Distributed production networks are structures which are considered able to provide the organisational agility and efficiency necessary to compete in the global market. The performance of such organisations heavily depends on the ability of those involved in the network to coordinate their activities. Two approaches are available for managing complex distributed production networks: a centralised approach, where a unique entity (the planner, for instance) has all the necessary information to make planning decisions for the entire network; or a decentralised approach where each entity in the network has the necessary information and knowledge to make autonomous planning decisions, while the common goal is reached through cooperation between all the people involved in the network.

Production Planning in Production Networks addresses production planning problems in distributed manufacturing networks from strategic, tactical, organisational and operative perspectives. New methodologies for capacity negotiation, allocation and workload assignment in production networks are presented. Specifically, three main problems are focussed on: how to negotiate production capacity availability in the long-term; how to allocate production capacity in medium-term planning; and, how to assign workloads in the short-term. The proposed approaches are based on negotiation algorithms in multi-agent networks. These approaches are compared with classical centralised approaches using discrete event simulation methodologies. Benchmark analysis is provided to understand the effectiveness and efficiency of the proposed approaches.

The methodologies, approaches and results presented in Production Planning in Production Networks will be of interest to production network managers who will learn how to organise decentralised production planning in distributed organisations, and enterprise resource planning vendors who can apply the proposed methodologies to theextended enterprise.

Auteur

Professor. Giovanni Perrone works in manufacturing and production systems and teaches manufacturing, computer integrated manufacturing and industrial engineering at the Faculty of Engineering of the University of Basilicata in Potenza (ITALY). He also teaches "Economics" at the University of Palermo (ITALY). His principal interests are in Production Engineering and Management, Operations Management, Advanced and Intelligent Manufacturing Systems, Production Economics and Soft Computing Techniques. Within these research fields he has published more than 70 papers, mainly in international journals and proceedings of international conferences. He is a member of IIE, IEEE, corresponding member of CIRP and member of AITEM (Italian association for manufacturing). He acts as reviewer for the following journals: Int. J. of Production Research, Int. J. of Production Economics, Omega, European J. of Operational Research.

Giovanna Lo Nigro is an assistant professor at the Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale, University of Palermo (Italy) and teaches Organization Design within the degree in Managerial Engineering. She obtained her PhD in Industrial Engineering in 1997. Her research interests include: response for quotation, distributed production planning, negotiation in economic transactions, supply chain management, reconfigurable manufacturing system, virtual organization, customer centered process reengineering. She is a member of Ithe talian Association of Management Engineering (AiIG).

Sergio Noto La Diega has been a Full Professor of Manufacturing Technology at the University of Palermo, Dipartimento di Tecnologia Meccanica, Produzione e Ingegneria Gestionale since 1975; he has also taught Business Management within the degree in Managerial Engineering since 1993. He is the author and co-author of more than 100 papers, mainly published in international journals and conference acts. His main research interests include: economic analysis of manufacturing systems, modelling and simulation of manufacturing systems, optimisation of machining processes, dynamic behaviour of machine tools in metal cutting, analysis of metal forming processes.

Paolo Renna is an assistant professor at the Engineering Faculty of the University of Basilicata. He gained his Masters Degree in mechanical engineering from University of Basilicata (2000). His principal research interest is the simulation of distributed agent systems applied to manufacturing systems and production planning.

Manfredi Bruccoleri received his 'Laurea' degree (1998) in Industrial Engineering from the Faculty of Engineering of the University of Palermo. From the same university, he holds a doctoral degree in Production Engineering (2003). In 2001 he was a visiting scholar at the ERC for Reconfigurable Manufacturing Systems at the University of Michigan. He has been Assistant Professor of Manufacturing Engineering at the University of Palermo since 2005.

Résumé

Distributed production networks are organizational structures considered able to meet the agility and efficiency necessary to compete in the global market. Performances of such organizations depends on the ability of network actors in coordinating their activities. There are two approaches for managing complex distributed production networks: a centralized approach, or a decentralized approach. This book addresses production planning problems in distributed manufacturing networks from strategic, tactical, organisational and operative perspectives. New methodologies for capacity negotiation, allocation and workload assignment are presented. Long, medium and short-term problems are focused on. The proposed approaches are based on negotiation algorithms in multi-agent networks and are compared with classical centralised approaches in order to understand the effectiveness and efficiency of these approaches. This book will interest production network managers and enterprise resource planning vendors.

Contenu
and Literature Overview.- Game Theory: an Overview.- Negotiation: an Overview.- Multiple-agent Systems: an Overview.- Distributed Production Planning in Reconfigurable Production Networks.- Distributed Models for Planning Capacity of Reconfigurable Production Networks at Medium Term.- Distributed Models for Plant Capacity Allocation.- Distributed Production Planning Models: an Integrated Approach.- Conclusions.