Anticipating Action Decisions of Automated Guided Vehicle in an Autonomous Decentralized Flexible Manufacturing System
Nowadays the market for industrial companies is becoming more and more globalized and highly competitive, forcing them to shorten the duration of the manufacturing system development time in order to reduce the time to market. In order to achieve this target, the hierarchical systems used in previous manufacturing systems are not enough because they cannot deal effectively with unexpected situations. To achieve flexibility in manufacturing systems, the concept of an Autonomous Decentralized Flexible Manufacturing System (AD-FMS) is useful. In this paper, we introduce a hypothetical reasoning based algorithm called the Algorithm for Future Anticipative Reasoning (AFAR) which is able to decide on a conceivable next action of an Automated Guided Vehicle (AGV) that works autonomously in the AD-FMS.
[1] M. P. Groover, "Automation, Production System and Computer
Integrated Manufacturing", New York: Prentice Hall, 1987
[2] M. Kaighobadi, and K. Venkatesh, "Flexible Manufacturing Systems: an
overview", International Journal of Operations & Production
Management, vol. 14, pp.26-49, 1994.
[3] G. G. Kost, and R. Zdanowicz, "Modeling of manufacturing systems and
robot motions", Journal of Materials Processing Technology, vol.
164-165, pp. 1369-1378, 2005.
[4] S. Takukawa, "The use of Simulation in Activity-Based Costing For
Flexible Manufacturing Systems", Proc of the 1997 Winter Simulation
Conference, pp. 793-800, 1997.
[5] P. E. Guy, and A. Castleberry, The AGV Handbook. Ann Arbor,
Michigan: Braun-Brumfield, Inc., 1991.
[6] T. Ohno, Toyota Production System: Beyond Large-Scale Production ,
Productivity Press, 1998.
[7] K. Hitomi, Manufacturing Systems Engineering: A Unified Approach to
Manufacturing Technology, Production Management, and Industrial
Economics, 2nd Edition, CRC Press, 1996.
[8] T. Nishi, M. Ando, and M. Konishi, "Experimental Studies on a Local
Rescheduling Procedure for Autonomous Decentralized AGV Systems",
Robotics and Computer Integrated Manufacturing, vol. 22, pp. 154-165,
2006.
[9] J. W. Yoo, E. S. Sim, C. Cao, and J. W. Park, "An Algorithm for Deadlock
Avoidance in an AGV System", International Journal of Advance
Manufacturing Technology, vol.26, pp. 659-668, 2005
[10] N. Wu, and M. Zhou, "Resource-oriented Petri Nets in Deadlock
Avoidance of AGV Systems", Proc. IEEE Conf Robot Automation, pp.
63-69, 2001.
[11] S. H. Kim, and H. Hwang, "An adaptive dispatching Algorithm for
Automated Guided Vehicles based on an evolutionary process", Int.
Journal of Prod Economics, vol. 60-61, pp. 465-472, 1999.
[12] M. Ficko, M. Brezocnik, and J. Balic, "Designing the layout of single- and
multiple-rows flexible manufacturing system by genetic algorithms",
Journal of Materials Processing Technology, vol. 157-158, pp. 150-158,
2004.
[13] G. Ulusoy, F. S. Serifolu, and Ü. Bilge, "A genetic algorithm approach to
the simultaneous scheduling of machines and automated guided vehicles",
Computers & Operations Research, vol. 24, pp. 335-351, 1997.
[14] J.-H. Chen, and S.-Y, Ho, " A novel approach to production planning of
flexible manufacturing systems using an efficient multi-objective genetic
algorithm", International Journal of Machine Tools and Manufacture ,
vol. 45, pp. 949-957, 2005.
[15] Y. C. Ho, " A dynamic zone strategy for vehicle-collision prevention and
load balancing in an AGV system with a single-loop guide path",
Computer in Industry, vol. 42, pp. 159-176, 2000.
[16] T. Nishi, M. Konishi, and S. Hasebe, "An Autonomous Decentralized
Supply Chain Planning System for Multi-Stage Production Processes",
Journal of Intelligent Manufacturing, vol. 16, pp. 259-275, 2005.
[17] R. C. Arkin, and R. R. Murphy, "Autonomous Navigation in a
Manufacturing Environment", IEEE Transactions on Robotics and
Automation, vol. 6, pp. 445-454, 1990.
[18] W. Shen, "Distributed Manufacturing Scheduling Using Intelligent
Agents", IEEE Intelligent Systems, vol. 17, pp. 88-94, 2002.
[19] H. Yamamoto, "AGV's Actions Decision by Reasoning to Anticipate
Future in Decentralized Autonomous FMS", Proceedings of 2000
Japan-USA Symposium on Flexible Automation, 2000.
[20] K. Kouiss, H. Pierreval, and N. Mebarki, "Using Multi-agent architecture
in FMS for dynamic scheduling", Journal of Intelligent Manufacturing,
vol. 8, pp. 41-47, 1997
[21] A. Provetti, "Hypothetical reasoning about actions: from situation
calculus to event calculus", Computational Intelligence, vol. 12,
pp.478-498, 1996.
[22] M. Baldoni, L. Giordano, and A. Martelli, "A modal extension of logic
programming: Modularity, beliefs and hypothetical reasoning", Journal
of Logic and Computation, vol. 8, pp.597-635, 1998.
[23] D. Poole, "A methodology for using a default and abductive reasoning
system", International Journal of Intelligent Systems, vol. 5, pp.521-548,
1990.
[1] M. P. Groover, "Automation, Production System and Computer
Integrated Manufacturing", New York: Prentice Hall, 1987
[2] M. Kaighobadi, and K. Venkatesh, "Flexible Manufacturing Systems: an
overview", International Journal of Operations & Production
Management, vol. 14, pp.26-49, 1994.
[3] G. G. Kost, and R. Zdanowicz, "Modeling of manufacturing systems and
robot motions", Journal of Materials Processing Technology, vol.
164-165, pp. 1369-1378, 2005.
[4] S. Takukawa, "The use of Simulation in Activity-Based Costing For
Flexible Manufacturing Systems", Proc of the 1997 Winter Simulation
Conference, pp. 793-800, 1997.
[5] P. E. Guy, and A. Castleberry, The AGV Handbook. Ann Arbor,
Michigan: Braun-Brumfield, Inc., 1991.
[6] T. Ohno, Toyota Production System: Beyond Large-Scale Production ,
Productivity Press, 1998.
[7] K. Hitomi, Manufacturing Systems Engineering: A Unified Approach to
Manufacturing Technology, Production Management, and Industrial
Economics, 2nd Edition, CRC Press, 1996.
[8] T. Nishi, M. Ando, and M. Konishi, "Experimental Studies on a Local
Rescheduling Procedure for Autonomous Decentralized AGV Systems",
Robotics and Computer Integrated Manufacturing, vol. 22, pp. 154-165,
2006.
[9] J. W. Yoo, E. S. Sim, C. Cao, and J. W. Park, "An Algorithm for Deadlock
Avoidance in an AGV System", International Journal of Advance
Manufacturing Technology, vol.26, pp. 659-668, 2005
[10] N. Wu, and M. Zhou, "Resource-oriented Petri Nets in Deadlock
Avoidance of AGV Systems", Proc. IEEE Conf Robot Automation, pp.
63-69, 2001.
[11] S. H. Kim, and H. Hwang, "An adaptive dispatching Algorithm for
Automated Guided Vehicles based on an evolutionary process", Int.
Journal of Prod Economics, vol. 60-61, pp. 465-472, 1999.
[12] M. Ficko, M. Brezocnik, and J. Balic, "Designing the layout of single- and
multiple-rows flexible manufacturing system by genetic algorithms",
Journal of Materials Processing Technology, vol. 157-158, pp. 150-158,
2004.
[13] G. Ulusoy, F. S. Serifolu, and Ü. Bilge, "A genetic algorithm approach to
the simultaneous scheduling of machines and automated guided vehicles",
Computers & Operations Research, vol. 24, pp. 335-351, 1997.
[14] J.-H. Chen, and S.-Y, Ho, " A novel approach to production planning of
flexible manufacturing systems using an efficient multi-objective genetic
algorithm", International Journal of Machine Tools and Manufacture ,
vol. 45, pp. 949-957, 2005.
[15] Y. C. Ho, " A dynamic zone strategy for vehicle-collision prevention and
load balancing in an AGV system with a single-loop guide path",
Computer in Industry, vol. 42, pp. 159-176, 2000.
[16] T. Nishi, M. Konishi, and S. Hasebe, "An Autonomous Decentralized
Supply Chain Planning System for Multi-Stage Production Processes",
Journal of Intelligent Manufacturing, vol. 16, pp. 259-275, 2005.
[17] R. C. Arkin, and R. R. Murphy, "Autonomous Navigation in a
Manufacturing Environment", IEEE Transactions on Robotics and
Automation, vol. 6, pp. 445-454, 1990.
[18] W. Shen, "Distributed Manufacturing Scheduling Using Intelligent
Agents", IEEE Intelligent Systems, vol. 17, pp. 88-94, 2002.
[19] H. Yamamoto, "AGV's Actions Decision by Reasoning to Anticipate
Future in Decentralized Autonomous FMS", Proceedings of 2000
Japan-USA Symposium on Flexible Automation, 2000.
[20] K. Kouiss, H. Pierreval, and N. Mebarki, "Using Multi-agent architecture
in FMS for dynamic scheduling", Journal of Intelligent Manufacturing,
vol. 8, pp. 41-47, 1997
[21] A. Provetti, "Hypothetical reasoning about actions: from situation
calculus to event calculus", Computational Intelligence, vol. 12,
pp.478-498, 1996.
[22] M. Baldoni, L. Giordano, and A. Martelli, "A modal extension of logic
programming: Modularity, beliefs and hypothetical reasoning", Journal
of Logic and Computation, vol. 8, pp.597-635, 1998.
[23] D. Poole, "A methodology for using a default and abductive reasoning
system", International Journal of Intelligent Systems, vol. 5, pp.521-548,
1990.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:64174", author = "Rizauddin Ramli and Jaber Abu Qudeiri and Hidehiko Yamamoto", title = "Anticipating Action Decisions of Automated Guided Vehicle in an Autonomous Decentralized Flexible Manufacturing System", abstract = "Nowadays the market for industrial companies is becoming more and more globalized and highly competitive, forcing them to shorten the duration of the manufacturing system development time in order to reduce the time to market. In order to achieve this target, the hierarchical systems used in previous manufacturing systems are not enough because they cannot deal effectively with unexpected situations. To achieve flexibility in manufacturing systems, the concept of an Autonomous Decentralized Flexible Manufacturing System (AD-FMS) is useful. In this paper, we introduce a hypothetical reasoning based algorithm called the Algorithm for Future Anticipative Reasoning (AFAR) which is able to decide on a conceivable next action of an Automated Guided Vehicle (AGV) that works autonomously in the AD-FMS.
", keywords = "Flexible Manufacturing System, Automated GuidedVehicle, Hypothetical Reasoning, Autonomous Decentralized.", volume = "1", number = "9", pages = "541-7", }
