Applications of the Monte Carlo simulation method in tool selection for punching operations in the sheet metal industry

The main effort in generating a production plan for punching operations lies in the process of tool selection. In the modern sheet metal industry the selection of a suitable set of tools for the fabrication of a flat sheet metal part, using punching and/or nibbling operations, is a major economic issue for two reasons. Firstly, tooling is very expensive and should be minimised. Secondly, if tool capacity of the tool rack is exceeded, expensive setups are required to mount different tools in the rack and to program the system. The approach used in this paper is to develop a genetic algorithm to select the best set of tools for producing a given sheet metal part, based upon searching a huge explosive decision tree which, in a practical sense is impossible to solve analytically. This paper shows how the well-known Monte Carlo simulation technique can be used in the decision tree search and hence in the process of selecting appropriate tooling. The method makes the selection of the best set of tools to produce any given sheet metal design, without any restriction on the geometry of the features involved