Occupational Risk Management for a Sustainable Workplace Using Simulation

Małgorzata Sławińska, Paweł Pawlewski, Izabela Kudelska, Daniel Kańduła

Abstract


Theoretical background: The article delves into the realm of occupational risk management within the context of supply chain management and enterprise logistics. It emphasizes the importance of ensuring safety and sustainable working conditions in today’s dynamic business environment, where supply chains are becoming increasingly globalized and complex.

Purpose of the article: The primary objective of the article is to introduce a novel approach to occupational risk management that leverages advanced digital technologies and simulations. It aims to address the existing research gap by developing a method that considers dynamic environmental factors and individual worker needs. By analyzing the synergy of various hazards, monitoring employee workload, and employing simulations, the article seeks to enhance the accuracy of occupational risk assessment and facilitate more effective corrective actions.

Research methods: The article employs a mixed-method research approach, drawing upon both theoretical analysis and practical application. It begins with a thorough literature review to establish the theoretical framework and identify research gaps. Subsequently, it discusses the proposed solution – a method for managing occupational risks using simulation – by presenting its theoretical description and implementation process. The research methodology involves the development and application of this method to a selected order picking process, followed by simulation to minimize occupational risks. The authors also utilize software tools to simulate work processes and assess health risks to workers.

Main findings: The main findings of the research suggest that occupational risk assessment using simulation has a significant impact on improving work processes in terms of sustainable workplaces. By introducing elements of labor humanization and redesigning work processes, the study demonstrates a reduction in the sources of occupational risk. The innovative approach to risk assessment, based on recursion across different organizational resources, facilitates the identification of improvement action projects. Additionally, the study emphasizes the importance of digitalization and Industry 4.0 technologies in monitoring working conditions, identifying risks, and implementing preventive measures. Overall, the research contributes to shaping new standards for safe and sustainable work environments, thereby enhancing both safety and efficiency within organizations.


Keywords


occupational risk; sustainable workplace; simulation; warehouse work; humanization of work

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References


Al-refaet, A.A.-Z., Zumrah, A.R., & Alshuhumi, S.R. (2019). The effect of organizational commitment on higher education services quality. E-Journal on Integration of Knowledge, 7, 8–16. http://dx.doi.org/10.2139/ssrn.4137052

Aneziris, O.N., Papazoglou, I.A., & Doudakmani, O. (2010). Assessment of occupational risks in an aluminium processing industry. International Journal of Industrial Ergonomics, 40(3), 321–329. https://doi.org/10.1016/j.ergon.2010.01.005

Ateeq, A., Al-refaei, A.A.-A., Alzoraiki, M., Milhem, M., Al-Tahitah, A.N., & Ibrahim, A. (2024). Sustaining organizational outcomes in manufacturing firms: The role of HRM and occupational health and safety. Sustainability, 16(3), 1035. https://doi.org/10.3390/su16031035

Badri, A., Boudreau-Trudel, B., & Souissi, A.S. (2018). Occupational health and safety in the industry 4.0 era: A cause for major concern? Safety Science, 109, 403–411. https://doi.org/10.1016/j.ssci.2018.06.012

Bartkowiak, A., & Butlewski, M. (2023). Sustainable agility culture – the case of pasta company. Sustainability, 15(23), 16540. https://doi.org/10.3390/su152316540

Bhattacharjee, S., Roy, P., Ghosh, S., Misra, S., & Obaidat, M.S. (2012). Wireless sensor network-based fire detection, alarming, monitoring and prevention system for Bord-and-Pillar coal mines. Journal of Systems and Software, 85, 571–581. https://doi.org/10.1016/j.jss.2011.09.015

Brocal, F., González, C., Reniers, G., Cozzani, V.,& Sebastián, M.A. (2018a). Risk management of hazardous materials in manufacturing processes: Links and transitional spaces between occupational accidents and major accidents. Materials, 11(10), 1915. https://doi.org/10.3390/ma11101915

Brocal, F., González, C., & Sebastián, M.A. (2018b). Technique to identify and characterize new and emerging risks: A new tool for application in manufacturing processes. Safety Science, 109, 144–156. https://doi.org/10.1016/j.ssci.2018.05.005

Brocal, F., Sebastián, M.A., & González, C. (2017). Theoretical framework for the new and emerging occupational risk modeling and its monitoring through technology lifecycle of industrial processes. Safety Science, 99(part B), 178–186. https://doi.org/10.1016/j.ssci.2016.10.016

European Agency for Safety and Health at Work. (2024). https://osha.europa.eu/en/themes/musculoskeletal-disorders/glossary

Folch-Calvo, M., Brocal, F., & Sebastián, M.A. (2019). New risk methodology based on control charts to assess occupational risks in manufacturing processes. Materials, 12(22), 3722. https://doi.org/10.3390/ma12223722

Goetsch, D. (2018). Occupational Safety and Health for Technologists, Engineers, and Managers. Financial Times Prentice Hall.

Gov.pl. (2024). Occupational risk assessments. https://www.biznes.gov.pl/en/portal/001827

Gualtieri, L., Rauch, E., & Vidoni, R. (2022). Development and validation of guidelines for safety in human-robot collaborative assembly systems. Computers & Industrial Engineering, 163, 107801. https://doi.org/10.1016/j.cie.2021.107801

Gul, M., & Fatih Ak, M. (2018). A comparative outline for quantifying risk ratings in occupational health and safety risk assessment. Journal of Cleaner Production, 196, 653–664. https://doi.org/10.1016/j.jclepro.2018.06.106

GUS. (2024). Warunki pracy. Wypadki przy pracy. https://stat.gov.pl/obszary-tematyczne/rynek-pracy/warunki-pracy-wypadki-przy-pracy/

Hu, S., Tang, C., Yu, R., Liu F., & Wang, X. (2013). Intelligent coal mine monitoring system based on the Internet of Things. In 3rd International Conference on Consumer Electronics, Communications and Networks (CECNet), IEEE, Nov 20–22; Xianning, China. https://doi.org/10.1109/CECNet.2013.6703350

INRS France (National Research and Safety Institute for the Prevention of Occupational Accidents and Diseases) Newsletter. (March 2018).

International Labour Organization. (2024). https://www.ilo.org/Search5/search.do?searchLanguage=en&searchWhat=occupational+risk

Javed, M.A., Muram, F.U., Hansson, H., Punnekkat, S., & Thane, H. (2021). Towards dynamic safety assurance for Industry 4.0. Journal of Systems Architecture, 114, 101914. https://doi.org/10.1016/j.sysarc.2020.101914

Kudelska, I., & Niedbał, R. (2020). Technological and organizational innovation in warehousing process – research over workload of staff and efficiency of picking stations. E&M Economics and Management, 23(3), 67–81. https://doi.org/10.15240/tul/001/2020-3-005

Lian, K.-Y., Hsiao, S.-J., & Sung, W.-T. (2013). Mobile monitoring and embedded control system for factory environment. Sensors, 13(12), 17379–17413. https://doi.org/10.3390/s131217379

Manuti, A., & Giancaspro, M.L. (2019). People make the difference: An explorative study on the relationship between organizational practices, employees’ resources, and organizational behavior enhancing the psychology of sustainability and sustainable development. Sustainability, 11(5), 1499. https://doi.org/10.3390/su11051499

Mur, S., & Demichela, M. (2009). Fuzzy application procedure (FAP) for the risk assessment of occupational accidents. Journal of Loss Prevention in the Process Industries, 22, 593–599. https://doi.org/10.1016/j.jlp.2009.05.007

Otto, A., Boysen, N., Scholl, A., & Walter, R. (2017). Ergonomic workplace design in the fast area. OR Spectrum, 39, 945–975. https://doi.org/10.1007/s00291-017-0479-x

Papazoglou, I.A., & Ale, B.J.M. (2007). A logical model for quantification of occupational risk. Reliability Engineering & System Safety, 92, 785–803. https://doi.org/10.1016/j.ress.2006.04.017

Papazoglou, I.A., Aneziris, O.N., Bellamy, L.J., Ale, B.J.M., & Oh, J. (2017a). Multi-hazard multi-person quantitative occupational risk model and risk management. Reliability Engineering & System Safety, 167, 310–326. https://doi.org/10.1016/j.ress.2017.06.019

Papazoglou, I.A., Aneziris, O.N., Bellamy, L.J., Ale, B.J.M., & Oh, J. (2017b). Quantitative occupational risk model: Single hazard. Reliability Engineering & System Safety, 160, 162–173. https://doi.org/10.1016/j.ress.2016.12.010

Park, J.-S., Lee, D.-G., Jimenez, J.A., Lee, S.-J., & Kim, J.-W. (2023). Human-focus digital twin applications for occupational safety and health in workplaces: A brief survey and research directions. Applied Sciences, 13(7), 4598. https://doi.org/10.3390/app13074598

Pawlewski, P. (2018a). Script language to describe agent’s behaviors. In J. Bajo et al. (Eds.), Highlights of Practical Applications of Agents, Multi-Agent Systems and Complexity. THE PAAMS Collection (pp. 137–148). Springer.

Pawlewski, P. (2018b). Using PFEP for simulation modeling of production systems. Procedia Manufacturing, 17, 811–818. https://doi.org/10.1016/j.promfg.2018.10.132

Pawlewski, P. (2019). Built-in lean management tools in simulation modeling. In N. Mustafee, K.-H.G. Bae, S. Lazarova-Molnar, M. Rabe, C. Szabo, P. Haas, & Y.J. Son (Eds.), Proceedings of the 2019 Winter Simulation Conference (pp. 2665–2676). IEEE Press.

Pfeffer, J. (2010). Building sustainable organizations: The human factors. Academy of Management Perspectives, 24(1), 34–45. http://www.jstor.org/stable/25682382

Podgórski, D., Majchrzycka, K., Dąbrowska, A., Gralewicz, G., & Okrasa, M. (2017). Towards a conceptual framework of OSH risk management in smart working environments based on smart PPE, ambient intelligence and the Internet of Things technologies. International Journal of Occupational Safety and Ergonomics, 23(1), 1–20. https://doi.org/10.1080/10803548.2016.1214431

Reiman, A., Kaivo-oja, J., Parviainen, E., Takala, E.P., & Lauraeus, T. (2021). Human factors and ergonomics in manufacturing in the industry 4.0 context-A scoping review. Technology in Society, 65, 101572. https://doi.org/10.1016/j.techsoc.2021.101572

Sadłowska-Wrzesińska, J. (2016). Assessment of safety and health of storage workers – a psychosocial approach. Log Forum, 12(1), 25–35. http://doi.org/10.17270/J.LOG.2016.1.3

Seminatore, A.A., Ghelardoni. L., Ceccarelli, A., Falai, L., Schultheis, M., & Malinowsky, B. (2012). ALARP (A Railway Automatic Track Warning System Based on Distributed Personal Mobile Terminals). Procedia – Social and Behavioral Sciences, 48, 2081–2090. https://doi.org/10.1016/j.sbspro.2012.06.1181

Song, G., Khan, F., Wang, H., Leighton, S., Yuan, Z., & Liu, H. (2016). Dynamic occupational risk model for offshore operations in harsh environments. Reliability Engineering & System Safety, 150, 58–64. https://doi.org/10.1016/j.ress.2016.01.021

Tobis, J., & Górny, A. (2014). The safety of manual handling in a warehouse – identification and assessment of transport and lifting hazards. Logistyka, 2, 6345–6357.

Zumrah, A.R.B., Bahaj, M.H.A., & Alrefai, A.S. (2021). An empirical investigation of the effect of training and development on organizational commitment in higher education sector. Journal of International Business and Management, 4(10), 1–15. https://doi.org/10.37227/JIBM-2021-09-1227




DOI: http://dx.doi.org/10.17951/h.2024.58.4.187-203
Date of publication: 2024-10-26 13:52:13
Date of submission: 2024-09-10 21:20:36


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Copyright (c) 2024 Małgorzata Sławińska, Paweł Pawlewski, Izabela Kudelska, Daniel Kańduła

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