Adaptive Production Control in a Modular Assembly System xe2x80x93 Towards an Agentbased Approach In industry, individualization leads to a slow replacement of assembly line production with more flexible modular assembly systems. In modular systems, each product can be completed on multiple routes through a grid of modular workstations, where transportation is handled by automated guided vehicles (AGV). In order to benefit from this routing flexibility and to react on disturbances in the system, new robust control approaches are crucial. While optimizing the production flow globally is limited by computing power, this work presents a decentralized control approach that reduces complexity by dividing the problem into subproblems: A job release agent releases jobs at certain points in time according to the systemxe2x80x99s inventory level. Each job in the system is linked to a job routing agent regularly choosing the optimal route out of the options given by the productxe2x80x99s flexibility. Every modular station is represented by a workstation agent optimizing the workstationxe2x80x99s schedule. Lastly, a vehicle agent assigns transports optimally to the AGVs and coordinates them accordingly. An evaluation example emphasized the decentralized approach as a valid way for realtime robust control solutions, where the makespan was about five percent away from the static optimum.

A Reusable Scheduling Problem Decomposition Framework for Smart Factories In most scheduling problems, such as plant and supply chain problems, the linkages between resources, and operations are often clearly demarcated due to their lateral, sequential nature. In comparison, the combinatorial nature, arising from the inherent network structure of a flexible manufacturing system problem causes the associated jobs, automated guided vehicles and job shops to be intermeshed topologically and temporally. The temporal and spatial network structure impedes direct application of conventional decomposition approaches. In this study, a reusable scheduling problem decomposition framework for Industry 4.0 that facilitates agent embedded optimization is being proposed. Modularity is enabled when each agent and its respective governed resource or resource group is replaceable by one that is similar in functionality, but possibly of a different layout. This schema is attractive to potential schedulers as the plugandplay nature of resources, via modularity, optimizes user friendliness via minimal customizations.