Real‐time routing selection for automated guided vehicles in a flexible manufacturing system

Journal of Manufacturing Technology Management - 2007
NebilBuyurgan1, LakshmananMeyyappan2, CanSaygin3, Cihan H.Dagli2
1Department of Industrial Engineering, University of Arkansas, Fayetteville, Arkansas, USA
2Smart Engineering Systems Lab, Engineering Management and Systems Engineering Department, University of Missouri‐Rolla, Rolla, Missouri, USA
3Integrated Systems Facility, Engineering Management and Systems Engineering Department, University of Missouri‐Rolla, Rolla, Missouri, USA

Tóm tắt

PurposeThe purpose of this paper is to present the development of an architecture for real‐time routing of automated guided vehicles (AGV) in a random flexible manufacturing system (FMS).Design/methodology/approachAGV routing problem is modeled using an evolutionary algorithm‐based intelligent path planning model, which handles vehicle assignments to material handling requests and makes routing decisions with the objective of maximizing the system throughput. The architecture is implemented on a 3‐layer software environment in order to evaluate the effectiveness of the proposed model.FindingsThe proposed architecture, along with the evolutionary algorithm‐based routing model, is implemented in a simulated FMS environment using hypothetical production data. In order to benchmark the performance of the path planning algorithm, the same FMS model is run by traditional dispatching rules. The analysis shows that the proposed routing model outperforms the traditional dispatching rules for real‐time routing of AGVs in many cases.Research limitations/implicationsFuture work includes expanding the scope of the current work by developing and implementing other routing models and benchmarking them against the proposed model on different performance measures.Originality/valueThe implementation of evolutionary algorithms in real‐time routing of AGVs is unique. In addition, due to its modularity, the proposed 3‐layer architecture can allow effective and efficient integration of different real‐time routing algorithms; therefore it can be used as a benchmarking platform.

Từ khóa


Tài liệu tham khảo

Akturk, M.S. and Yilmaz, H. (1996), “Scheduling of automated guided vehicles in a decision making hierarchy”, International Journal of Production Research, Vol. 32, pp. 577‐91.

Barbera, H.M., Quinonero, J.P.C., Izquierdo, M.A.Z. and Skarmeta, A.G. (2003), “I‐fork: a flexible AGV system using topological and grid maps”, Proceedings of the 2003 IEEE International Conference on Robotics and Automation, Taipei, Taiwan, September, pp. 2147‐52.

Bremermann, H.J., Rogson, M. and Salaff, S. (1965), Search by Evolution, Biophysics and Cybernetic Systems, Spartan Books, Washington, DC, pp. 157‐67.

Buyurgan, N., Saygin, C. and Kilic, E. (2004), “Tool allocation in flexible manufacturing systems with tool alternatives”, Robotics and Computer Integrated Manufacturing, Vol. 20, pp. 341‐9.

Daniels, S.C. (1988), “Real‐time conflict resolution in automated guided vehicle scheduling”, PhD thesis, Department of Industrial Engineering, Pennsylvania State University, Pennsylvania.

Davis, L. (1985), “Job shop scheduling with genetic algorithms”, Proceedings of the 1st International Conference on Genetic Algorithms and Their Applications, Lawrence Erlbaum, Mahwah, NJ, pp. 136‐40.

Gaskins, R.J., Tanchoco, J.M.A. and Taghaboni, F. (1989), “Virtual flow paths for free ranging automated guided vehicle systems”, International Journal of Production Research, Vol. 27, pp. 91‐100.

Hocaoglu, C. and Sanderson, A.C. (2001), “Planning multiple paths with evolutionary specification”, IEEE Transactions on Evolutionary Computation, Vol. 5 No. 3, pp. 169‐91.

Kim, C.W. and Tanchoco, J.M.A. (1993), “Operational control of a bi‐directional automated guided vehicle systems”, International Journal of Production Research, Vol. 31, pp. 2123‐38.

Nishi, T., Ando, M., Konishi, M. and Imai, J. (2003), “A distributed route planning method for multiple mobile robots using Lagrangian decomposition technique”, Proceedings of the 2003 IEEE International Conference on Robotics and Automation, Taipei, Taiwan, September, pp. 3855‐61.

Page, W.C., McDConell, J.R. and Anderson, B. (1992), “An evolutionary programming approach to multi‐dimensional part planning”, Proceedings of the First Annual Conference on Evolutionary Programming, pp. 63‐70.

Papadimitiriou, C.H. (1997), “The Euclidean traveling salesman problem is NP‐complete”, Theoretical Computer Science, Vol. 4, pp. 237‐44.

Qiu, L., Hsu, W‐J., Huang, S‐Y.H. and Wang, H. (2002), “Scheduling and routing for AGVs: a survey”, International Journal of Production Research, Vol. 40, pp. 745‐60.

Roszkowska, E. (2002), “Unidirected colored Petri net for modeling and supervisory control of AGV systems”, Proceedings of the 6th International Workshop on Discrete Event Systems, October, pp. 135‐42.

Saygin, C. and Kilic, S.E. (2004), “Dissimilarity maximization method for real‐time routing of parts in random flexible manufacturing systems”, International Journal of Flexible Manufacturing Systems, Vol. 16 No. 2, pp. 169‐82.

Saygin, C. and Kilic, S.E. (1999), “Integrating flexible process plans with scheduling in flexible manufacturing systems”, International Journal of Advanced Manufacturing Technology, Vol. 15 No. 4, pp. 268‐80.

Saygin, C., Chen, F.F. and Singh, J. (2001), “Real‐time manipulation of alternate routings in flexible manufacturing systems: a simulation study”, International Journal of Advanced Manufacturing Technology, Vol. 18 No. 10, pp. 755‐63.

Siwamogsatham, T. and Saygin, C. (2004), “Auction‐based distributed scheduling scheme for flexible manufacturing systems”, International Journal of Production Research, Vol. 42 No. 3, pp. 547‐72.

Syswerda, G. (1991), Schedule Optimization Using Genetic Algorithms Handbook of Genetic Algorithms, Van Nostrand Reinhold, New York, NY, pp. 332‐49.

Xiao, J., Michalewicz, Z. and Zhang, L. (1997), “Adaptive evolutionary planner/navigator for mobile robots”, IEEE Transactions on Evolutionary Computation, Vol. 1, pp. 18‐28.

Thông tin
Thông tin xuất bản

Journal of Manufacturing Technology Management

Thông tin tác giả