Risk assessment for multiple automated guided vehicle manufacturing network

Automated guided vehicles (AGVs) are moving devices for material handling in a manufacturing system through a network of guide paths. The network is configured of nodes of work stations and arcs of guide paths. To obtain this more availability of the system having reliable arcs are desirable. Advanced manufacturing systems feasibility is considered via economic evaluation. Thus, this work proposes a risk based dynamic program to determine more reliable arcs for fortification purposes. With respect to the multi stage decision making process of the multiple AGVs on different arcs, we develop a dynamic program being a useful tool for multi stage decision making. To counteract the dynamism of data in different time periods, Bayesian approach is employed to determine the loss function of moving through the stages of the proposed AGV routing network. By increasing the number of nodes and AGVs the problem is considered in NP-hard class, and thus the required effort for optimization motivates to develop a heuristic solution approach.