An optimization method for shopfloor material handling based on real-time and multi-source manufacturing data

With the wide use of auto-ID devices in manufacturing shop floors, it creates a huge number of real-time and multi-source manufacturing data. To make a better decision based on the real-time and multi-source manufacturing data, in this paper, a dynamical optimization model for shopfloor material handling (DOM-SMH) is designed. Contrast to a traditional material handling method, each trolley is an active entity which will request the transport tasks. Then, the optimal transport tasks will be assigned to the optimal trolleys according to their real-time status. The key technologies such as intelligent trolley, real-time information exchange and optimization for material handling tasks are designed and developed to implement the dynamical optimization model. The presented method is demonstrated by a case study, and its effectiveness is also analyzed and discussed through the empty-loading ratio and total distance.