AI-Supported Process Management Tools for Handling Disturbances in Industry 4.0 Production Systems
References
- Ślusarczyk B., (2018) Industry 4.0 – are we ready?, Polish Journal of Management Studies 17 pp. 232-248. https://doi.org/10.17512/pjms.2018.17.1.19.
- Suchacka M., Pabian A.M., Ulewicz R., (2023) Industry 4.0 and socio-economic evolution, Polish Journal of Management Studies 28 pp. 311-329. https://doi.org/10.17512/pjms.2023.28.1.18.
- Zahid A., Leclaire P., Hammadi L., Costa-Affonso R., El Ballouti A., (2025) Exploring the potential of industry 4.0 in manufacturing and supply chain systems: Insights and emerging trends from bibliometric analysis, Supply Chain Analytics 10 100108. https://doi.org/10.1016/j.sca.2025.100108.
- Koul P., (2025) Automation and Industry 4.0 in production engineering: A comprehensive review, Advances in Mechanical and Materials Engineering 42 pp. 149-190. https://doi.org/10.7862/rm.2025.14.
- Cimino A., Grazia Gnoni M., Longo F., Solina V., (2023) Integrating multiple industry 4.0 approaches and tools in an interoperable platform for manufacturing SMEs, Comput. Ind. Eng. 186. 109732. https://doi.org/10.1016/j.cie.2023.109732.
- Thomas S., Nair D.S., Joseph J., Srampical S.G., Cleetus R.S., (2025) Examining the Sustainable Integration of Artificial Intelligence in Human Resource Digitalization in the Context of Industry 4.0, European Public & Social Innovation Review 11 pp. 1-14. https://doi.org/10.31637/epsir-2026-2044.
- Wolniak R., Saniuk S., Grabowska S., Gajdzik B., (2020) Identification of Energy Efficiency Trends in the Context of the Development of Industry 4.0 Using the Polish Steel Sector as an Example, Energies (Basel). 13. 2867. https://doi.org/10.3390/en13112867.
- Lazar S., Klimecka-Tatar D., Obrecht M., (2021) Sustainability Orientation and Focus in Logistics and Supply Chains, Sustainability 13. 3280. https://doi.org/10.3390/su13063280.
- Brodny J., Tutak M., (2024) Assessing the level of innovativeness and digitalization of enterprises in the European Union States, Journal of Open Innovation: Technology, Market, and Complexity 10. 100210. https://doi.org/10.1016/j.joitmc.2024.100210.
- Nain G., Samal U., (2026) Intelligence behind individualization: A survey on role of AI in mass customized and personalized production, Technol. Soc. 85. 103195. https://doi.org/10.1016/j.techsoc.2025.103195.
- Cimino A., Elbasheer M., Longo F., Mirabelli G., Solina V., Veltri P., (2025) Automatic simulation models generation in industrial systems: A systematic literature review and outlook towards simulation technology in the Industry 5.0, J. Manuf. Syst. 80 pp. 859-882. https://doi.org/10.1016/j.jmsy.2025.03.027.
- Hein-Pensel F., (2026) Organizational identity meets digital transformation: understanding the interplay between transformation and identity in Industry 5.0, Journal of Organizational Change Management 39. pp. 1-21. https://doi.org/10.1108/JOCM-04-2025-0352.
- Schwierzy J., Dehghan R., Schmidt S., Grashof N., Hottenrott H., Woywode M., (2026) Mapping technology diffusion with AI: A web-based approach for tracking additive manufacturing adoption, International Journal of Information Management Data Insights 6. 100387. https://doi.org/10.1016/j.jjimei.2025.100387.
- Cimino A., Longo F., Solina V., Veltri P., (2026) Integrating large language models with industrial simulation for multi-level decision support: an innovation management perspective in Industry 5.0, European Journal of Innovation Management 29. pp. 27-53. https://doi.org/10.1108/EJIM-10-2024-1246.
- Brodny J., Tutak M., (2021) Assessing the level of digitalization and robotization in the enterprises of the European Union Member States, PLoS One 16. e0254993. https://doi.org/10.1371/journal.pone.0254993.
- Bednarek M., Luściński S., Jabłoński M., Schaffeld Graniffo G.J., (2025) Harnessing Industry 4.0 Technologies: A Novel Predictive Maintenance Method for Advanced Production Systems, Management and Production Engineering Review. https://doi.org/10.24425/mper.2025.153928.
- Mesjasz-Lech A., (2024) Trends of Industrial Waste Generation in Manufacturing Enterprises in the Context of Waste Prevention – Shift-Share Analysis for European Union Countries, Sustainability 17. 34. https://doi.org/10.3390/su17010034.
- Mesjasz-Lech A., Kemendi Á., Michelberger P., (2024) Circular manufacturing and Industry 5.0. assessing material flows in the manufacturing process in relation to e-waste streams, Engineering Management in Production and Services 16. pp. 114-133. https://doi.org/10.2478/emj-2024-0009.
- Ślusarczyk B., Wiśniewska J., (2024) Barriers and the potential for changes and benefits from the implementation of Industry 4.0 solutions in enterprises, Production Engineering Archives 30 pp. 145-154. https://doi.org/10.30657/pea.2024.30.14.
- Pietraszek J., Radek N., Goroshko A.V., (2020) Challenges for the DOE methodology related to the introduction of Industry 4.0, Production Engineering Archives 26. pp. 190-194. https://doi.org/10.30657/pea.2020.26.33.
- Karkoszka T., (2021) Technological Risk in the Context of Process Approach and Risk Assessment, System Safety: Human – Technical Facility – Environment 3. pp. 312-319. https://doi.org/10.2478/czoto-2021-0033.
- Stelmach A., (2025) Digital Transformation: Impact of Modern Technologies and Project Management on Optimization of Production Processes in Era of Industry 4.0, Decision Making in Manufacturing and Services pp. 39-47. https://doi.org/10.7494/dmms.2024.si.6650.
- Ahmmed M.S., Isanaka S.P., Liou F., (2024) Promoting Synergies to Improve Manufacturing Efficiency in Industrial Material Processing: A Systematic Review of Industry 4.0 and AI, Machines 12. 681. https://doi.org/10.3390/machines12100681.
- Wachnik B., (2022) Analysis of the use of artificial intelligence in the management of Industry 4.0 projects. The perspective of Polish industry, Production Engineering Archives 28 pp. 56-63. https://doi.org/10.30657/pea.2022.28.07.
- Čermáková J., Houda M., Rolínek L., Pech M., (2023) Perception of the Leadership Competency in the 4th Revolution Era in the Czech Republic, Management and Production Engineering Review pp. 3-12. https://doi.org/10.24425/mper.2023.145361.
- Sathyamoorthi V., Inayath Ahamed S.B., Hariharasudan A., Szczepanska-Woszczyna K., Kot S., (2023) Unveiling the Factors of Green Human Resources in Manufacturing Industries, Management and Production Engineering Review. https://doi.org/10.24425/mper.2023.147190.
- Del Gallo M., Mazzuto G., Ciarapica F.E., Bevilacqua M., (2023) Artificial Intelligence to Solve Production Scheduling Problems in Real Industrial Settings: Systematic Literature Review, Electronics (Basel). 12. 4732. https://doi.org/10.3390/electronics12234732.
- Wolniak R., Stecuła K., (2024) Artificial Intelligence in Smart Cities – Applications, Barriers, and Future Directions: A Review, Smart Cities 7. pp. 1346-1389. https://doi.org/10.3390/smartcities7030057.
- Espina-Romero L., Gutiérrez Hurtado H., Ríos Parra D., Vilchez Pirela R.A., Talavera-Aguirre R., Ochoa-Díaz A., (2024) Challenges and Opportunities in the Implementation of AI in Manufacturing: A Bibliometric Analysis, Sci 6. 60. https://doi.org/10.3390/sci6040060.
- Midor K., Sujová E., Cierna H., Zarebinska D., Kaniak W., (2020) Key Performance Indicators (KPIs) as a Tool to Improve Product Quality, New Trends in Production Engineering 3 pp. 347-354. https://doi.org/10.2478/ntpe-2020-0029.
Language: English
Page range: 433 - 443
Submitted on: Feb 1, 2026
Accepted on: Jul 1, 2026
Published on: Aug 6, 2026
Published by: STE Group sp. z.o.o.
In partnership with: Paradigm Publishing Services
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© 2026 Dorota Klimecka-Tatar, published by STE Group sp. z.o.o.
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.