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The Mathematical Model for Describing the Principles of Enterprise Management “Just in Time, Design to Cost, Risks Management”

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Recent Research in Control Engineering and Decision Making (ICIT 2019)

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 199))

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Abstract

The formalization of the principles “just in time”, “design to cost” and “risks management” is described in the form of a mathematical model. These principles are chosen on the basis of the analysis of the management methodologies used in the practice of industrial enterprises. The model is recommended to be used in the design of information systems to support management decisions. The model can be built on the basis of different methods: stochastic, parametric, heuristic, etc. The proposed approach allows to use heterogeneous submodels for the assessment and management task based on one or more specific criteria: just in time, design to cost and risks management.

The proposed mathematical model is a model of the upper level of abstraction, in practical use it is required to take into account the task being solved, selected criteria and available limitations. Practical implementation of the proposed model and its introduction into digital production presuppose the implementation and monitoring with the help of an information system. The use of such a methodology is advisable at large enterprises, in particular machine building and aviation.

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References

  1. Aven, T.: Risk assessment and risk management: review of recent advances on their foundation. Eur. J. Oper. Res. 253(1), 1–13 (2016)

    Article  MathSciNet  Google Scholar 

  2. Aven, T.: Risk analysis validation and trust in risk management: a postscript. Saf. Sci. 99(part B), 255–256 (2017)

    Article  Google Scholar 

  3. Baklashov, V.I., Kazanskaya, D.N., Skobelev, P.O., Shpilevoy, V.F., Shepilov, Y.Y.: Multi-agent system “Smart Factory” for strategic and operational management of machine-building production “Just in time” and “For a given price”. Izvestiya Samara Sci. Center Russ. Acad. Sci. 16, 1292–1295 (2014). 1(5). (in Russian)

    Google Scholar 

  4. Che-Ani, M.N., Kamaruddin, S., Azid, I.A.: Towards just-in-time (JIT) production system through enhancing part preparation process. In: Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, pp. 669–673. IEEE (2017)

    Google Scholar 

  5. Chursin, A.A., Davydov, V.A.: Economic and mathematical model of the impact of risks on the competitiveness of enterprises of the rocket and space industry. Econ. Manag. Eng. 5, 46–52 (2012). (in Russian)

    Google Scholar 

  6. Denkena, B., Horst, P., Schmidt, C., Behr, M., Krieglsteiner, J.: Estimation of production cost in an early design stage of CFRP lightweight structures. Proc. CIRP 62, 45–50 (2017)

    Article  Google Scholar 

  7. Feduzi, A., Runde, J.: Uncovering unknown unknowns: towards a Baconian approach to management decision-making. Org. Behav. Hum. Decis. Process. 124, 268–283 (2014)

    Article  Google Scholar 

  8. Flage, R., Aven, T., Baraldi, P., Zio, E.: Concerns, challenges and directions of development for the issue of representing uncertainty in risk assessment. Risk Anal. 34(7), 1196–1207 (2014)

    Article  Google Scholar 

  9. Flage, R., Aven, T.: Emerging risk—conceptual definition and a relation to black swan types of events. Reliab. Eng. Syst. Saf. 144, 61–67 (2015)

    Article  Google Scholar 

  10. Gabrel, V., Murat, C., Thiele, A.: Recent advances in robust optimization: an overview. Eur. J. Oper. Res. 235, 471–483 (2014)

    Article  MathSciNet  Google Scholar 

  11. Giannakis, M., Papadopoulos, T.: Supply chain sustainability: a risk management approach. Int. J. Prod. Econ. 171(4), 455–470 (2016)

    Article  Google Scholar 

  12. Goerlandt, F., Khakzad, N., Reniers, G.: Validity and validation of safety-related quantitative risk analysis: a review. Saf. Sci. 99(part B), 127–139 (2017). https://doi.org/10.1016/j.ssci.2016.08.023

    Article  Google Scholar 

  13. Guskova, T.N., Spiridonova, E.E.: Static methodology and practical issues of risk management. Bull. Volga State Univ. Serv. Series: Econ. 1(47), 87–93 (2017). (in Russian)

    Google Scholar 

  14. Hansson, S.O., Aven, T.: Is risk analysis scientific? Risk Anal. 34(7), 1173–1183 (2014)

    Article  Google Scholar 

  15. Heckmann, I., Comes, T., Nickel, S.: A critical review on supply chain risk—Definition, measure and modeling. Omega 52, 119–132 (2015)

    Article  Google Scholar 

  16. Jardini, B., Kyal, M.E., Amri, M.: The management of the supply chain by the JIT system (Just in Time) and the EDI technology (Electronic Data Interchange). In: Proceedings of the 3rd IEEE International Conference on Logistics Operations Management, Article ID 7731712 (2016)

    Google Scholar 

  17. Khan, F., Rathnayaka, S., Ahmed, S.: Methods and models in process safety and risk management: past, present and future. Process Saf. Environ. Prot. 98, 116–147 (2015)

    Article  Google Scholar 

  18. Klochkov, V.V., Vdovenkov, V.A.: The problem of ensuring the production of aviation equipment “Just in time” and the concept of “fast-reacting production”. Izvestiya Samara Sci. Center Russ. Acad. Sci. 16, 1418–1425 (2014). 1(5). (in Russian)

    Google Scholar 

  19. Li, X., Guo, S., Liu, Y., Du, B., Wang, L.: A production planning model for make-to-order foundry flow shop with capacity constraint. Math. Probl. Eng. (2017). https://doi.org/10.1155/2017/6315613

    Google Scholar 

  20. Liu, L., Wang, J.J., Liu, F., Liu, M.: Single machine-by-product planning and resource allocation scheduling problem with learning and general positional effects. J. Manuf. Syst. 43, 1–14 (2017)

    Article  Google Scholar 

  21. Lundberg, J., Johansson, B.J.E.: Systemic resilience model. Reliab. Eng. Syst. Saf. 141, 22–32 (2015)

    Article  Google Scholar 

  22. Lutoshkin, I.V.: The parameterization method for optimizing the systems which have integro-differential equations. Bull. Irkutsk State Univ. Series “Mathematics” 4(1), 44–56 (2011). (in Russian)

    MATH  Google Scholar 

  23. Malek, R., Baxter, B., Hsiao, C.: A decision-based perspective on assessing system robustness. Proc. Comput. Sci. 44, 619–629 (2015)

    Article  Google Scholar 

  24. Pasman, H., Reniers, G.: Past, present and future of Quantitative Risk Assessment (QRA) and the incentive it obtained from Land-Use Planning (LUP). J. Loss Prev. Process Ind. 28, 2–9 (2014)

    Article  Google Scholar 

  25. Petrenya, Y.K., Glukhov, V.V., Shilin, P.S.: The concept of “designing for competition” as the basis for the formation of an innovative enterprise policy. Econ. Sci. 10(1), 155–163 (2017). Scientific and technical statements of the St. Petersburg State Polytechnic University. (in Russian)

    Google Scholar 

  26. Sahebjamnia, N., Torabi, S.A., Mansouri, S.A.: Innovative applications of O.R. integrated business continuity and disaster recovery planning: towards organizational resilience. Eur. J. Oper. Res. 242, 261–273 (2015)

    Article  Google Scholar 

  27. Spiegelhalter, D.J., Riesch, H.: Don’t know, can’t know: embracing deeper uncertainties when analysing risks. Philos. Trans. Roy. Soc. A 369, 4730–4750 (2014)

    Article  MathSciNet  Google Scholar 

  28. SRA: Glossary society for risk analysis (2015). www.sra.com/resources. Accessed 14 Aug 2018

  29. Turnbull, P., Oliver, N., Wilkinson, B.: Buyer-supplier relations in the UK - automotive industry: strategic implications of the Japanese manufacturing model. Strateg. Manag. J. 13, 159–168 (1992)

    Article  Google Scholar 

  30. Zahedi, R., Yusriski, R.: Stepwise optimization for model of integrated batch production and maintenance scheduling for single item processed on flow shop with two machines in JIT environment. Proc. Comput. Sci. 116, 408–420 (2017)

    Article  Google Scholar 

  31. http://www.uacrussia.ru/en/corporation/. Accessed 01 June 2018

  32. Wang D., Chen Y., Chen D.: Efficiency optimization and simulation to manufacturing and service systems based on manufacturing technology Just-In-Time. Pers. Ubiquit. Comput. 22, 1–13 (2018)

    Article  Google Scholar 

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Acknowledgements

Work carried out in the framework of the state task 2.1816.2017/PCH Ministry of Education and Science of the Russian Federation.

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Authors and Affiliations

  1. Ulyanovsk State University, L. Tolstoy 42, Ulyanovsk, 432017, Russia

    Igor Lutoshkin, Svetlana Lipatova, Yuriy Polyanskov, Nailya Yamaltdinova & Margarita Yardaeva

Authors
  1. Igor Lutoshkin
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  2. Svetlana Lipatova
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  3. Yuriy Polyanskov
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  4. Nailya Yamaltdinova
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  5. Margarita Yardaeva
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Corresponding author

Correspondence to Igor Lutoshkin .

Editor information

Editors and Affiliations

  1. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Olga Dolinina

  2. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Alexander Brovko

  3. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Vitaly Pechenkin

  4. Institute of Applied Information Technologies and Communication, Yuri Gagarin State Technical University of Saratov, Saratov, Russia

    Alexey Lvov

  5. Department of Automation, Novosibirsk State Technical University, Novosibirsk, Russia

    Vadim Zhmud

  6. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

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Lutoshkin, I., Lipatova, S., Polyanskov, Y., Yamaltdinova, N., Yardaeva, M. (2019). The Mathematical Model for Describing the Principles of Enterprise Management “Just in Time, Design to Cost, Risks Management”. In: Dolinina, O., Brovko, A., Pechenkin, V., Lvov, A., Zhmud, V., Kreinovich, V. (eds) Recent Research in Control Engineering and Decision Making. ICIT 2019. Studies in Systems, Decision and Control, vol 199. Springer, Cham. https://doi.org/10.1007/978-3-030-12072-6_55

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