Skip to main content
Top
Published in: Automatic Documentation and Mathematical Linguistics 5/2023

01-10-2023 | INFORMATION PROCESSES

Efficiency of the Design Processes for Complex Systems with the Mathematical Apparatus of Fuzzy Sets

Authors: S. G. Tsapko, I. V. Tsapko, D. V. Tarakanov

Published in: Automatic Documentation and Mathematical Linguistics | Issue 5/2023

Login to get access

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

An analysis of methods for evaluating the effectiveness of complex system design processes is presented, and formal indicators for assessing their quality based on the mathematical apparatus of fuzzy sets are proposed. A complex system, such as a model of the business processes of designing, testing, and manufacturing (creating) on-board radio-electronic equipment was chosen as the basis, involving multiple departments of the enterprise, from managers, circuit designers, and designers to the procurement department, testing workshops, and support services. It is proposed to consider all components of business processes as resources, to identify material, labor, financial, temporal, hardware, and software resources among them, establish a connection between them, and evaluate the weight coefficients of the connections to find the most effective implementation of the complex system design process using a radar diagram of relative quality indicators. An E-network logical-dynamic model of project design work execution is used to evaluate the efficiency of each resource over time and calculate the integrated efficiency indicator of the life cycle business processes of creating a complex system. This model allows for the consideration of dynamic characteristics of parallel interacting departments and project stages. Based on the fuzzy set apparatus, an approach to evaluating the effectiveness of each stage of the complex system creation project is considered, which in turn allows for the uncertainty and fuzziness in evaluation to be taken into account and determine the importance of each criterion based on investor preferences. This helps make informed decisions about building an investment portfolio and achieving desired financial goals.
Literature
1.
go back to reference Fuzzy Sets and Decision Analysis, Zimmermann, H.J., Zadeh, L.A., and Gaines, A.R., Eds., New York: North Holland, 1984.MATH Fuzzy Sets and Decision Analysis, Zimmermann, H.J., Zadeh, L.A., and Gaines, A.R., Eds., New York: North Holland, 1984.MATH
2.
go back to reference Klir, G.J. and Yuan, B., Fuzzy Sets and Fuzzy Logic: Theory and Applications, Upper Saddle River, N.J.: Prentice Hall, 1995.MATH Klir, G.J. and Yuan, B., Fuzzy Sets and Fuzzy Logic: Theory and Applications, Upper Saddle River, N.J.: Prentice Hall, 1995.MATH
3.
go back to reference Demidova, G.L. and Lukichev, D.V., Regulyatory na osnove nechetkoi logiki v sistemakh upravleniya tekhnicheskimi ob’’ektami (Fuzzy Logic-Based Regulators in Control Systems of Engineering Objects), St. Petersburg: S.-Peterb. Nats. Issled. Univ. Informatsionnykh Tekhnologii, 2017. Demidova, G.L. and Lukichev, D.V., Regulyatory na osnove nechetkoi logiki v sistemakh upravleniya tekhnicheskimi ob’’ektami (Fuzzy Logic-Based Regulators in Control Systems of Engineering Objects), St. Petersburg: S.-Peterb. Nats. Issled. Univ. Informatsionnykh Tekhnologii, 2017.
4.
go back to reference Zinov’ev, I.P. and Anikin, I.V., Logic inference model based on fuzzy linear regression, Nauchn.-Tekh. Vedomosti S.-Peterb. Gos. Politekh. Univ. Inf., Telekommunikatsii. Upr., 2023, no. 5, pp. 139–145. https://cyberleninka.ru/article/n/model-logicheskogo-vyvoda-na-osnove-nechetkoy-lineynoy-regressii. Cited May 11, 2023. Zinov’ev, I.P. and Anikin, I.V., Logic inference model based on fuzzy linear regression, Nauchn.-Tekh. Vedomosti S.-Peterb. Gos. Politekh. Univ. Inf., Telekommunikatsii. Upr., 2023, no. 5, pp. 139–145. https://​cyberleninka.​ru/​article/​n/​model-logicheskogo-vyvoda-na-osnove-nechetkoy-lineynoy-regressii.​ Cited May 11, 2023.
6.
go back to reference Ptuskin, A.S., Levner, E., and Zhukova, Yu.M., A multicriteria model of determining the best available technology under fuzzy input data, Vestn. MGTU N.E. Baumana. Ser. Mashinostr., 2016, no. 6, pp. 105–127. https://cyberleninka.ru/article/n/mnogokriterialnaya-model-opredeleniya-nailuchshey-dostupnoy-tehnologii-pri-nechetkih-ishodnyh-dannyh. Cited May 11, 2023. Ptuskin, A.S., Levner, E., and Zhukova, Yu.M., A multicriteria model of determining the best available technology under fuzzy input data, Vestn. MGTU N.E. Baumana. Ser. Mashinostr., 2016, no. 6, pp. 105–127. https://​cyberleninka.​ru/​article/​n/​mnogokriterialna​ya-model-opredeleniya-nailuchshey-dostupnoy-tehnologii-pri-nechetkih-ishodnyh-dannyh.​ Cited May 11, 2023.
9.
go back to reference Polozyuk, O.E., Optimization of technological processes using the apparatus of fuzzy set theory, Visn. Priazovskogo Derzhavnogo Tekh. Univ., 2001, no. 11. https://cyberleninka.ru/article/n/optimizatsiya-tehnologicheskih-protsessov-s-ispolzovaniem-apparata-teorii-nechetkih-mnozhestv. Cited May 11, 2023. Polozyuk, O.E., Optimization of technological processes using the apparatus of fuzzy set theory, Visn. Priazovskogo Derzhavnogo Tekh. Univ., 2001, no. 11. https://​cyberleninka.​ru/​article/​n/​optimizatsiya-tehnologicheskih​-protsessov-s-ispolzovaniem-apparata-teorii-nechetkih-mnozhestv.​ Cited May 11, 2023.
14.
go back to reference Yang, K.-M., Kim, E.-H., Hwang, S.-H., and Choi, S.-H., Conceptual analysis of fuzzy data using FCA, Proc. 8th WSEAS Int. Conf. on Applied Computer Science (ACS’08), Venice, 2008, Stevens Point, Wis.: World Sci. and Eng. Acad. and Society, 2008, pp. 37–42. Yang, K.-M., Kim, E.-H., Hwang, S.-H., and Choi, S.-H., Conceptual analysis of fuzzy data using FCA, Proc. 8th WSEAS Int. Conf. on Applied Computer Science (ACS’08), Venice, 2008, Stevens Point, Wis.: World Sci. and Eng. Acad. and Society, 2008, pp. 37–42.
15.
go back to reference Lu, P. and Jiang, X., Fuzzy bidirectional weighted sum for face recognition, Open Autom. Control Syst. J., 2015, vol. 6, pp. 447–452.CrossRef Lu, P. and Jiang, X., Fuzzy bidirectional weighted sum for face recognition, Open Autom. Control Syst. J., 2015, vol. 6, pp. 447–452.CrossRef
Metadata
Title
Efficiency of the Design Processes for Complex Systems with the Mathematical Apparatus of Fuzzy Sets
Authors
S. G. Tsapko
I. V. Tsapko
D. V. Tarakanov
Publication date
01-10-2023
Publisher
Pleiades Publishing
Published in
Automatic Documentation and Mathematical Linguistics / Issue 5/2023
Print ISSN: 0005-1055
Electronic ISSN: 1934-8371
DOI
https://doi.org/10.3103/S0005105523050096

Other articles of this Issue 5/2023

Automatic Documentation and Mathematical Linguistics 5/2023 Go to the issue

Premium Partner