Abstract
The issue of avoiding deadlocks in unmanned automated manufacturing systems with automated guided vehicle systems is addressed in this paper. In the automated guided vehicle systems, multi-load vehicles are used. A simple and easily adoptable deadlock-free real-time vehicle control strategy is developed for this type of vehicle, by using an intelligent rule-based method. The proposed strategy uses the global information and current states of the system to control the resource allocation. Based on the proposed strategy, the system resource can be appropriately allocated and utilized efficiently. A hypothetical system is built to investigate the performance of the proposed vehicle control strategy and to discuss the interactions between the fleet size, queuing capacity, and vehicle loading capacity by computer simulation tool.
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References
Coffman, E. G., Jr., Elphick, M. and Shoshani, A.: System deadlocks, Comput. Surveys 3 (1971), 67–78.
Ferreira, P. M., Lawley, M. A. and Reveliotis, S. A.: Deadlock avoidance policies for resource allocation systems with applications to FMS, IEEE Sympos. Emerging Technologies & Factory Automation, 1996, pp. 42–48.
Ierovante, S.: Petri nets supervisory control for deadlock prevention and avoidance, In: Proc. IEEE Internat. Conf. Systems, Man and Cybernetics, 1994, pp. 1024–1029.
Barkaoui, K., Chaoui, A. and Benamara, R.: Performance of alternative strategies for dealing with deadlocks in FMS, In: IEEE Sympos. Emerging Technologies & Factory Automation, 1997, pp. 281–286.
Reveliotis, S. A. and Lawley, M. A.: Efficient implementations of Bankers algorithm for deadlock avoidance in flexible manufacturing systems, In: IEEE Sympos. Emerging Technologies & Factory Automation, 1997, pp. 214–220.
Lawley, M., Reveliotis, S. and Ferreira, P.: The application and evaluation of bankers algorithm for deadlock-free buffer space allocation in flexible manufacturing systems, Internat. J. Flexible Manufact. Systems 10 (1998), 73–100.
Ferrarini, L., Piroddi, L. and Allegri, S.: A comparative performance analysis of deadlock avoidance control algorithm for FMS, J. Intell. Manufact. 10 (1999), 569–585.
Kim, C.W., Tanchoco, J. M. A. and Koo, P. H.: Deadlock prevention in manufacturing systems with AGV systems: Bankers algorithm approach, J. Manufacturing Sci. Eng. 119 (1997), 849–854.
Viswanadham, N., Narahari, Y. and Johnson, T. L.: Deadlock prevention and deadlock avoidance in flexible manufacturing systems using Petri net models, IEEE Trans. Robot. Automat. 6 (1990), 713–723.
Wysk, R. A., Yang, N. S. and Joshi, S.: Detection of deadlocks in flexible manufacturing cells, IEEE Trans. Robot. Automat.7 (1991), 853–859.
Fanti, M. P., Maione, B. and Turchiano, B.: Deadlock detection and recovery in flexible production systems with multiple capacity resources, In: Industrial Applications in Power Systems, Computer Science and Telecommunications Proc. of the Mediterranean Electrotechnical Conference, 1996, pp. 237–241.
Lee, C. C. and Lin, J. T.: Deadlock prediction and avoidance based on petri nets for zone-control automated guided vehicle systems, Internat. J. Product. Res. 33 (1995), 3249–3266.
Yeh, M. S. and Yeh, W. C.: Deadlock prediction and avoidance for zone-control AGVS, Internat. J. Product. Res. 36 (1998), 2879–2889.
Kim, C. O. and Kim, S. S.: Efficient real-time deadlock-free control algorithm for automated manufacturing systems, Internat. J. Product. Res. 35 (1997), 1545–1560.
Ozden, M.: A simulation study of multiple-load-carrying automated guided vehicles in a flexible manufacturing system, Internat. J. Product. Res. 26 (1988), 1353–1366.
Leung, L. C., Khator, S. K. and Kimbler, D. L.: Assignments of AGVS with different vehicle types, Material Flow 4 (1987), 33–51.
Hodgson, T. J., King, R. E., Monteith, S. K. and Schultz, S. R.: Developing control rules for an AGVS using Markov decision processes, Material Flow 4 (1987), 85–96.
Nayyar, P. and Khator, S. K.: Operational control of multi-load vehicles in an automated guided vehicles system, Comput. Industr. Eng. 25 (1993), 503–506.
Lee, J., Tangjarukij, M. and Zhu, Z.: Load selection of automated guided vehicles in flexible manufacturing systems, Internat. J. Product. Res. 34 (1996), 3383–3400.
Occena, L. G. and Yokota, T.: Analysis of the AGV loading capacity in a JIT environment, J. Manufact. Systems 12 (1993), 24–35.
Tanchoco, J. M. A. and Co, C. G.: Real-Time Control Strategies for Multiple-Load AGVS, Material Flow Systems in Manufacturing, Chapman & Hall, London, 1994.
Bilge, Ñ. and Tanchoco, J. M. A.: AGV systems with multi-load carriers: Basic issues and potential benefits, J. Manufact. Systems 16 (1997), 159–174.
Sinriech, D. and Palni, L.: Scheduling pickup and deliveries in a multiple-load discrete carrier environment, IIE Trans. 30 (1998), 1035–1047.
Egbelu, J. P. and Tanchoco, J. M. A.: Characterization of automated guided vehicle dispatching rules, Internat. J. Product. Res. 22 (1984), 359–374.
AutoMod, AutoMod Users Manual, AutoSimulations Inc., Bountiful, Utah, USA, 1998.
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Liu, FH., Hung, PC. Control Strategy for Dispatching Multi-load Automated Guided Vehicles in a Deadlock-Free Environment. Journal of Mathematical Modelling and Algorithms 1, 117–134 (2002). https://doi.org/10.1023/A:1016564209985
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DOI: https://doi.org/10.1023/A:1016564209985