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All Journal International Journal of Mechanical, Industrial and Control Systems Engineering
Fayyadh Annas
Universitas Bina Bangsa
Computer Science & IT Engineering

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Analysis of Physical and Mental Load on Wheat Flour Production Operators Using %Cvl and Nasa-Tlx Methods Fayyadh Annas; Eka Lailita Eti Varina; Resti Yuliana
International Journal of Mechanical, Industrial and Control Systems Engineering Vol. 3 No. 3 (2026): September :IJMICSE: International Journal of Mechanical, Industrial and Control
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/ijmicse.v3i3.486

Abstract

The wheat flour processing industry involves production activities that require operators to maintain physical and mental conditions throughout the work process. Operators in the milling and mixing sections perform prolonged standing, machine monitoring, material handling, production target achievement, and work in hot, noisy, and dusty environments. This study aimed to analyze physical and mental workload, compare both workloads, and formulate improvement recommendations for wheat flour production operators. A descriptive quantitative approach was applied using the Cardiovascular Load (%CVL) and NASA-Task Load Index (NASA-TLX) methods. The sample consisted of 30 milling and mixing operators selected using total sampling. %CVL data were obtained by measuring heart rate using a pulse oximeter, while mental workload was assessed using the NASA-TLX questionnaire. The results showed an average %CVL of 21%, with 24 operators (80%) classified as having a low workload and 6 operators (20%) requiring improvement. Meanwhile, the average NASA-TLX score was 79.7, with 14 operators (46.7%) classified as having a high workload and 15 operators (50%) as very high. Mental workload was primarily influenced by Physical Demand, Effort, and Temporal Demand. The findings indicate a discrepancy between physiological responses and perceived workload. Improvements can be achieved through periodic evaluations, task allocation optimization, effective rest periods, and training.
Co-Authors Eti Varina, Eka Lailita Resti Yuliana