Certificate of Registration Media number Эл #ФС77-53688 of 17 April 2013. ISSN 2308-6033. DOI 10.18698/2308-6033
  • Русский
  • Английский

The concept of operational readiness of a multifunctional technical system based on creating individual maintenance models of its components

Published: 25.06.2021

Authors: Zerkin D.G., Tsybakin K.A., Shibanov Y.A.

Published in issue: #6(114)/2021

DOI: 10.18698/2308-6033-2021-6-2089

Category: Aviation and Rocket-Space Engineering | Chapter: Innovation Technologies of Aerospace Engineering

The scheduled preventive system of weapon maintenance and repair currently in use in the Armed Forces of the Russian Federation does not adequately correspond to the engineering level of modern multifunctional technical systems. This maintenance and repair system allows assessing the technical condition of multifunctional technical systems with the established diagnostic level, but does not allow predicting their short- and medium-term technical condition. As a result, there is a lack of complete information on the actual technical condition of multifunctional technical systems, which increases the risk of their inoperability at the time of intended use. In addition, the inability to predict the operability of multifunctional technical systems prevents timely detection and anticipation of failures and malfunctions. This leads to unplanned inoperability by reducing the alert readiness rate, and as a consequence, to significant corrective and preventive maintenance costs. Analysis of the technical conditions of multifunctional technical systems shows that the existing preventive maintenance and repair system makes it increasingly more difficult to ensure the required level of the specified operational and technical characteristics. The development and implementation of built-in automated control and diagnostic systems can provide numerical values of multifunctional technical system parameters in real time, to objectively assess their actual technical condition and predict the technical condition for a certain period of operation. These circumstances objectively raise the issue of improving the existing preventive maintenance and repair system and developing an individual system for sustaining the operational readiness of multifunctional technical systems.
This paper presents the conceptual foundations of operational readiness of a multifunctional technical system based on the individual assessment of the technical state of its components and adaptive-situational management of the readiness sustainment process. The proposed approach is based on the creation of an individual technical state model for a multifunctional technical system, assessing and predicting its technical state, and adjusting the readiness sustainment program through adaptive situational management. The proposed approach ensures the required level of readiness and reliability of multifunctional technical systems operating in a dynamically changing environment.

[1] Rembeza A.I. Nadjozhnost i effektivnost v tekhnike. T. 1: Metodologiya. Organizatsiya. Terminologiya [Reliability and efficiency in technology. Vol. 1: Methodology. Organization. Terminology]. Mosсow, Mashinostroenie Publ., 1986, 224 p.
[2] Truhanov V.M. Nadjozhnost tekhnicheskih system [Reliability of technical systems]. Moscow, Mashinostroenie-1 Publ., 2008, 585 p.
[3] Russel S., Norvig P. Artificial Intelligence: A Modern Approach. 2nd ed., Pearson, 2003, 1132 p. [In Russ.: Russel S., Norvig P. Iskusstvenny intellekt. Sovremenny podkhod. Moscow, Vilyams Publ., 2006, 1408 p.].
[4] Santalainen T., Voutilainen E., Porenne P., Nissenen J. Upravlenie po rezultatu [Management by results]. Moscow, Progress, Univers Publ., 1993, 320 p. (In Russ.).
[5] Alan Bundy, ed. Artificial Intelligence Techniques. Springer Verlag, 1997, 129 p.
[6] Efendiev B.A. Rossiiskoe predprinimatelstvo — Russian Journal of Entrepreneurship, 2008, vol. 9, no. 11, pp. 21–25.
[7] Zerkin D.G. Vestnik MGOU — Bulletin of the MRSU, 2014, no. 2, pp. 16–18.
[8] Althof K.-D., Auriol E., Barlette R., Manago M. A Review of Industrial Case-Based Reasoning Tools, AI Intelligence, 1995.
[9] Anand S.S., Hughes J.G., Bell D.A., Hamilton P. Utilising Censored Neighbours in Prognostication, Workshop on Prognostic Models in Medicine. Ameen AbuHanna, Peter Lucas, eds. Aalborg (AIMDM’99), Denmark, 1999, pp. 15–20.
[10] Kuzmenko V.V., Grishin D.V. Vestnik SevKavGTU. Seriya «Ekonomika» — Newsletter of North-Caucasus Federal University. Economic Sciences, 2003, no. 2 (10). ISBN 5-9296-0140-2.