To the Methods of System Engineering
Probabilistic Approaches to the Analysis of the System Quality Management Process
Abstract
Advanced system engineering should be based on interdisciplinary theory and focused on the systems of the future, becoming more intelligent, self-organizing, resource-efficient, safe and sustainable. As a result of the analysis of forecasts for the application of system engineering, probabilistic approaches to the analysis of the system quality management process are proposed.
The proposed probabilistic approaches allow us to assess the risks of violation of the reliability of the implementation of the system quality management process (including the risks of failure to perform the necessary actions, violation of the deadlines for performing the necessary actions of the process and/or the presence of unacceptable defects in the supplied products and/or services) without taking into account and taking into account additional specific system requirements. Their application is focused on solving actual problems of system engineering.
References
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4. Kostogryzov A., Stepanov P., Grigoriev L., Atakishchev O., Nistratov A., Nistratov G. Improvement of Existing Risks Control Concept for Complex Systems by the Automatic Combination and Generation of Probabilistic Models and Forming the Storehouse of Risks Predictions Knowledge. Proceedings of the 2nd International Conference on Applied Mathematics, Simulation and Modelling (AMSM). DEStech Publications Inc., Phuket, Thailand; 2017. p. 279-283. (In Eng.) doi: https://doi.org/10.12783/dtetr/amsm2017/14857
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6. Kostogryzov A.I., et al. Mathematical Models and Applicable Technologies to Forecast, Analyze, and Optimize Quality and Risks for Complex Systems. Proceedings of the First International Conference on Transportation Information and Safety (ICTIS). American Society of Civil Engineers, Wuhan, China; 2011. p. 845-854. (In Eng.) doi: https://doi.org/10.1061/41177(415)107
7. Kostogryzov A., Nistratov G., Nistratov A. Some Applicable Methods to Analyze and Optimize System Processes in Quality Management. In: Aized T. (ed.) Total Quality Management and Six Sigma. IntechOpen, London; 2012. p. 127-196. (In Eng.) doi: http://dx.doi.org/10.5772/46106
8. Kostogryzov A., Grigoriev L., Nistratov G., Nistratov A., Krylov V. Prediction and Optimization of System Quality and Risks on the Base of Modelling Processes. American Journal of Operations Research. 2013; 3(1A):217-244. (In Eng.) doi: https://doi.org/10.4236/ajor.2013.31A021
9. Artemyev V., Kostogryzov A., Rudenko J., Kurpatov O., Nistratov G., Nistratov A. Probabilistic methods of estimating the mean residual time before the next parameters abnormalities for monitored critical systems. 2017 2nd International Conference on System Reliability and Safety (ICSRS). IEEE Press, Milan, Italy; 2017. p. 368-373. (In Eng.) doi: https://doi.org/10.1109/ICSRS.2017.8272850
10. Kostogryzov A., Grigoriev L., Golovin S., Nistratov A., Nistratov G., Klimov S. Probabilistic Modeling of Robotic and Automated Systems Operating in Cosmic Space. Proceedings of the International Conference on Communication, Network and Artificial Intelligence (CNAI). DEStech Publications Inc., Beijing, China; 2018. p. 298-303. (In Eng.) doi: https://doi.org/10.12783/dtcse/cnai2018/24174
11. Kostogryzov A., Grigoriev L., Kanygin P., Golovin S., Nistratov A., Nistratov G. The Experience of Probabilistic Modeling and Optimization of a Centralized Heat Supply System Which is an Object for Modernization. International Conference on Physics, Computing and Mathematical Modeling (PCMM). DEStech Publications Inc., Shanghai; 2018. p. 93-97. (In Eng.) doi: https://doi.org/10.12783/dtcse/pcmm2018/23643
12. Artemyev V., Rudenko J., Nistratov G. Probabilistic Methods and Technologies of Risk Prediction and Rationale of Preventive Measures by Using "Smart Systems": Applications to Coal Branch for Increasing Industrial Safety of Enterprises. In: Kostogryzov A. (ed.) Probabilistic Modeling in System Engineering. IntechOpen, London; 2018. p. 23-51. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.75109
13. Kershenbaum V., Grigoriev L., Kanygin P., Nistratov A. Probabilistic Modeling Processes for Oil and Gas. In: Kostogryzov A. Probabilistic Modeling in System Engineering. IntechOpen, London; 2018. p. 55-79. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.74963
14. Kostogryzov A., Nistratov A., Nistratov G., Atakishchev O., Golovin S., Grigoriev L. The Probabilistic Analysis of the Possibilities to Keep "Organism Integrity" by Continuous Monitoring. Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018). Atlantis Press, Chengdu, China; 2018. p. 432-435. (In Eng.) doi: https://doi.org/10.2991/mmsa-18.2018.96
15. Kostogryzov A., Korolev V. Probabilistic Methods for Cognitive Solving of Some Problems in Artificial Intelligence Systems. In: Kostogryzov A., Korolev V. (eds.) Probability, Combinatorics and Control. IntechOpen, London; 2019. p. 3-34. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.89168
16. Kostogryzov A., Makhutov N., Nistratov A., Reznikov G. Probabilistic Predictive Modelling for Complex System Risk Assessments. In: Abdalla R., El-Diasty M., Kostogryzov A., Makhutov N.A. (ed.) Time Series Analysis ‒ New Insights. London: IntechOpen; 2022. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.106869
17. Akundi A., Lopez V. A Review on Application of Model Based Systems Engineering to Manufacturing and Production Engineering Systems. Procedia Computer Science. 2021; 185:101-108. (In Eng.) doi: https://doi.org/10.1016/j.procs.2021.05.011
18. Kołowrocki K., Soszyńska-Budny J. Reliability and Safety of Complex Technical Systems and Processes. Springer Series in Reliability Engineering. Springer London; 2011. 405 p. (In Eng.) doi: https://doi.org/10.1007/978-0-85729-694-8
19. Kołowrocki K., Soszyńska-Budny J. Prediction of critical infrastructures safety. The 10th International Conference on Digital Technologies 2014. IEEE Press; 2014. p. 130-138. (In Eng.) doi: https://doi.org/10.1109/DT.2014.6868704
20. Zio E. An Introduction to the Basics of Reliability and Risk Analysis. World Scientific Publishing Co Pte Ltd; 2007. 236 p. (In Eng.) doi: https://doi.org/10.1142/6442
21. Eid M., Rosato V. Critical Infrastructure Disruption Scenarios Analyses via Simulation. In: Setola R., Rosato V., Kyriakides E., Rome E. (eds.) Managing the Complexity of Critical Infrastructures. Studies in Systems, Decision and Control. Vol. 90. Springer, Cham; 2016. p. 43-61. (In Eng.) doi: https://doi.org/10.1007/978-3-319-51043-9_3
22. Gneiting T., Balabdaoui F., Raferty A.E. Probabilistic forecasts, calibration and sharpness. Journal of the Royal Statistical Society. Series B (Statistical Methodology). 2007; 69(2):243-268. (In Eng.) doi: https://doi.org/10.1111/j.1467-9868.2007.00587.x
23. Meridji K., Issa G. A development approach of software requirements for renewable energy applications using fundamental principles of software engineering. 2013 1st International Conference & Exhibition on the Applications of Information Technology to Renewable Energy Processes and Systems. IEEE Press; 2013. p. 107-112. (In Eng.) doi: https://doi.org/10.1109/IT-DREPS.2013.6588162
24. Wisniewski M., Gladysz B., Ejsmont K., Wodecki A., Van Erp T. Industry 4.0 Solutions Impacts on Critical Infrastructure Safety and Protection ‒ A Systematic Literature Review. IEEE Access. 2022; 10:82716-82735. (In Eng.) doi: https://doi.org/10.1109/ACCESS.2022.3195337
25. Shah L., Siadat A., Vernadat F. Maturity assessment in risk management in manufacturing engineering. 2009 3rd Annual IEEE Systems Conference. IEEE Press; 2009. p. 296-301. (In Eng.) doi: https://doi.org/10.1109/SYSTEMS.2009.4815815
2. Kostogryzov A., Nistratov A., Nistratov G. Analytical Risks Prediction. Rationale of System Preventive Measures for Solving Quality and Safety Problems. In: Sukhomlin V., Zubareva E. (eds.) Modern Information Technology and IT Education. SITITO 2018. Communications in Computer and Information Science. Vol. 1201. Springer, Cham; 2020. p. 352-364. (In Eng.) doi: https://doi.org/10.1007/978-3-030-46895-8_27
3. Kostogryzov A., Panov V., Stepanov P., Grigoriev L., Nistratov A., Nistratov G. Optimization of sequence of performing heterogeneous repair work for transport systems by criteria of timeliness. 2017 4th International Conference on Transportation Information and Safety (ICTIS). IEEE Press Banff, AB, Canada; 2017. p. 872-876. (In Eng.) doi: https://doi.org/10.1109/ICTIS.2017.8047870
4. Kostogryzov A., Stepanov P., Grigoriev L., Atakishchev O., Nistratov A., Nistratov G. Improvement of Existing Risks Control Concept for Complex Systems by the Automatic Combination and Generation of Probabilistic Models and Forming the Storehouse of Risks Predictions Knowledge. Proceedings of the 2nd International Conference on Applied Mathematics, Simulation and Modelling (AMSM). DEStech Publications Inc., Phuket, Thailand; 2017. p. 279-283. (In Eng.) doi: https://doi.org/10.12783/dtetr/amsm2017/14857
5. Kostogryzov A.I. Software Tools Complex for Evaluation of Information Systems Operation Quality (CEISOQ). Proceedings of the 34-th Annual Event of the Government Electronics and Information Association (GEIA). Engineering and Technical Management Symposium, USA, Dallas; 2000. p. 63-70. (In Eng.)
6. Kostogryzov A.I., et al. Mathematical Models and Applicable Technologies to Forecast, Analyze, and Optimize Quality and Risks for Complex Systems. Proceedings of the First International Conference on Transportation Information and Safety (ICTIS). American Society of Civil Engineers, Wuhan, China; 2011. p. 845-854. (In Eng.) doi: https://doi.org/10.1061/41177(415)107
7. Kostogryzov A., Nistratov G., Nistratov A. Some Applicable Methods to Analyze and Optimize System Processes in Quality Management. In: Aized T. (ed.) Total Quality Management and Six Sigma. IntechOpen, London; 2012. p. 127-196. (In Eng.) doi: http://dx.doi.org/10.5772/46106
8. Kostogryzov A., Grigoriev L., Nistratov G., Nistratov A., Krylov V. Prediction and Optimization of System Quality and Risks on the Base of Modelling Processes. American Journal of Operations Research. 2013; 3(1A):217-244. (In Eng.) doi: https://doi.org/10.4236/ajor.2013.31A021
9. Artemyev V., Kostogryzov A., Rudenko J., Kurpatov O., Nistratov G., Nistratov A. Probabilistic methods of estimating the mean residual time before the next parameters abnormalities for monitored critical systems. 2017 2nd International Conference on System Reliability and Safety (ICSRS). IEEE Press, Milan, Italy; 2017. p. 368-373. (In Eng.) doi: https://doi.org/10.1109/ICSRS.2017.8272850
10. Kostogryzov A., Grigoriev L., Golovin S., Nistratov A., Nistratov G., Klimov S. Probabilistic Modeling of Robotic and Automated Systems Operating in Cosmic Space. Proceedings of the International Conference on Communication, Network and Artificial Intelligence (CNAI). DEStech Publications Inc., Beijing, China; 2018. p. 298-303. (In Eng.) doi: https://doi.org/10.12783/dtcse/cnai2018/24174
11. Kostogryzov A., Grigoriev L., Kanygin P., Golovin S., Nistratov A., Nistratov G. The Experience of Probabilistic Modeling and Optimization of a Centralized Heat Supply System Which is an Object for Modernization. International Conference on Physics, Computing and Mathematical Modeling (PCMM). DEStech Publications Inc., Shanghai; 2018. p. 93-97. (In Eng.) doi: https://doi.org/10.12783/dtcse/pcmm2018/23643
12. Artemyev V., Rudenko J., Nistratov G. Probabilistic Methods and Technologies of Risk Prediction and Rationale of Preventive Measures by Using "Smart Systems": Applications to Coal Branch for Increasing Industrial Safety of Enterprises. In: Kostogryzov A. (ed.) Probabilistic Modeling in System Engineering. IntechOpen, London; 2018. p. 23-51. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.75109
13. Kershenbaum V., Grigoriev L., Kanygin P., Nistratov A. Probabilistic Modeling Processes for Oil and Gas. In: Kostogryzov A. Probabilistic Modeling in System Engineering. IntechOpen, London; 2018. p. 55-79. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.74963
14. Kostogryzov A., Nistratov A., Nistratov G., Atakishchev O., Golovin S., Grigoriev L. The Probabilistic Analysis of the Possibilities to Keep "Organism Integrity" by Continuous Monitoring. Proceedings of the 2018 International Conference on Mathematics, Modelling, Simulation and Algorithms (MMSA 2018). Atlantis Press, Chengdu, China; 2018. p. 432-435. (In Eng.) doi: https://doi.org/10.2991/mmsa-18.2018.96
15. Kostogryzov A., Korolev V. Probabilistic Methods for Cognitive Solving of Some Problems in Artificial Intelligence Systems. In: Kostogryzov A., Korolev V. (eds.) Probability, Combinatorics and Control. IntechOpen, London; 2019. p. 3-34. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.89168
16. Kostogryzov A., Makhutov N., Nistratov A., Reznikov G. Probabilistic Predictive Modelling for Complex System Risk Assessments. In: Abdalla R., El-Diasty M., Kostogryzov A., Makhutov N.A. (ed.) Time Series Analysis ‒ New Insights. London: IntechOpen; 2022. (In Eng.) doi: http://dx.doi.org/10.5772/intechopen.106869
17. Akundi A., Lopez V. A Review on Application of Model Based Systems Engineering to Manufacturing and Production Engineering Systems. Procedia Computer Science. 2021; 185:101-108. (In Eng.) doi: https://doi.org/10.1016/j.procs.2021.05.011
18. Kołowrocki K., Soszyńska-Budny J. Reliability and Safety of Complex Technical Systems and Processes. Springer Series in Reliability Engineering. Springer London; 2011. 405 p. (In Eng.) doi: https://doi.org/10.1007/978-0-85729-694-8
19. Kołowrocki K., Soszyńska-Budny J. Prediction of critical infrastructures safety. The 10th International Conference on Digital Technologies 2014. IEEE Press; 2014. p. 130-138. (In Eng.) doi: https://doi.org/10.1109/DT.2014.6868704
20. Zio E. An Introduction to the Basics of Reliability and Risk Analysis. World Scientific Publishing Co Pte Ltd; 2007. 236 p. (In Eng.) doi: https://doi.org/10.1142/6442
21. Eid M., Rosato V. Critical Infrastructure Disruption Scenarios Analyses via Simulation. In: Setola R., Rosato V., Kyriakides E., Rome E. (eds.) Managing the Complexity of Critical Infrastructures. Studies in Systems, Decision and Control. Vol. 90. Springer, Cham; 2016. p. 43-61. (In Eng.) doi: https://doi.org/10.1007/978-3-319-51043-9_3
22. Gneiting T., Balabdaoui F., Raferty A.E. Probabilistic forecasts, calibration and sharpness. Journal of the Royal Statistical Society. Series B (Statistical Methodology). 2007; 69(2):243-268. (In Eng.) doi: https://doi.org/10.1111/j.1467-9868.2007.00587.x
23. Meridji K., Issa G. A development approach of software requirements for renewable energy applications using fundamental principles of software engineering. 2013 1st International Conference & Exhibition on the Applications of Information Technology to Renewable Energy Processes and Systems. IEEE Press; 2013. p. 107-112. (In Eng.) doi: https://doi.org/10.1109/IT-DREPS.2013.6588162
24. Wisniewski M., Gladysz B., Ejsmont K., Wodecki A., Van Erp T. Industry 4.0 Solutions Impacts on Critical Infrastructure Safety and Protection ‒ A Systematic Literature Review. IEEE Access. 2022; 10:82716-82735. (In Eng.) doi: https://doi.org/10.1109/ACCESS.2022.3195337
25. Shah L., Siadat A., Vernadat F. Maturity assessment in risk management in manufacturing engineering. 2009 3rd Annual IEEE Systems Conference. IEEE Press; 2009. p. 296-301. (In Eng.) doi: https://doi.org/10.1109/SYSTEMS.2009.4815815
Published
2022-07-20
How to Cite
KOSTOGRYZOV, Andrey Ivanovich.
To the Methods of System Engineering.
Modern Information Technologies and IT-Education, [S.l.], v. 18, n. 2, p. 227-240, july 2022.
ISSN 2411-1473. Available at: <http://sitito.cs.msu.ru/index.php/SITITO/article/view/868>. Date accessed: 14 sep. 2025.
doi: https://doi.org/10.25559/SITITO.18.202202.227-240.
Section
Theoretical Questions of Computer Science, Computer Mathematics
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