Applying Multi-Agent System Modelling to the Scheduling Problem in a Ceramic Tile Factory

The actual ceramic tile sector needs dynamic production processes to offer its clients on-line programming. Thus, companies can manage real-time response about their services and delivery times of required products, tackling a Mass Customization process in which design and sales activities are done before the production stage. The customer service must cover all activities that can improve the client satisfaction (offers, orders, after-sales services, etc.). Moreover, production tasks scheduling in a ceramic tile factory is a complex problem which requires robust and flexible software applications. Recent advances in Multi-Agent Systems applied to general scheduling problems and industrial applications have demonstrated the advantages of the agent technology in complex distributed problems. In this work we present a Multi-Agent System modelling for a scheduling problem in a ceramic tile factory. Our approach tries to improve the production performance, increase the schedule reliability and keep updated schedules. We propose a multi-agent system in which the constituent agents cooperate to find a feasible schedule taking into account on-line orders, factory layout and capacity, time constraints, anticipated demands and constraints imposed by the master plan. The value of our approach is two fold. On the one hand it is useful for defining the production tasks schedule, while on the other hand it can be suitable for simulating purposes, for example to find out whether a customer order is feasible or to figure out different schedules for a specific production lot.

[1]  Wen-Hwa Yang,et al.  Survey of scheduling research involving setup times , 1999, Int. J. Syst. Sci..

[2]  Stefan Bussmann Daimler-Benz An Agent-Oriented Architecture for Holonic Manufacturing Control , 2007 .

[3]  Jorge J. Gómez-Sanz,et al.  Agent Oriented Software Engineering with INGENIAS , 2003, CEEMAS.

[4]  Douglas H. Norrie,et al.  Agent-Based Systems for Intelligent Manufacturing: A State-of-the-Art Survey , 1999, Knowledge and Information Systems.

[5]  Luc Bongaerts,et al.  Reference architecture for holonic manufacturing systems: PROSA , 1998 .

[6]  A D R I A N A G I R E T,et al.  Holons and Agents , 2022 .

[7]  Klaus Fischer,et al.  An agent-based Approach to holonic manufacturing systems , 1998, BASYS.

[8]  Peter B. Luh,et al.  Holonic planning and scheduling for a robotic assembly testbed , 1994, Proceedings of the Fourth International Conference on Computer Integrated Manufacturing and Automation Technology.

[9]  D. McFarlane,et al.  Holonic Manufacturing Control: Rationales, Developments and Open Issues , 2003 .

[10]  Jatinder N. D. Gupta,et al.  A review of scheduling research involving setup considerations , 1999 .

[11]  Douglas H. Norrie,et al.  Distributed decision-making using the contract net within a mediator architecture , 1997, Decis. Support Syst..

[12]  Jean-Pierre Kruth,et al.  Holonic machine controller: a study and implementation of holonic behaviour to current NC controller , 1997 .

[13]  Paul Valckenaers,et al.  An Object-Oriented Execution Model for a Machine Controller Holon , 1998, Eur. J. Control.

[14]  David S. Linthicum,et al.  Enterprise Application Integration , 1999 .

[15]  Martyn Fletcher,et al.  Fault‐tolerant holonic manufacturing systems , 2001, Concurr. Comput. Pract. Exp..

[16]  D. H. Jarvis,et al.  A strategy for the migration of existing manufacturing systems to holonic systems , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[17]  Jorge J. Gómez-Sanz,et al.  Agent Oriented Analysis Using Message/UML , 2001, AOSE.

[18]  Jean-Charles Billaut,et al.  Les problèmes d'ordonnancement de type flow-shop hybride : état de l'art , 1999, RAIRO Oper. Res..