Rapid tooling route selection and evaluation for sand and investment casting

Abstract

Today, a number of direct routes using rapid prototyping (RP) processes (fused deposition modelling (FDM), laminated object manufacturing (LOM), stereolithography apparatus (SLA), selective laser sintering (SLS), etc.), as well as indirect routes (RP coupled with secondary or soft-tooling processes like RTV vacuum casting) are available for rapid fabrication of tooling for sand and investment casting processes. Each route is unique in terms of geometric, material, quality and cost characteristics; no comprehensive database of their capabilities has been reported, especially for metal casting applications. The problem of selecting the optimal rapid tooling (RT) route is a complex multi-criteria decision-making problem. This paper describes a systematic approach for RT route selection and planning. A database of RT process capabilities was generated through benchmarking experiments, covering 20 different widely used RT routes (both direct and indirect: two- and three-step processes) involving an impeller pattern. In this approach, RT process route selection involves translating the tooling requirements specified by the casting engineer into weighted tooling attributes using quality function deployment and analytic network process (QFD-ANP), which along with part specifications is used for RT route selection by calculating the overall process compatibility indices. The routes are ranked as per the value of the overall compatibility index. Once the optimal route is selected, process planning is carried out by retrieving a similar process plan using case-based reasoning (CBR). The methodology has been implemented in a software program using Visual C + + programming language in a Windows environment. The methodology is demonstrated and validated with an industrial example of a separator body casting. It has proved to be a robust evaluation and decision-making tool for selecting appropriate tooling route for a given casting based on customer requirements.