RESEARCH PAPER
Risk assessment of a production system based on a technological description model
1
Wrocław University of Science and Technology, Poland
2
Kharkiv Polytechnic Institute, National Technical University, Ukraine
Submission date: 2025-02-13
Final revision date: 2025-03-27
Acceptance date: 2025-05-01
Online publication date: 2025-05-03
Publication date: 2025-05-03
Eksploatacja i Niezawodność – Maintenance and Reliability 2026;28(2):204577
HIGHLIGHTS
- Method for assessing the risk of exceeding production time in manufacturing process.
- Risk calculation considers technological route structure and statistical operation traits.
- Factors of equipment breakdown and adjustment states are included in risk calculation.
- Method estimates processing time and losses due to unproduced parts.
- A production line with seven sequential operations is analyzed for risk assessment.
KEYWORDS
reliabilityrisk assessmentProduction riskproduction system modelrandom process realizationtransport delay
TOPICS
ABSTRACT
The paper presents a method for assessing the risk of exceeding the agreed production time for a batch of products using the statistical modeling of a production system. The approach considers the structure of the technological route and statistical characteristics of operations. It accounts for both the probability of a given state, such as equipment failure or adjustment, and the distribution of time spent in that state. A production line with seven sequential operations is analyzed. Risk is defined as the probability that production time will exceed the planned order completion time. The method estimates total processing time and potential losses due to unproduced parts. The results show that batch processing time follows a distribution close to the normal law. This provides a basis for optimizing the exploitation and reliability of manufacturing systems, ensuring their efficiency and reducing downtime.
REFERENCES (29)
1.
Ahmad Jaber, T., Mohammed Shah, S.: Enterprise risk management literature: emerging themes and future directions. Journal of Accounting & Organizational Change, 20(1), 84-111, (2024).
2.
Chairani, C., Siregar, S. V.: The effect of enterprise risk management on financial performance and firm value: the role of environmental, social and governance performance. Meditari Accountancy Research, 29(3), 647-670, (2021).
3.
Zhang, C., Zhang, Y., Dui, H., Wang, S., and Tomovic, M. (2023). Component Maintenance Strategies and Risk Analysis for Random Shock Effects Considering Maintenance Costs. Eksploatacja i Niezawodność – Maintenance and Reliability, 25(2). https://doi.org/10.17531/ein/1....
4.
International Organization for Standardization. ISO 9001:2015 Quality management systems – Requirements. Geneva, Switzerland: ISO; 2015.
5.
International Organization for Standardization. ISO 31000:2018 Risk management – Principles and guidelines. Geneva, Switzerland: ISO; 2018.
6.
International Organization for Standardization. ISO 31010:2019 Risk management – Risk assessment techniques. Geneva: ISO; 2019.
7.
Araújo Lima, P. F., Crema, M., Verbano, C.: Risk management in SMEs: A systematic literature review and future directions. European Management Journal, 38(1), 78-94, (2020).
8.
Fraser, J. R., Quail, R., Simkins, B. J. Questions asked about enterprise risk management by risk practitioners. Business Horizons, 65(3), 251-260, (2022).
9.
Aven T.: The reliability science: Its foundation and link to risk science and other sciences. Reliability Engineering & System Safety, vol. 215, 107863, (2021).
10.
Wu, Z., Liu, W., Nie, W.: Literature review and prospect of the development and application of FMEA in manufacturing industry. The International Journal of Advanced Manufacturing Technology, 112, 1409-1436, (2021).
11.
Rishabh, S., Prashant, C.: Modelling of risk analysis in production system. IOP Conf. Ser.Mater. Sci. Eng. 691(1), 012087, (2019).
12.
Simon P., Zeiträg Y., Glasschroeder J., Gutowski, T., Reinhart G.: Approach for a Risk Analysis of Energy Flexible Production Systems. Procedia CIRP No.72, pp. 677-682, (2018).
13.
Dąbrowska, M., Medyński, D., Łapczyńska, D., Burduk, A., Pihnastyi, O.: Assessment of Risk and Production Losses Based on a Selected Carpentry Company. In: Hamrol, A., Grabowska, M., Hinz, M. (eds) Advances in Manufacturing IV. MANUFACTURING 2024. Lecture Notes in Mechanical Engineering. Springer, Cham, (2024). https://doi.org/10.1007/978-3-....
14.
Pihnastyi, O., Analytical methods for designing technological trajectories of the object of labour in a phase space of states, Scientific bulletin of National Mining University (2017). №.4. P. 104–111. http://nvngu.in.ua/index.php/e....
15.
Pihnastyi O. Statistical theory of control systems of the flow production. / O.M. Pihnastyi LAP LAMBERT Academic Publishing. –2018. – 436 с. –ISBN: 978-613-9-95512-1.
16.
Pałęga, M. Ł., Rydz, D., Salwin, M., Lewczuk, K., and Chmielewski, T. (2024). Occupational safety management and human reliability testing during the operation of a plastic injection molding machine. Eksploatacja i Niezawodność – Maintenance and Reliability, 26(4). https://doi.org/10.17531/ein/1....
17.
Kabir, S., & Papadopoulos, Y.: Applications of Bayesian networks and Petri nets in safety, reliability, and risk assessments: A review. Safety science, 115, 154-175, (2019).
18.
Aven T.: Risk, surprises and black swans: fundamental ideas and concepts in risk assessment and risk management. Routledge, (2014).
19.
Nepal B.P., Yadav O., Monplaisir L., Murat A.: A framework for capturing and analyzing the failures due to system/component interactions. Quality and Reliability Engineering International, 24(3), pp. 265-289, (2008). https://doi.org/10.1002/qre.89....
20.
Kerstin D., Simone O., Nicole Z.: Challenges in implementing enterprise risk management. ACRN Journal of Finance and Risk Perspectives, Vol. 3, No. 3, pp. 1-14, (2014). https://www.acrn-journals.eu/r...
21.
Serrano-Ruiz JC, Mula J, Poler R. (2022), Development of a multidimensional conceptual model for job shop smart manufacturing scheduling from the Industry 4.0 perspective. J Manuf Syst. 2022;63:185-202. https://doi.org/10.1016/j.jmsy....
22.
Horlick-Jones T., Rosenhead J., Georgiou I., Ravetzd J., Löfstedte R.: Decision support for organisational risk management by problem structuring. Health, Risk & Society, Vol. 3, No. 2, pp. 141-165, (2001). https://doi.org/10.1080/136985....
23.
Łapczyńska D., Burduk A.: Fuzzy FMEA Application to Risk Assessment of Quality Control Process. International Workshop on Soft Computing Models in Industrial and Environmental Applications, pp. 309-319, Springer, Cham, (2020). https://doi.org/10.1007/978-3-....
24.
Iranzadeh, S.: Investigating the relationship between RPN parameters in fuzzy PFMEA and OEE in a sugar factory. Journal of Loss Prevention in the Process Industries, 60, 221-232, (2019). https://doi.org/10.1080/133167....
25.
Sawhney R., Subburaman K. et al.: A modified FMEA approach to enhance reliability of lean systems. International Journal of Quality & Reliability Management, Vol. 22 No. 9, pp. 986-1004 (2010). https://doi.org/10.1108/026567....
26.
Prasetyo V., Rahardjo J.: The use of the Lean Method and Failure Mode and Effects Analysis (FMEA) on Product Costing-An. Implementation in Automotive Battery Manufacturing, International Journal of Industrial Research and Applied Engineering, Vol. 4, No. 1, pp. 13-20, (2020). https://doi.org/10.9744/jirae.....
27.
Von Bertalanffy, L., & Sutherland, J. W.: General systems theory: Foundations, developments, applications. IEEE Transactions on Systems, Man, and Cybernetics, (6), 592-592, (1974). https://doi.org/10.1109/TSMC.1....
28.
Aven, T.: Reliability and Risk Analysis. Springer, London (2012). https://doi.org/10.1007/978-0-....
29.
Pihnastyi O. (2014). Fundamentals of the statistical theory of the construction of continuum models of production lines. Eastern-European Journal of Enterprise Technologies, 4(3(70), 38–48. https://doi.org/10.15587/1729-....
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| eISSN: | 2956-3860 |
| ISSN: | 1507-2711 |
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