Research on the Design Method of Virtual Debugging System for Digital Intelligent Production Line
DOI:
https://doi.org/10.54691/mhx0vt69Keywords:
Digital Twins; Virtual Debugging; Tecnomatix; Digital Production Line.Abstract
With the rapid transformation of the manufacturing industry to intelligentization, efficient debugging of digital intelligent production lines has become a key link in the product development stage. This paper focuses on the virtual debugging system construction method for the digital intelligent production line. Firstly, digital twin technology is used to construct a digital twin model of the digital intelligent production line of the pager with the help of Tecnomatix digital twin software platform, which covers mechanical, electrical, and control logic, and other fields, realizes the analog simulation of the production process, and effectively solves the problems of model interference and robot path planning. Secondly, according to the system requirements and the characteristics of the application environment, the virtual debugging system platform of the digital intelligent production line is designed, and its components and data communication technology implementation scheme is analyzed in detail. Finally, the virtual debugging system platform of the digital intelligent production line of the call machines is successfully built. This method provides comprehensive, systematic, and practical method guidance for enterprises to build digital intelligent production line virtual debugging systems, which is of great theoretical and practical significance for industrial upgrading.
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[1] Jakhotiya Y, Rahul M R, Chiddarwar S S: Integrating digital twin and computer vision system for efficient pick-and-place operation using Tecnomatix Process Simulate, International Journal on Interactive Design and Manufacturing (IJIDeM), (2023), p.1-5.
[2] Sueldo C S, Villar S A, De Paula M, et al: Integration of ROS and Tecnomatix for the development of digital twins based decision-making systems for smart factories, IEEE Latin America Transactions, Vol. 19(2021) No. 9, p.1546-1555.
[3] Song H, Ye R, Xie M: Research on complex surface grinding path planning of grinding robot based on NX and Tecnomatix, The International Journal of Advanced Manufacturing Technology, (2024), p.1-11.
[4] Wang B, Yuan L, Yu X, et al: Construction and optimization of digital twin model for hardware production line, IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society (Singapore, October 18-21, 2020), p.4756-4761.
[5] Liu J, Zhang K: Design and Simulation Debugging of Automobile Connecting Rod Production Line Based on the Digital Twin, Applied Sciences, Vol. 13(2023) No.8, p.4919.
[6] Lan X, Chen H: Simulation analysis of production scheduling algorithm for intelligent manufacturing cell based on artificial intelligence technology, Soft Computing, Vol. 27(2023) No.9, p.6007-6017.
[7] Wu Y, Zhou L, Zheng P, et al: A digital twin-based multidisciplinary collaborative design approach for complex engineering product development, Advanced Engineering Informatics, Vol. 52(2022), p.101635.
[8] Ran W, Hu Y, Yang Z: Application of digital twins to flexible production management: taking a Shandong factory as an example, Mobile Information Systems, Vol. 2022(2022) No.1, p.6099409.
[9] Fan Y, Yang J, Chen J, et al: A digital-twin visualized architecture for Flexible Manufacturing System, Journal of Manufacturing Systems, Vol. 60(2021), p.176-201.
[10] Guo K, Wan X, Liu L, et al: Fault diagnosis of intelligent production line based on digital twin and improved random forest, Applied Sciences, Vol.11(2021) No.16, p.7733.
[11] Wu Q, Mao Y, Chen J, et al: Application research of digital twin-driven ship intelligent manufacturing system: Pipe machining production line, Journal of Marine Science and Engineering, Vol. 9(2021) No.3, p.338.
[12] He B, Bai K J: Digital twin-based sustainable intelligent manufacturing: a review, Advances in Manufacturing, Vol. 9(2021) No.1, p.1-21.
[13] Yuan G, Liu X, Zhu C, et al: Multi-objective coupling optimization of electrical cable intelligent production line driven by digital twin, Robotics and Computer-Integrated Manufacturing, Vol. 86(2024), p.102682.
[14] Husár J, Hrehova S, Trojanowski P, et al: Optimizing the simulation of conveyor systems through digital shadow integration to increase assembly efficiency, Technologia i Automatyzacja Montażu (Assembly Techniques and Technologies), Vol. 123(2024) No.1, p.16-22.
[15] Wang H, Yang Z, Zhang Q, et al: A Digital Twin Platform Integrating Process Parameter Simulation Solution for Intelligent Manufacturing, Electronics, Vol. 13(2024) No.4, p.802.
[16] Zhang Q, Shen S, Li H, et al: Digital twin-driven intelligent production line for automotive MEMS pressure sensors, Advanced Engineering Informatics, Vol. 54(2022), p.101779.
[17] Wang Z, Feng W, Ye J, et al: A study on intelligent manufacturing industrial internet for injection molding industry based on digital twin, Complexity, Vol. 2021(2021) No.1, p.8838914.
[18] Lee J D, Hsu H Y, Li C Y, et al: Design and implementation of intelligent automated production-line control system, Electronics, Vol. 10(2021) No.20, p.2502.
[19] Sun M, Cai Z, Zhao N: Design of intelligent manufacturing system based on digital twin for smart shop floors, International Journal of Computer Integrated Manufacturing, Vol. 36(2023) No.4, p.542-566.
[20] Zhang Q, Li H, Shen S, et al: Multi-objective optimization of the mixed-flow intelligent production line for automotive MEMS pressure sensors, Applied Intelligence, Vol. 55(2025) No.1, p.1-14.
[21] Zhang L, Feng L, Wang J, et al: Integration of design, manufacturing, and service based on digital twin to realize intelligent manufacturing, Machines, Vol. 10(2022) No.4, p.275.
[22] Zhou L, Jiang Z, Geng N, et al: Production and operations management for intelligent manufacturing: A systematic literature review, International Journal of Production Research, Vol. 60(2022) No.2, p.808-846.
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