INTEGRATING OBJECTIVE AND SUBJECTIVE WORKLOAD ASSESSMENT

IN ERGONOMIC JOB ROTATION DESIGN: A CONCEPTUAL FRAMEWORK

DOWNLOAD DOI: 10.62897/COS2025.3-1.100

Tilen Medved*, Zvone Balantič
*University of Maribor, Faculty of Organizational Sciences, Kidričeva 55A, Kranj,
Slovenia
tilen.medved2@um.si


Abstract: Job rotation is widely used to reduce physical workload, but rotation plans often fail when they consider only objective exposure or only perceived workload. Effective rotation design requires a consistent representation of workload that combines both physical and subjective aspects of work. This paper presents a conceptual framework for the design of ergonomic job rotation based on the integration of objective and subjective workload assessment. Objective workload is obtained using wearable inertial sensors and evaluated with the Ovako Working Posture Analysing System (OWAS), while subjective workload is assessed using the NASA Task Load Index (NASA-TLX). The main contribution of the paper is a structured research framework that defines the planned experimental procedure for developing and validating a job rotation model. The framework includes workload measurement, integration of indicators, design of rotation scenarios, simulation of alternative schedules, and experimental validation in a controlled environment. The paper does not present empirical results, but outlines the methodological basis for later simulation and optimization of rotation schedules. The proposed approach aims to support more transparent and data-based job rotation design and to improve workload balance between workers.1. Introduction: topic of PhD study


 

REFERENCES

  • Alenjareghi M.J., Sekkay F., Dadouchi C., Keivanpour S., 2026, Wearable sensors in Industry 4.0: Preventing
    work-related musculoskeletal disorders. Sensors International, 7, 100343.
  • Asensio-Cuesta S., Diego-Mas J.A., Canós-Darós L., Andrés-Romano C., 2012a, A genetic algorithm for the
    design of job rotation schedules considering ergonomic and competence criteria. International Journal
    of Advanced Manufacturing Technology, 60, 1161–1174.
  • Asensio-Cuesta S., Diego-Mas J.A., Cremades-Oliver L.V., González-Cruz M.C., 2012b, A method to design
    job rotation schedules to prevent work-related musculoskeletal disorders in repetitive work. International
    Journal of Production Research, 50(24), 7467–7478.
  • Asensio-Cuesta S., García-Gómez J.M., Poza-Luján J.-L., Conejero J.A., 2019, A game-theory method to
    design job rotation schedules to prevent musculoskeletal disorders based on workers’ preferences and
    competencies. International Journal of Environmental Research and Public Health, 16(23), 4666.
  • Baklouti S., Chaker A., Rezgui T., Sahbani A., Bennour S., Laribi M.A., 2024, A novel IMU-based system for
    work-related musculoskeletal disorders risk assessment. Sensors, 24(11), 3419, DOI: 10.3390/s24113419.
  • Carnahan B.J., Redfern M.S., Norman B., 2000, Designing safe job rotation schedules using optimization
    and heuristic search. Ergonomics, 43(4), 543–560, DOI: 10.1080/001401300184404.
  • Dhengre S., Rothrock L., 2025, Investigating mental workload across task modalities: a multimodal
    analysis using pupillometry. Ergonomics, 68(9), 1458–1471, DOI: 10.1080/00140139.2024.2414203.
  • García-Luna M.A., Ruiz-Fernández D., Tortosa-Martínez J., Manchado C., García-Jaén M., Cortell-Tormo
    J.M., 2024, Transparency as a means to analyse the impact of inertial sensors on users during the
    occupational ergonomic assessment: A systematic review. Sensors, 24(1), 298, DOI: 10.3390/s24010298.
  • Hart S.G., Staveland L.E., 1988, Development of NASA-TLX (Task Load Index): Results of empirical and
    theoretical research. In: Advances in Psychology, 52, 139–183, Elsevier.
  • Hertzum M., 2021, Reference values and subscale patterns for the task load index (TLX): a meta-analytic
    review. Ergonomics, 64(7), 869–878.
  • Inegbedion H., Inegbedion E., Peter A., Harry L., 2020, Perception of workload balance and employee job
    satisfaction in work organisations. Heliyon, 6(1), e03160.
  • Karwowski W., 2005, Ergonomics and human factors: the paradigms for science, engineering, design,
    technology and management of human-compatible systems. Ergonomics, 48(5), 436–463, DOI:
    10.1080/00140130400029167.
  • Mathiassen S.E., 2006, Diversity and variation in biomechanical exposure: what is it, and why would we
    like to know? Applied Ergonomics, 37(4), 419–427.
  • Mehdizadeh A., Vinel A., Hu Q., Schall M.C. Jr, Gallagher S., Sesek R.F., 2020, Job rotation and work-related
    musculoskeletal disorders: a fatigue-failure perspective. Ergonomics, 63(4), 461–476.
  • Miyake S., 2001, Multivariate workload evaluation combining physiological and subjective measures.
    International Journal of Psychophysiology, 40(3), 233–238.
  • Mlekus L., Maier G.W., 2021, More hype than substance? A meta-analysis on job and task rotation.
    Frontiers in Psychology, 12, 633530.
  • Otto A., Battaïa O., 2017, Reducing physical ergonomic risks at assembly lines by line balancing and job
    rotation: A survey. Computers & Industrial Engineering, 111, 467–480, DOI: 10.1016/j.cie.2017.04.011.
  • Padula R.S., Comper M.L.C., Sparer E.H., Dennerlein J.T., 2017, Job rotation designed to prevent
    musculoskeletal disorders and control risk in manufacturing industries: A systematic review. Applied
    Ergonomics, 58, 386–397.
  • Schall M.C. Jr, Chen H., Cavuoto L., 2022, Wearable inertial sensors for objective kinematic assessments:
    A brief overview. Journal of Occupational and Environmental Hygiene, 19(9), 501–508.
  • Wahyudi M.A., Dania W.A.P., Silalahi R.L.R., 2015, Work posture analysis of manual material handling
    using OWAS method. Agriculture and Agricultural Science Procedia, 3, 195–199.

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