Determination of sustainable levels of design alternatives selection in the workflow cap system


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Abstract

The development of the mechanical treatment workflow CAP system is aimed at the solution of a crucial task of reduction of terms and the improvement of quality of multiproduct machining manufactures work preparation, as the existing workflow CAP systems have not got the possibility of fast response to changes in a production situation often arising within the multiproduct manufacture. The authors of this paper developed the workflow CAP system, which contains the requirements of the design activity full automation, design solution multivariance, and the feedback with the engineering process implementation subsystem. The paper deals with the development of a mathematical model and the technique of searching for sustainable levels of selecting design alternatives depending on the production situation for the whole design procedures of the workflow CAP system. The authors prove the application of a mathematical tool of genetic algorithms; describe the mathematical model using its terms. As a gene, the level of selection in a separate project procedure is specified. A chromosome is a set of genes according to the project procedures. The objective function determines the minimum total time of processing of the specified nomenclature of parts based on the ranges of gene aggregates resulting from crossing and mutation operations. The result of the work is the mathematical model and the technique for identifying the sustainable levels of selection in each project procedure ensuring the possibility of self-adjustment of the workflow CAP system depending on the production situation.

About the authors

Sergey G. Mitin

Kamyshin Institute of Technology (branch) of Volgograd State Technical University, Kamyshin (Russia)

Email: fake@neicon.ru
ORCID iD: 0000-0001-6709-0424

Doctor of Sciences (Engineering), Associate Professor, professor of Chair of Mechanical Engineering and Applied Mechanics

Russian Federation

Petr Yu. Bochkarev

Kamyshin Institute of Technology (branch) of Volgograd State Technical University, Kamyshin (Russia); Saratov State Vavilov Agrarian University, Saratov (Russia)

Author for correspondence.
Email: bpy@mail.ru
ORCID iD: 0000-0003-0587-6338

Doctor of Sciences (Engineering), Professor, professor of Chair of Mechanical Engineering and Applied Mechanics, professor of Chair of Engineering Support of AIC

Russian Federation

Vyacheslav V. Shalunov

V.I. Razumovsky Saratov State Medical University, Saratov (Russia)

Email: fake@neicon.ru
ORCID iD: 0000-0002-9908-232X

PhD (Engineering), Associate Professor, assistant professor of Chair of Teaching, Education Technologies and Business Communications

Russian Federation

Ivan A. Razmanov

Gazsnabinvest JSC, Saratov (Russia)

Email: fake@neicon.ru
ORCID iD: 0000-0003-1921-057X

researcher, leading design engineer

Russian Federation

References

  1. Tsvetkov V.D. Sistemno-strukturnoe modelirovanie i avtomatizatsiya proektirovaniya tekhnologicheskikh protsessov [The systemic-structural modeling and business process design automation]. Minsk, Nauka i tekhnika Publ., 1979. 264 p.
  2. Mitrofanov S.P. Gruppovaya tekhnologiya mashinostroitelnogo proizvodstva. Organizatsiya gruppovogo proizvodstva [Group technology of mechanical production. Organization of group production]. 3rd ed., pererab. i dop. Leningrad, Mashinostroenie, Leningradskoe otdelenie Publ., 1983. Vol. 1, 407 p.
  3. Bazrov B.M. Modular processing and its application in mechanical assembly production. Naukoemkie tekhnologii v mashinostroenii, 2014, no. 7, pp. 24–30.
  4. Averchenkov A.V. Improving the efficiency of virtual preparation of production on the basis of selection of optimal cutting tool and strategies for treatment. Vestnik Tambovskogo gosudarstvennogo tekhnicheskogo universiteta, 2011, vol. 17, no. 3, pp. 767–774.
  5. Yusof Y., Latif K. Survey on computer-aided process planning. International Journal of Advanced Manufacturing Technology, 2014, vol. 75, no. 1-4, pp. 77–89.
  6. Xu X., Wang L., Newman S.T. Computer-aided process planning – A critical review of recent developments and future trends. International Journal of Computer Integrated Manufacturing, 2011, vol. 24, no. 1, pp. 1–31.
  7. Kulikov D.D., Padun B.S., Yablochnikov E.I. Perspectives of automation of technological preproduction. Izvestiya vysshikh uchebnykh zavedeniy. Priborostroenie, 2014, vol. 57, no. 8, pp. 7–11.
  8. Andrichenko A.N. Three generations of domestic CAD/CAM. Stankoinstrument, 2017, no. 1, pp. 56–63.
  9. Evgenev G.B., Kryukov S.S., Kuzmin B.V., Stises A.G. An integrated process automation and operations management system. Izvestiya vysshikh uchebnykh zavedeniy. Mashinostroenie, 2015, no. 3, pp. 49–60.
  10. Milovzorov O.V. Realization of synthesis principles of technological processes using generalized structure on the basis of T-flex technology. Vestnik Ryazanskogo gosudarstvennogo radiotekhnicheskogo universiteta, 2015, no. 54-1, pp. 133–138.
  11. Dolgov V.A. Increase of effectiveness of multiproduct limited production by adaptation of engineering process to current status of the technological system. Vestnik MGTU Stankin, 2011, no. 3, pp. 83–87.
  12. Bochkarev P.Yu. System representation of planning technological machining process. Tekhnologiya mashinostroeniya, 2002, no. 1, pp. 10–14.
  13. Mitin S.G., Bochkarev P.Yu. Principles of creating the system of computer-aided design of production operations in multiproduct manufacturing. Vektor nauki Tolyattinskogo gosudarstvennogo universiteta, 2015, no. 2-2, pp. 117–122.
  14. Razmanov I.A., Mitin S.G., Bochkarev P.Yu. Improving the efficiency of technological preparation of diversified production based on the development of a system of indicators to assess the level of design solutions. Izvestiya Volgogradskogo gosudarstvennogo tekhnicheskogo universiteta, 2017, no. 9, pp. 132–134.
  15. Razmanov I.A., Mitin S.G., Bochkarev P.Yu. The formation of project procedures ranking technique in the system of planning of multiproduct engineering processes. Vektor nauki Tolyattinskogo gosudarstvennogo universiteta, 2019, no. 1, pp. 58–63. doi: 10.18323/2073-5073-2019-1-58-63.
  16. Venttsel E.S. Issledovanie operatsiy. Zadachi, printsipy, metodologiya [The research of operations. Objectives, principles, methodology]. Moscow, Knorus Publ., 2018. 192 p.
  17. Bo Z.W., Hua L.Z., Yu Z.G. Optimization of process route by genetic algorithms. Robotics and Computer-Integrated Manufacturing, 2006, vol. 22, no. 2, pp. 180–188.
  18. Qiao L., Wang X.-Y., Wang S.-C. A GA-based approach to machining operation sequencing for prismatic parts. International Journal of Production Research, 2000, vol. 38, no. 14, pp. 3283–3303. doi: 10.1080/002075400418261.
  19. Cai N., Wang L., Feng H.-Y. GA-based adaptive setup planning toward process planning and scheduling integration. International Journal of Production Research, 2009, vol. 47, no. 10, pp. 2745–2766. doi: 10.1080/00207540701663516.
  20. Salehi M., Tavakkoli-Moghaddam R. Application of genetic algorithm to computer-aided process planning in preliminary and detailed planning. Engineering Applications of Artificial Intelligence, 2009, vol. 22, no. 8, pp. 1179–1187.

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