
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Corresponding author

Correspondence to Ezgi Aktas Potur .

Editor information

Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, Sichuan, China

    Jiuping Xu

  2. Department of Industrial Engineering, Gazi University, Faculty of Engineering, Ankara, Turkey

    Fulya Altiparmak

  3. School of Mathematical Sciences, University of Khartoum, Khartoum, Sudan

    Mohamed Hag Ali Hassan

  4. University of Castilla-La Mancha (UCLM), Ciudad Real, Spain

    Fausto Pedro García Márquez

  5. Institute of Control Systems, Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Asaf Hajiyev

Appendix

Appendix

See Table 4.

Table 4. The results of adjusted ratings and weighted and unweighted workloads
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Aktas Potur, E., Toptancı, Ş., Kabak, M. (2022). Mental Workload Assessment in Construction Industry with Fuzzy NASA-TLX Method. In: Xu, J., Altiparmak, F., Hassan, M.H.A., García Márquez, F.P., Hajiyev, A. (eds) Proceedings of the Sixteenth International Conference on Management Science and Engineering Management – Volume 2. ICMSEM 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 145. Springer, Cham. https://doi.org/10.1007/978-3-031-10385-8_52

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