Abstract
The concept of virtual machine tool (VMT) is introduced in this paper to specify machining resources of multi-functional machine tools. A two-level model for makespan minimization in a flow shop is developed in multi-functional machine tool environments. The model is first optimized with an Hopfield neural network to find the optimal processing sequence for components to visit all the necessary VMTs. Secondly, according to a set of shop floor control rules, the VMTs for components machining are matched with real machine tools. This procedure is driven by the events taking place in components machining, such as the arriving or the finishing of a component. Numerical experiments are conducted in a number of flow shop scheduling problems up to 8×8 and the mean relative optimizing rate is employed to assess the results of numerical experiments.
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