IJAT Vol.14 No.6 pp. 943-950
doi: 10.20965/ijat.2020.p0943


Task Scheduling of Material-Handling Manipulator for Enhancing Energy Efficiency in Flow-Type FMS

Ryo Yonemoto and Haruhiko Suwa

Setsunan University
17-8 Ikeda-naka-machi, Neyagawa, Osaka 572-8508, Japan

Corresponding author

March 28, 2020
September 23, 2020
November 5, 2020
energy-efficiency, productivity, manufacturing system, scheduling, industrial robot

Energy savings and reduction in environmental burdens are necessitated to enhance sustainable manufacturing performances. Not only should energy consumption in the factory be visualized, but also a mechanism, by which in-process production and energy-related information measured in the shop floor are fed back into planning/scheduling decision-making, must be established to improve the energy efficiency during manufacturing execution. This study addresses the effect of scheduling on the improvement of energy efficiency in manufacturing by connecting a developed measurement and control platform with a real manufacturing system. The manufacturing system testbed utilized in this study forms a simple flow-type flexible manufacturing system composed of automated manufacturing cell with a CNC lathe, material-handling manipulator, and vertical machining center. We focus on the task scheduling of the material-handling manipulator, which yields a job sequence, and the effect of task scheduling of the manipulator on the energy efficiency and productivity of the entire manufacturing system.

Cite this article as:
R. Yonemoto and H. Suwa, “Task Scheduling of Material-Handling Manipulator for Enhancing Energy Efficiency in Flow-Type FMS,” Int. J. Automation Technol., Vol.14 No.6, pp. 943-950, 2020.
Data files:
  1. [1] H. Makita, Y. Shida, and N. Nozue, “Factory Energy Management System Using Production Information,” Mitsubishi Electric Advance, Vol.140, pp. 7-11, 2012.
  2. [2] K.-D. Thoben, S. Wiesner, and T. Wuest, “‘Industrie 4.0’ and smart manufacturing: A review of research issues and application examples,” Int. J. Automation Technol., Vol.11, No.1, pp. 4-16, 2017.
  3. [3] J. R. Duflou, J. W. Sutherland, D. Dornfeld, C. Herrmann, J. Jeswiet, S. Kara, M. Hauschild, and K. Kellens, “Towards energy and resource efficient manufacturing: A processes and systems approach,” CIRP Annals – Manufacturing Technology, Vol.61, No.2, pp. 587-609, 2012.
  4. [4] R. Yonemoto and H. Suwa, “Evaluation of Energy Efficiency and Productivity in Scheduling by Using Physical Simulator,” Trans. of the Institute of Systems, Control and Information Engineers, Vol.32, No.5, pp. 185-191, 2019.
  5. [5] T. Samukawa and H. Suwa, “Development of heterogeneous measurement system for predicting power consumption in eco-machining,” Proc. of 2016 Int. Symp. on Flexible Automation, pp. 413-419, 2016.
  6. [6] M. Fujishima, H. Shimanoe, and M. Mori, “Reducing the energy consumption of machine tools,” Int. J. Automation Technol., Vol.11, No.4, pp. 601-607, 2017.
  7. [7] H. Ohtani, “Development of energy-saving machine tool,” Int. J. Automation Technol., Vol.11, No.4, pp. 608-614, 2017.
  8. [8] T. Shudeleit, S. Züst, L. Weiss, and K. Wegner, “Machine tool energy efficiency: A component mapping-based approach,” Int. J. Automation Technol., Vol.10, No.5, pp. 717-726, 2016.
  9. [9] H. Koresawa, K. Tanaka, and H. Narahara, “Low-energy injection molding process by a mold with permeability fabricated by additive manufacturing,” Int. J. Automation Technol., Vol.10, No.1, pp. 101-105, 2016.
  10. [10] A. Glodde and M. Afrough, “Energy efficiency evaluation of an underactuated robot in comparison to traditional robot kinematics,” Procedia CIRP, Vol.23, pp. 127-130, 2014.
  11. [11] M. B. Paryanto, J. M. J. Kohl, and J. F. S. Spreng, “Energy consumption and dynamic behavior analysis of a six-axis industrial robot in an assembly system,” Procedia CIRP, Vol.23, pp. 131-136, 2014.
  12. [12] E. Uhlmann, S. Reinkober, and T. Hollerbach, “Energy efficient usage of industrial robots for machining process,” Procedia CIRP, Vol.48, pp. 206-211, 2016.
  13. [13] Y. Kawamura, H. Horiguchi, and T. Ono, “A Framework for Optimal Planning Systems on the EMS Platform,” Fuji Electric J., Vol.86, pp. 97-201, 2013.
  14. [14] H. Hibino, T. Sakuma, and M. Yamaguchi, “Evaluation system for energy consumption and productivity in manufacturing system simulation,” Int. J. Automation Technol., Vol.6, No.3, pp. 248-288, 2012.
  15. [15] H. Hibino, Y. Fukuda, and Y. Yura, “A synchronization mechanism with shared storage model for distributed manufacturing simulation systems,” Int. J. Automation Technol., Vol.9, No.3, pp. 279-260, 2015.
  16. [16] H. Hibino, M. Yamamoto, M. Yamaguchi, and T. Kobayashi, “A study on lot-size dependence of energy consumption per unit of production throughput considering buffer capacity,” Int. J. Automation Technol., Vol.11, No.1, pp. 46-55, 2017.
  17. [17] C. Herrmann, S. Thiede, S. Kara, and J. Hesselbach, “Energy oriented simulation of manufacturing systems – Concept and application,” CIRP Annals, Vol.60, No.1, pp. 45-48, 2011.
  18. [18] J. Kohl, S. Spreng, and J. Franke, “Discrete Event Simulation of Individual Energy Consumption for Product-varieties,” Procedia CIRP, Vol.17, pp. 517-522, 2014.
  19. [19] T. L. Garwood, B. R. Hughes, M. R. Oates, D. O’Connor, and R. Hughes, “A review of energy simulation tools for the manufacturing sector,” Renewable and Sustainable Energy Reviews, Vol.81, No.1, pp. 895-911, 2018.
  20. [20] H. Murata, N. Yokono, S. Fukushige, and H. Kobayashi, “A lifecycle simulation method for global reuse,” Int. J. Automation Technol., Vol.12, No.6, pp. 814-821, 2018.
  21. [21] Y. Mizuno, Y. Kishita, S. Fukushige, and Y. Umeda, “Envisioning sustainable manufacturing industries of Japan,” Int. J. Automation Technol., Vol.8, No.5, pp. 634-643, 2014.
  22. [22] M. M. Isnaini, Y. Shinoki, R. Sato, and K. Shirase, “Development of a CAD-CAM interaction system to generate a flexible machining process plan,” Int. J. Automation Technol., Vol.9, No.2, pp. 104-114, 2015.
  23. [23] T. Samukawa and H. Suwa, “An optimization of energy-efficiency in machining manufacturing systems based on a framework of multi-mode RCPSP,” Int. J. Automation Technol., Vol.10, No.6, pp. 985-992, 2016.
  24. [24] C. Gahm, F. Denz, M. Dirr, and A. Tuma, “Energy-efficient scheduling in manufacturing companies: A review and research framework,” European J. of Operational Research, Vol.248, pp. 744-757, 2016.
  25. [25] C. Artigues, P. Lopez, and A. Haït, “The energy scheduling problem: Industrial case-study and constraint propagation techniques,” Int. J. of Production Economics, Vol.143, No.1, pp. 13-23, 2013.
  26. [26] Z. Zhang, R. Tang, T. Peng, L. Tao, and S. Jia, “A method for minimizing the energy consumption of machining system: integration of process planning and scheduling,” J. of Cleaner Production, Vol.137, pp. 1647-1662, 2016.
  27. [27] R. Yonemoto, H. Suwa, and T. Samukawa, “Evaluation of energy efficiency in scheduling by using cyber-physical manufacturing simulator,” Proc. of Int. Symp. on Scheduling, pp. 111-116, 2017.

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Last updated on Jul. 23, 2024