IJAT Vol.9 No.3 pp. 248-260
doi: 10.20965/ijat.2015.p0248


A Synchronization Mechanism with Shared Storage Model for Distributed Manufacturing Simulation Systems

Hironori Hibino*, Yoshiro Fukuda**, and Yoshiyuki Yura***

*Tokyo University of Science
2641, Yamazaki, Noda, Chiba, Japan

**Hosei University, Shinjuku, Tokyo, Japan

***Shimiz Co., Chuo, Tokyo, Japan

December 11, 2014
February 27, 2015
May 5, 2015
manufacturing system, distributed simulation, simulation model, system integration, rollback function
Simulators play important roles in the designing of new acturing systems. As manufacturing systems are being created on larger and more complicated scales than ever before, it is increasingly necessary to have opportunities for several persons to design a manufacturing system concurrently. In this case, the designers often use suitable discrete event simulators to evaluate their assigned subsystems. After the subsystems are evaluated, it is necessary to evaluate the full system. To do this, the designers need to make the manufacturing system model by synchronizing several different simulators. In such distributed simulation systems using discrete event simulators, it is important to manage a distributed simulation clock and each simulator clock as well as to define interfaces among the simulation models. With the simulation clock, it is often necessary to perform rollbacks. The rollback function returns the simulation clock to a past time in order to synchronize events among the simulations. However, most commercially available simulators do not include the rollback function.
The purpose of this research is to develop a distributed simulation synchronization method that includes a function for managing distributed simulation clocks without the rollback function and for managing interfaces among simulation models.
In this paper, we propose a storage model concept as the method. We develop an algorithm to implement the proposed concept, and we develop a distributed simulation system configuration using HLA. A case study is then carried out to evaluate the performance of the cooperative work.
Cite this article as:
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. 248-260, 2015.
Data files:
  1. [1] A. Molina, C. Rodriguez, H. Ahuett, J. Cortes, M. Ramirez, G. Jimenez, and S. Martinez, “Next-generation Manufacturing Systems: Key Research Issues in Developing and Integrating Reconfigurable and Intelligent Machines,” I. J. Computer Integrated Manufacturing, Vol.18, pp. 525-536, 2005.
  2. [2] G. Mehrabi, G. Ulsoy, and Y. Koren, “Reconfigurable manufacturing systems: key to future manufacturing,” J. Intelligent Manufacturing, Vol.11, pp. 403-419, 2000.
  3. [3] Y. Fukuda, “The state of the arts for digital engineering,” J. Japan Society of Mechanical Engineers, Vol.106, pp. 230-233, 2003 (in Japanese).
  4. [4] H. Hibino, K. Tanaka, Y. Umezawa, and Y. Fukuda, “Method for Production Forecast in Demand-Synchronized Production,” J. of Advanced Mechanical Design, Systems, and Manufacturing, Vol.8, No.6, pp. 1-15, 2014.
  5. [5] K. Mitsuyuki, F. Kojima, H. Douba, Y. Fukuda, and E. Arai, “Simulation to design and improve kanban system,” CIRP J. Manufacturing Systems, Vol.33, pp. 200-206, 2004.
  6. [6] H. Kim, S. Lee, J. Park, and J. Lee, “A model for a simulation-based shipbuilding system in a shipyard manufacturing process,” Int. J. Computer Integrated Manufacturing, Vol.18, pp. 427-441, 2005.
  7. [7] H. Hibino, T. Sakuma, and M. Yamaguchi, “Evaluation system for energy consumption and productivity in manufacturing system simulation,” Int. J. of Automation Technology, Vol.6, No.3, pp. 279-288, 2012.
  8. [8] H. Hibino, T. Inukai, and Y. Fukuda, “Efficient Manufacturing System Implementation based on Combination between Real and Virtual Factory,” I. J. Production Research, Vol.44, pp. 3897-3915, 2006.
  9. [9] H. Hibino, “Method to Control Manufacturing Cell by Driving Simulation Model,” Int. J. of Automation Technology, Vol.8, No.4, pp. 539-549, 2014.
  10. [10] E. Williams and H. Celik, “Analysis of conveyor systems within automotive final assembly,” Proceedings of the 1998 Winter Simulation Conference, pp. 915-920, 1998.
  11. [11] R. Lu and S. Sundaram, “Manufacturing process modeling of Boeing 747 moving line concepts,” Proceedings of the 2002 Winter Simulation Conference, pp. 1041-1045, 2002.
  12. [12] G. Wohlke and E. Schiller, “Digital planning validation in automotive industry,” Proceedings of the IFIP WG 5.7 Working Conference on Human Aspects in Production Management, Vol. 1, pp. 120-128, 2003.
  13. [13] H. Hibino, Y. Fukuda, M. Nakano, and S. Sato, “The Development of a Method for Integration between Different Types of Simulators,” Global Production Management, Kluwer Academic Publishers, pp. 201-211, 1999.
  14. [14] S. Fujii, Y. Kidani, A. Ogita, and T. Kaihara, “Synchronization Mechanisms for Integration of Distributed Manufacturing Simulation Systems,” International Journal of Simulation, Vol. 71, No.3, pp. 187-197, 1999.
  15. [15] R. Fujimoto, “Parallel Discrete Event Simulation,” Communication of ACM, Vol. 33, No.10, pp. 30-53, 1999.

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

Last updated on May. 28, 2024