Integrating Capacity and Logistics of Large Additive Manufacturing Networks

Among future manufacturing systems, we are going to see networks of intelligent and autonomous entities sharing manufacturing resources, knowledge and information. Possible advantages are relevant, such as increasing overall production efficiency and product variety as well as reducing responsiveness and lead times. This paper focuses on the architectures and dynamics of productive-demanding nodes in a Scattered Manufacturing (SM) Network, with an application in Additive Manufacturing scenarios. SM allows launching production orders everywhere anytime inside the domain of the network. These autonomous nodes can rely on on-demand manufacturing services by sharing resources in a geographically distributed network. One possible approach is the introduction of a platform to coordinate the dynamics along the network according to principles of sustainability, equated shared resources and transparency by managing communication activities among nodes. To identify variables/factors that affect the system, a unique model is proposed by combining different perspectives, which focus on: a) decomposition and localization of demanding node's order into subtasks of variable size; b) tasks allocation criteria among geographically distributed nodes; c) logistics issues related to the localization of productive nodes. In particular, the model, with the aim of optimizing the overall manufacturing and logistics costs, suggests either logistics paths along the sub-network or tasks assignment criteria and scheduling in geographically distributed nodes. (C) 2019 The Authors. Published by Elsevier Ltd.