A mathematical model for production routing of mechanical engineering products

Cover Page

Cite item

Full Text

Abstract

The aim was to create a mathematical model describing the development of a production (shop-to-shop) routing of mechanical engineering products based on a 3D model and allowing the cost of the final product to be reduced. The developed mathematical model was simulated based on 3D models designed in the Siemens NX system, which were subsequently imported into the *stp format and recognized by a designed module written in the Phyton programming language. The factors of the production environment affecting the formation of the production routing of mechanical engineering products were determined. A diagram of the algorithm for the “constructive element - technological operation - means of technological equipment (equipment-tool)” relationship was developed. Based on the results of testing the developed mathematical model, the use of neural networks as a tool for the implementation and automation of the work was found advantageous as compared to the standard scheme of work of a process engineer when developing a production routing of mechanical engineering products. These advantages include a decrease in the time for the development of a routing and the cost of the final product. The developed model has a practical limitation consisting in a rather complex geometry of some structural elements of a unit, which impedes the development of an algorithm for recognizing their structure. The use of a neural network prototype in automatic mode is advisable for relatively simple parts (including a flange, hole, chamfer and rounding). However, since the number of simple units from the recognition point of view amounts to about 40% among the nomenclature of manufactured units, the reduction in the development time of the technological process in comparison with the conventional approach comprises only 10–25% of the total time of technological preparation.

About the authors

I. V. Fokin

Irkutsk National Research Technical University

Email: fokiniv@ex.istu.edu

A. N. Smirnov

Irkutsk National Research Technical University

Email: horror512@yandex.ru

References

  1. Govorkov A.S. Technique of designing of the product of aviation technics with maintenance of the set criteria of adaptability to manufacture // Journal of International Scientific Publications: Materials, Methods & Technologies. 2011. Vol. 5. Part. 3. P. 156–161.
  2. Govorkov A., Zhilyaev A. The estimation technique of the airframe design for manufacturability // Materials Science and Engineering: IOP Conference Series. 2016. Vol. 124. Iss. 1. P. 012014. https://doi.org/10.1088/1757-899X/124/1/012014
  3. Малыгин А.Н. Модернизация предприятий судостроения и судоремонта на основе внедрения автоматизированных информационных технологий // Juvenis Scientia. 2017. № 7. С. 26–29.
  4. Lychagin D.V., Walter A.V., Arkhipova D.A., Lasukov A.A. Systematic classifier of manufacturing processes for medium size shafts // Materials Science and Engineering: IOP Conference Series. 2016. Vol. 125. Р. 012030. https://doi.org/10.1088/1757-899X/125/1/012030
  5. Бурмистров Е.Г., Михеев Т.А. Проблемы внедрения автоматизированных систем управления проектами на судостроительных и судоремонтных предприятиях // Вестник Волжской государственной академии водного транспорта. 2017. Вып. 52. С. 73–79.
  6. Rabinskiy L.N., Ripetskiy A.V., Zelenov S.V., Kuznetsova E.L. Analysis and monitoring methods of technological preparation of the additive production // Journal of Industrial Pollution Control. 2017.. URL: https://www.icontrolpollution.com/articles/analysisand-monitoring-methods-of-technologicalpreparation-ofthe-additive-production.php?aid=86082&view=mobile (12.03.2020).
  7. Svetlík J., Baron P., Dobránsky J., Kočiško M. Implementation of computer system for support of technological preparation of production for technologies of surface processing // Applied Mechanics and Materials. 2014. Vol. 613. P. 418–425. https://doi.org/10.4028/www.scientific.net/AMM.613.418
  8. Burdo G.B. Improving the technological preparations for manufacturing production // Russian Engineering Research. 2017. Vol. 37. Iss. 1. P. 49–56. https://doi.org/10.3103/S1068798X17010051
  9. Tkachev A.A., Ivanenko Yu.G., Zarubin V.V., Olgarenko I.V. Automation of water distribution man-agement during the reconstruction of main irrigation canals // Materials Science and Engineering: IOP Conference Series. 2019. Vol. 537. Iss. 3. P. 032070. https://doi.org/10.1088/1757-899X/537/3/032070
  10. Зяблов О.К., Фунтикова Е.В. Автоматизация технологической подготовки судоремонтного производства // Вестник Волжской государственной академии водного транспорта. 2014. № 38. С. 49–53.
  11. Сахаров В.В., Кузьмин А.А., Чертков А.А. Алгоритм принятия оптимальных решений в судоремонте с применением матрицы Крылова // Вестник государственного университета морского и речного транспорта имени адмирала С.О. Макарова. 2014. № 3. С. 81–89.
  12. Зяблов О.К., Кочнев Ю.А. Разработка системы автоматизированного проектирования технологических процессов ремонта судов внутреннего плавания // Речной транспорт (XXI век). 2017. № 2. С. 43–45.
  13. Reş M.-D., Bresfelean V.P. Means to enhance the performance of ERP systems’ personalized production modules // Emerging Markets Queries in Finance and Business. 2014. Vol. 15. P. 262–270. https://doi.org/10.1016/S2212-5671(14)00499-7
  14. Grechishnikov V.A., Khusainov R.M., Akhkiyamov D.R., Yurasov S.Yu., Yurasova O.I. Identifying the primary rigidity axes in the elastic system of a metal-cutting machine // Russian Engineering Research. 2016. Vol. 36. No. 8. P. 673–676. https://doi.org/10.3103/S1068798X16080104
  15. Khusainov R.M., Sharafutdinov I.F. Methods of assessing the dynamic stability of the cutting process using UNIGRAPHICS NX // Materials Science and Engineering: IOP Conference Series. 2016. Vol. 134. No. 1. Р. 012042. https://doi.org/10.1088/1757-899X/134/1/012042
  16. Krastyaninov P.M., Khusainov R. Selection of equipment for machining processing of parts using NX and TEAMCENTER programs // Materials Science and Engineering: IOP Conference Series. 2016. Vol. 134. No. 1. Р. 012041. https://doi.org/10.1088/1757-899X/134/1/012041
  17. Говорков А.С., Жиляев А.С. Практическое применение «Системы анализа технологичности» при проведении технологического контроля изделия авиационной техники // Труды Московского авиационного института. 2014. № 74. P. 21.
  18. Subrahmanyam S., Wozny M. An overview of automatic feature recognition techniques for computer-aided process planning // Computers in industry. 1995. Vol. 26. P. 1–21.
  19. Akhatov R., Govorkov A., Zhilyaev A. Software solution designing of «The analysis system of workability of industrial product» during the production startup of aeronautical products // International Journal of Applied Engineering Research. 2015. Vol. 10. No. 21. P. 42560‒42562.
  20. Говорков А.С., Ахатов Р.Х. Анализ технологичности изделия авиационной техники на основе информационного образа изделия // Известия Самарского научного центра Российской академии наук. 2011. Т. 13. № 6. С. 285–292.

Supplementary files

Supplementary Files
Action
1. JATS XML
Download

Согласие на обработку персональных данных

 

Используя сайт https://journals.rcsi.science, я (далее – «Пользователь» или «Субъект персональных данных») даю согласие на обработку персональных данных на этом сайте (текст Согласия) и на обработку персональных данных с помощью сервиса «Яндекс.Метрика» (текст Согласия).