single-au.php

IJAT Vol.15 No.5 pp. 651-660
doi: 10.20965/ijat.2021.p0651
(2021)

Paper:

High-Precision Mobile Robotic Manipulator for Reconfigurable Manufacturing Systems

Shinichi Inoue*,†, Akihisa Urata*, Takumi Kodama*, Tobias Huwer*, Yuya Maruyama*, Sho Fujita*, Hidenori Shinno*, and Hayato Yoshioka**

*Makino Milling Machine Co., Ltd.
2-3-19 Nakane, Meguro-ku, Tokyo 152-8578, Japan

Corresponding author

**Tokyo Institute of Technology, Yokohama, Japan

Received:
February 27, 2021
Accepted:
May 14, 2021
Published:
September 5, 2021
Keywords:
reconfigurable manufacturing system, robotic manipulator, AGV
Abstract

The manufacturing industry has identified a new megatrend of mass customization, which is one of the essential goals of Industry 4.0. This megatrend requires the realization of manufacturing that can respond quickly and flexibly to various changing production requirements and ensure the achievement of various quality criteria. However, the manufacturing cannot be realized by conventional manufacturing systems in which reconfigurations need to be performed by skilled engineers. This paper proposes a new reconfigurable manufacturing system concept based on an ultra-flexible transfer system. Particularly, an autonomous mobile robotic manipulator, consisting of a high-performance automated guided vehicle module and a collaborative robotic manipulator module, represents a key component of the system concept. In this context, the focus is on the cooperative control between the modules of the autonomous mobile manipulator, which is essential for high-precision processes (e.g., machining, assembly, measurement, inspection), and its wide operating area. The experimental results confirm that the proposed cooperative control improves the positioning performance of the autonomous mobile manipulator, including the time required for positioning and the positioning accuracy.

Cite this article as:
Shinichi Inoue, Akihisa Urata, Takumi Kodama, Tobias Huwer, Yuya Maruyama, Sho Fujita, Hidenori Shinno, and Hayato Yoshioka, “High-Precision Mobile Robotic Manipulator for Reconfigurable Manufacturing Systems,” Int. J. Automation Technol., Vol.15, No.5, pp. 651-660, 2021.
Data files:
References
  1. [1] J. Deaboul, C. Da Cunha, A. Bernard, and F. Laroche, “Design for Mass Customization: Product Variety vs. Process Variety,” CIRP Annals, Vol.60, No.1, pp. 169-174, 2011.
  2. [2] T. Takenaka, Y. Yamamoto, K. Fukuda, A. Kimura, and K. Ueda, “Enhancing Products and Services Using Smart Appliance Networks,” CIRP Annals, Vol.65, No.1, pp. 397-400, 2016.
  3. [3] D. Kokuryo, T. Kaihara, S. S. Kuik, S. Suginouchi, and K. Hirai, “Value Co-Creative Manufacturing with IoT-Based Smart Factory for Mass Customization,” Int. J. Automation Technol., Vol.11, No.3, pp. 509-518, 2017.
  4. [4] Y. Koren, U. Heisel, F. Jovane, T. Moriwaki, G. Prischow, G. Ulsoy, and H. van Brussel, “Reconfigurable Manufacturing Systems,” CIRP Annals, Vol.48, No.2, pp. 527-540, 1999.
  5. [5] R. G. Landers, B.-K. Min, and Y. Koren, “Reconfigurable Machine Tools,” CIRP Annals, Vol.50, No.1, pp. 269-274, 2001.
  6. [6] H.-P. Wiendahl, H. A. ElMaraghy, P. Nyhuis, M. F. Zaeh, H.-H. Wiendahl, N. Duffie, and M. Brieke, “Changeable Manufacturing-Classification, Design and Operation,” CIRP Annals, Vol.56, No.2, pp. 783-809, 2007.
  7. [7] R. Katz, “Design Principles of Reconfigurable Machine,” Int. J. of Advanced Manufacturing Technology, Vol.34, Nos.5-6, pp. 430-439, 2007.
  8. [8] A. M. Farid and D. C. McFarlane, “A Design Structure Matrix Based for Reconfigurability Measurement of Distributed Manufactuting Systems,” Int. J. of Intelligent Control and Sytems, Vol.1, No.1, pp. 1-12, 2007.
  9. [9] A. Napoleone, A. Prozzetti, and M. Macchi, “A Framework to Manage Reconfigurability in Manufacturing,” Int. J. of Production Research, Vol.56, No.11, pp. 3815-3837, 2018.
  10. [10] X. Li, A. E. Bayrak, B. I. Epureanu, and Y. Koren, “Real-time Teaming of Multiple Reconfigurable Manufacturing Systems,” CIRP Annals, Vol.67, No.1, pp. 437-440, 2018.
  11. [11] J. Franke and F. Luetteke, “Versatile Autonomous Transportation Vehicle for Highly Flexible Use in Industrial Applications,” CIRP Annals, Vol.61, No.1, pp. 407-410, 2012.
  12. [12] P. Kotler, “Marketing Management: Analysis, Planning, and Control,” Prentice Hall, 1997.
  13. [13] H. Shinno and Y. Ito, “Computer Aided Concept Design for Structural Configuration of Machine Tools: Variant Design Using Direct Graph,” J. of Mechanisms, Transmissions, and Automation in Design, Vol.109, No.9, pp. 372-376, 1987.
  14. [14] Y. Ito, “Modular Design for Machine Tools,” McGraw-Hill Education, 2008.
  15. [15] K. Salonitis, “Modular Design for Increasing Assembly Automation,” CIRP Annals, Vol.63, No.1, pp. 189-192, 2014.
  16. [16] E. G. Tsardoulias, A. Iliakopoulou, A. Kargakos, and L. Petrou, “A review of global path planning methods for occupancy grid maps regardless of obstacle density,” J. of Intelligent and Robotic Systems, Vol.84, No.1, pp. 829-858, 2016.
  17. [17] “FANUC Robot series R-30iB Plus / R-30iB Mate Plus / R-30iB Compact Plus Controller iRVision 3D Laser Vision Operator’s Manual,” B-83914EN-04/02, 2020.
  18. [18] K. Sawada, S. Shin, K. Kumagai, and H. Yoneda, “Optimal Scheduling of Automatic Guided Vehicle System via State Space Realization,” Int. J. Automation Technol., Vol.7, No.5, pp. 571-580, 2013.
  19. [19] L. Peihuang, W. Xing, and W. Jiarong, “Path Planning and Control for Multiple AGVs Based on Improved Two-Stage Traffic Scheduling,” Int. J. Automation Technol., Vol.3, No.2, pp. 157-164, 2009.

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Nov. 25, 2021