Distributed and centralised material handling scheduling: Comparison and results of a simulation study

Part of a larger research that employs decentralized holonic modelling techniques in manufacturing planning and control, this work proposes a holonic-based material handling system and contrasts the centralized and distributed scheduling approaches for the allocation of material handling operations to the available system resources. To justify the use of the decentralized holonic approach and assess its performance compared to conventional scheduling systems, a series of evaluation tests and a simulation study are carried out. As illustrated by the results obtained from the simulation study, the decentralized holonic approach is capable of delivering competitive feasible solutions in, practically, real-time.

[1]  Nobuhiro Sugimura,et al.  A Study on Integrated Process Planning and Scheduling System for Holonic Manufacturing , 2006 .

[2]  Robert H. Sturges,et al.  The influence of material handling operations on the schedule makespan in manufacturing cell environments , 2005 .

[3]  Peter B. Luh,et al.  Holonic manufacturing scheduling: architecture, cooperation mechanism and implementation , 1998 .

[4]  Radu F. Babiceanu,et al.  Performance evaluation of agent-based material handling systems using simulation techniques , 2005, Proceedings of the Winter Simulation Conference, 2005..

[5]  Averill M. Law,et al.  Simulation Modeling and Analysis , 1982 .

[6]  Peter Norvig,et al.  Artificial Intelligence: A Modern Approach , 1995 .

[7]  Robert W. Brennan,et al.  Realizing holonic control with function blocks , 2001, Integr. Comput. Aided Eng..

[8]  Robert H. Sturges,et al.  Real-time holonic scheduling of material handling operations in a dynamic manufacturing environment , 2005 .

[9]  R. H. Sturges,et al.  Framework for the control of automated material-handling systems using the holonic manufacturing approach , 2004 .

[10]  Robert W. Brennan,et al.  Holonic job shop scheduling using a multiagent system , 2005, IEEE Intelligent Systems.

[11]  Lihui Wang,et al.  Agent-based control system for next generation manufacturing , 1998, Proceedings of the 1998 IEEE International Symposium on Intelligent Control (ISIC) held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA) Intell.

[12]  Radu F. Babiceanu,et al.  Manufacturing scheduling in decentralised holonic systems using artificial intelligence techniques , 2007, Int. J. Manuf. Technol. Manag..

[13]  Weiming Shen,et al.  Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing , 2000 .