Production Planning in Production Networks: Models for Medium and Short-term Planning

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 the extended enterprise.