Keywords
Reliability-Centered Maintenance
Total Cost of Ownership
Digital Twin
Fatigue Risk Management System
Operational Efficiency
Chuikov’s Multi-Contour Safety Framework
How to Cite
Abstract
The paper substantiates the necessity of transitioning from discrete logistical practices to the creation of holistic cyber-physical ecosystems, ensuring the reliability of production processes in a “24/7” mode. The methodological basis of the study constituted a synthesis of systems engineering principles, ISO 55000 standards and RCM II/III methodology. The practical validity of the research is confirmed by the implementation of the proprietary “Chuikov’s Multi-Contour Safety Framework” on a fleet of 350 special machinery units, demonstrating resilience under critical loads. The article presents a management architecture based on the deep integration of IoT telematic solutions, DVRP algorithms and “Digital Twin” technologies. It is proven that the convergence of GIS and SCADA data in water supply enterprises allows considering transport logistics as a key element of hydraulic stability, contributing to the reduction of unaccounted resource losses and minimization of accident elimination time. The efficiency of transitioning to planning based on TCO and dynamic LCC modeling, as well as precision control of special machinery operating modes (separation of consumption into motion and PTO), is demonstrated. The paper forms an updated competency profile of a fleet department head – strategic asset management, including cyber risk management and human capital through bio-mathematical FRMS. A distinctive contribution of the study is the identification and engineering resolution of the “alarm fatigue” phenomenon in high-tech vehicle cabs: the paradoxical decrease in operator vigilance caused by an excess of simultaneous acoustic and visual alerts. The proposed transition to tactile feedback interfaces and cognitively structured information grouping substantially maintained driver focus under high-intensity dispatch conditions. A retrospective analysis of industry data for the decade 2015–2025 documents measurable structural outcomes: implementation of predictive diagnostics reduced the unscheduled repair share by 32%, while precision driving profile analytics delivered a 12–23% reduction in fuel and operating expenditures versus the base period. The paper further substantiates a revised organizational role for the transport division head – one who must simultaneously master OT cybersecurity to protect the fleet’s digital perimeter, lead decarbonization roadmap development for alternative powertrains (EV, hydrogen, biofuel), and act as a cross-functional integrator between technical services, finance and top management. The findings confirm that a scientifically governed transport complex, deeply embedded in the enterprise’s value creation chain, constitutes a strategic resilience asset capable of maintaining hydraulic and operational stability under extreme technogenic and cyber threat conditions.
References
1. Rehak, D., Senovsky, P., Hromada, M., & Lovecek, T. (2019). Complex approach to critical infrastructure resilience assessment. International Journal of Critical Infrastructure Protection, (25), 125–138. https://doi.org/10.1016/j.ijcip.2019.03.003
2. Mobley, R. K. (2002). Predictive maintenance techniques. In An introduction to predictive maintenance (2nd ed., pp. 99–113). Butterworth-Heinemann. https://doi.org/10.1016/B978-075067531-4/50006-3
3. Stanton, N.A., Salmon, P.M., Rafferty, L.A., Walker, G.H., Baber, C., & Jenkins, D.P. (2013). Human Factors Methods: A Practical Guide for Engineering and Design (2nd ed.). CRC Press. https://doi.org/10.1201/9781315587394
4. Berg Insight. (2024). Fleet management in Europe: 18th Edition. Gothenburg: Berg Insight AB. https://media.berginsight.com/2023/12/08233419/bi-fm18-ps.pdf
5. Killeen, P., Ding, B., Kiringa, I., & Yeap, T. (2019). IoT-based predictive maintenance for fleet management. Procedia Computer Science, (151), 607–613. https://doi.org/10.1016/j.procs.2019.04.184
6. Naumann, R.B., Kreuger, L. K., Sandt, L., Hassmiller Lich, K., Bauchwitz, B., Kumfer, W. & Combs, T. (2023). Examining the Safety Benefits of Partial Vehicle Automation Technologies in an Uncertain Future (Technical Report). Washington, D.C.: AAA Foundation for Traffic Safety. https://aaafoundation.org/examining-the-safety-benefits-of-partial-vehicle-automation-technologies-in-an-uncertain-future/
7. Kossiakoff, A., Seymour, S. J., Flanigan, D. J., & Biemer, S. M. (2020). Systems engineering: Principles and practice (3rd ed.). John Wiley & Sons, Inc. https://doi.org/10.1002/9781119516699
8. Hastings, N. A. J. (2015). Physical asset management. Springer. https://books.google.com.ua/books/about/Physical_Asset_Management.html?id=wxnGBgAAQBAJ&redir_esc=y
9. Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019). Digital twin in industry: State-of-the-art. IEEE Transactions on Industrial Informatics, 15(4), 2405–2415. https://www.researchgate.net/publication/345078627_Digital_Twin_in_Industry_State-of-the-Art
10. The Institute of Asset Management. (2024). Asset management – an anatomy. IAM. Version 4. https://theiam.org/media/5615/iam-anatomy-version-4-final.pdf
11. Minis, I., Zeimpekis, V., Dounias, G., & Ampazis, N. (Eds.). (2011). Supply chain optimization, design, and management: Advances and intelligent methods. Business Science Reference (an imprint of IGI Global). https://ndl.ethernet.edu.et/bitstream/123456789/23290/1/21%202011.pdf
12. Gransberg, D. (2010). Life Cycle Costing for Engineers. Construction Management and Economics, 28(10), 1113–1114. https://doi.org/10.1080/01446193.2010.508500
13. Ivanov, D., & Dolgui, A. (2021). A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0. Production Planning & Control, 32(9), 775–788. https://doi.org/10.1080/09537287.2020.1768450
14. Pyzdek, T. (2014). The Six Sigma handbook (4th ed.). McGraw‑Hill Education. https://semcme.org/wp-content/uploads/The-Six-Sigma-Handbook.pdf
15. Gross, D., Shortle, J. F., Thompson, J. M., & Harris, C. M. (2018). Fundamentals of queueing theory (5th ed.). Wiley. https://books.google.com.ua/books/about/Fundamentals_of_Queueing_Theory.html?id=P4ZZDwAAQBAJ&redir_esc=y
16. Jardine, A. K. S., & Tsang, A. H. C. (2021). Maintenance, Replacement, and Reliability: Theory and Applications (3rd ed.). CRC Press. https://doi.org/10.1201/9780429021565
17. Dawson, D., & McCulloch, K. (2005). Managing fatigue: It’s about sleep. Sleep Medicine Reviews, 9(5), 365–380. https://doi.org/10.1016/j.smrv.2005.03.002
18. Pamidimukkala, A., Kermanshachi, S., Adepu, N., & Safapour, E. (2021). Resilience in Water Infrastructures: A Review of Challenges and Adoption Strategies. Sustainability, 13(23), 12986. https://doi.org/10.3390/su132312986
19. Psaraftis, H. N., Wen, M., & Kontovas, C. A. (2016). Dynamic vehicle routing problems: Three decades and counting. Networks, 67(1), 3–31. https://doi.org/10.1002/net.21628
20. Hazen, B. (2014). Green logistics. Transportation Journal, 53(3), 376–378. https://www.jstor.org/stable/10.5325/transportationj.53.3.fm
21. Basma, H., & Rodríguez, F. (2023, November 13). A total cost of ownership comparison of truck decarbonization pathways in Europe (Working Paper). International Council on Clean Transportation. https://theicct.org/publication/total-cost-ownership-trucks-europe-nov23/#:~:text=Heavy%2Dduty%20vehicles%20(HDV),options%20(see%20figure%20below)
22. Stouffer, K., Pease, M., Tang, C. Y., Zimmerman, T., Pillitteri, V., Lightman, S., Hahn, A., Saravia, S., Sherule, A., & Thompson, M. (2023). Guide to operational technology (OT) security (NIST Special Publication 800-82r3). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.SP.800-82r3
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