Enhancing Operational Resilience Through the Simulation of Automated Material Handling in the Food Industry

Authors

  • Anna Lewandowska-Ciszek Department of Logistics, Poznań University of Economics and Business, Poland
  • Sylwia Konecka Department of Logistics, Poznań University of Economics and Business, Poland
  • Cyryl Leszczyński Department of Information Technology, Poznan University of Economics and Business, Poland
  • Piotr Szczypa The College of Economics and Social Sciences, Warsaw University of Technology, Poland
  • Marcin Szymkowiak Department of Statistics, Poznan University of Economics and Business, Poland

DOI:

https://doi.org/10.24425/mper.2025.157214

Abstract

Operating within a complex and dynamic global ecosystem, organizations are subject to continual evolution in response to shifting market demands. Adaptability has long been a crucial attribute of modern organizations. However, in recent years, resilience has become equally essential, shaping the future trajectory of their development. The aim of this study is to contribute empirically by proposing simulation as a method for enhancing operational resilience. Designing workflows within this context necessitates a multifaceted approach. While a comprehensive understanding of the individual process steps is essential, it is equally crucial to consider the broader system context and the factors that influence the successful execution and desired outcomes. This paper presents simulation research as a tool for performance improvement, and investment decisions. Crucially, simulation modelling facilitates a forwardlooking approach, enabling organizations to not only withstand and recover from challenges but to emerge strengthened and transformed, rather than merely reverting to pre-crisis conditions. The article emphasizes the strategic value of simulation modelling in enhancing an organization’s operational resilience.

References

Aastrup, J., & Halldórsson, Á. (2008). Epistemological role of case studies in logistics. International Journal of Physical Distribution & Logistics Management, 38 (10), 746–763. DOI: 10.1108/09600030810926475

Banaszyk, P. (2022). The economic resilience and the logistics company business. In Logistykacja gospodarki światowej (pp. 26–43). Publishing House of the University of Economics in Poznan. DOI: 10.18559/978-83-8211-106-4/2

Banks, J., Nelson, B.L., Carson, J.S., & Nicol, D.M. (2010). Discrete-Event System Simulation. Published by Pearson.

Beaverstock, M., Greenwood, A., & Nordgren, W. (2017). Applied simulation modeling and analysis using FlexSim. In Technometrics (Vol. 46, Issue 3).

Bennett, A. (2004). Case Study Methods: Design, Use, and Comparative Advantages. In D.F. Sprinz & Y. Wolinsky-Nahmias (Eds.), Models, Numbers, and Cases: Methods for Studying International Relations (pp. 19–55). University of Michigan Press.

Burduk, A. (2013). Modelowanie systemów narzedziem oceny stabilności procesów produkcyjnych. Oficyna Wydawnicza Politechniki Wrocławskiej.

Burduk, A., Lapczynska, D., & Popiel, P. (2021). Simulation modeling in production effectiveness improvement – case study. In Management and Production Engineering Review (Vol. 12, Issue 2). DOI: 10.24425/mper.2021.137680

Christopher, M., & Peck, H. (2004). Building the Resilient Supply Chain. The International Journal of Logistics Management, 15 (2). DOI: 10.1108/09574090410700275

Diakun, J. (2023, August). The multifaceted nature and contexts of “process simulation” and the associated pedagogical challenges in higher education. Modelling and Improving Production and Logistics Processes Using the FlexSim Simulation Environment within the FlexSim InterMarium Tour.

Dinwoodie, J., & Xu, J. (2008). Case studies in logistics: a review and tentative taxonomy. International Journal of Logistics Research and Applications, 11 (5), 393–408. DOI: 10.1080/13675560802389130

Domingo, R., Alvarez, R., Melodía Peña, M., & Calvo, R. (2007). Materials flow improvement in a lean assembly line: a case study. Assembly Automation, 27 (2), 141– 147. DOI: 10.1108/01445150710733379

Dulina, L., Zuzik, J., Furmannova, B., & Kukla, S. (2024). Improving Material Flows in an Industrial Enterprise: A Comprehensive Case Study Analysis. Machines, 12 (5), 308. DOI: 10.3390/machines12050308

Eberle, E. (2020). Process simulation – what can a digital twin do? https://www.controlengeurope.com/article/182444/Process-simulation-what-can-adigital-twin-do-.aspx

Essuman, D., Boso, N., & Annan, J. (2020). Operational resilience, disruption, and efficiency: Conceptual and empirical analyses. International Journal of Production Economics, 229. DOI: 10.1016/j.ijpe.2020.107762

Fishman, G. (1981). Computer Simulation: Concepts and Methods. PWE.

Fishman, G. (2001). Discrete-event simulation: modeling, programming, and analysis (Vol. 537). Springer.

Gołda, G., Kampa, A., & Paprocka, I. (2018). Analysis of human operators and industrial robots performance and reliability. Management and Production Engineering Review, 9 (1). DOI: 10.24425/119397

Goldratt, E.M., & Cox, J. (2016). The goal: a process of ongoing improvement. Routledge.

Hakkinen, L., & Hilmola, O.-P. (2005). Methodological pluralism in case study research: an analysis of contem porary operations management and logistics research. International Journal of Services and Operations Management, 1 (3), 239. DOI: 10.1504/ijsom.2005.006576

Halim, N.H.A., Jaffar, A., Noriah, Y., & Naufal, A.A. (2013). Case Study: The Methodology of Lean Manufacturing Implementation. Applied Mechanics and Materials, 393, 3–8. DOI: 10.4028/www.scientific.net/amm.393.3

Hamrol, A., Gawlik, J., & Skołud, B. (2015). Strategies and practices of efficient operation. Lean, Six Sigma, and other (methods). PWN Scientific Publishers.

Hepfer, M., & Lawrence, T.B. (2022). The Heterogeneity of Organizational Resilience: Exploring functional, operational and strategic resilience. Organization Theory, 3 (1). DOI: 10.1177/26317877221074701

Hohenstein, N.O., Feise, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience: A systematic review and paths for further investigation. International Journal of Physical Distribution and Logistics Management, 45. DOI: 10.1108/IJPDLM-05-2013-0128

Holgado, M., Blome, C., Schleper, M.C., & Subramanian, N. (2024). Brilliance in resilience: operations and supply chain management’s role in achieving a sustainable future. International Journal of Operations and Production Management, 44 (5). DOI: 10.1108/IJOPM-12-2023-0953

Irfan, I., Sumbal, M.S.U.K., Khurshid, F., & Chan, F.T.S. (2022). Toward a resilient supply chain model: critical role of knowledge management and dynamic capabilities. Industrial Management and Data Systems, 122 (5). DOI: 10.1108/IMDS-06-2021-0356

Kaczmar, I., & Banyai, T. (2024). The Optimal Routing of Raspberry Pickers in an Analytical and Simulation Approach. Management and Production Engineering Review, No 1. DOI: 10.24425/mper.2024.149998

Kósi, K., & Torma, A. (2005). Tracing material flows on industrial sites. Periodica Polytechnica Social and Management Sciences, 13 (2), 133–149.

Królczyk, G., Legutko, S., Królczyk, J., & Tama, E. (2014). Materials Flow Analysis in the Production Process – Case Study. Applied Mechanics and Materials, 474, 97–102. DOI: 10.4028/www.scientific.net/amm.474.97

Łatuszyńska, M. (2011). Computer simulation methods an attempt of logical classicifation. Studies and Materials of the Polish Knowledge Management Association, 41, 163–176.

Lewandowska-Ciszek, A. (2025). Znaczenie symulacji procesów biznesowych dla projektowania odpornych łańcuchów dostaw. In Logistyka i zarządzanie łańcuchem dostaw w czasach turbulencji, zakłóceń i niestabilnej gospodarki (pp. 141–159). Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu. DOI: 10.18559/978-83-8211-251-1/8

Lewandowska-Ciszek, A., Szczypa, P., Szymkowiak, M., & Grabański, S. (2024). Navigating hyperindividualization: building resilience systems through process simulation. Scientific Papers of Silesian University of Technology. Organization and Management Series, 2024 (209), 229–247. DOI: 10.291 19/1641-3466.2024.209.13

Lidberg, S., Aslam, T., Pehrsson, L., & Ng, A.H.C. (2020). Optimizing real-world factory flows using aggregated discrete event simulation modelling. Flexible Services and Manufacturing Journal, 32 (4). DOI: 10.1007/s10696-019-09362-7

Luscinski, S., & Ivanov, V. (2020). A simulation study of industry 4.0 factories based on the ontology on flexibility with using flexsim®software. Management and Production Engineering Review, 11 (3). DOI: 10.24425/mper.2020.134934

Marinus, E., Mostard, M., Segers, E., Schubert, T.M., Madelaine, A., & Wheldall, K. (2016). A Special Font for People with Dyslexia: Does it Work and, if so, why? Dyslexia, 22 (3). DOI: 10.1002/dys.1527

Maryniak, A., Bulhakova, Y., & Lewoniewski, W. (2021). Resilient supply chains 4.0 – A research review. Proceeding – 2021 26th IEEE Asia-Pacific Conference on Communications, APCC 2021. DOI: 10.1109/APCC49754.2021.9609916

Mielczarek, B. (2009). Simulation modelling in management: Discrete-event simulation. Wroclaw University of Science and Technology Press.

Modrák, V. (2009). Case on Manufacturing Cell Formation Using Production Flow Analysis.

Moore, R., & Scheinkopf, L. (1998). Theory of constraints and lean manufacturing: friends or foes. Chesapeake Consulting Inc.

Ocicka, B., Mierzejewska, W., & Brzeziński, J. (2022). Correction: Creating supply chain resilience during and post-COVID-19 outbreak: the organizational ambidexterity perspective. DECISION, 49 (3). DOI: 10.1007/s40622-022-00322-z

Rice Jr, J.B., & Caniato, F. (2003). Building a secure and resilient supply network. Supply Chain Management Review, 7 (5).

Robinson, S. (2004). Simulation : The practice of model development and use. In Practice of model development and use. John Wiley & Sons.

Schleper, M.C., Gold, S., Trautrims, A., & Baldock, D. (2021). Pandemic-induced knowledge gaps in operations and supply chain management: COVID-19’s impacts on retailing. International Journal of Operations and Production Management, 41 (3). DOI: 10.1108/IJOPM-12-2020-0837

Srai, J.S., Graham, G., Van Hoek, R., Joglekar, N., & Lorentz, H. (2023). Impact pathways: unhooking supply chains from conflict zones—reconfiguration and fragmentation lessons from the Ukraine–Russia war. International Journal of Operations and Production Management, 43 (13). DOI: 10.1108/IJOPM-08-2022-0529

Szymczak, M. (2015). Responsibility and resiliency as features of adaptive supply chains. Studia Oeconomica Posnaniensia, 3 (6), 39–54.

Winkowski, J. (1974). Process Simulation Programming. Scientific and Technical Publishing House.

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Published

2025-12-30

How to Cite

Lewandowska-Ciszek, Anna, et al. “Enhancing Operational Resilience Through the Simulation of Automated Material Handling in the Food Industry”. Management and Production Engineering Review, vol. 16, no. 4, Dec. 2025, pp. [nr art. 11], s. 1-14, doi:10.24425/mper.2025.157214.

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