A hybrid system combining rapid prototyping and CNC machining operation

Abstract

At present, two important processes, namely CNC (Computer Numerical Control) machining and rapid prototyping (RP) are being used to create prototypes and functional products. CNC machining (subtractive method) is relatively more precise and accurate, but it is tough to create stuffs with complex features. RP (additive method), by contrast, is able to form parts with sophisticated features, that consents materials to be utilized more efficiently. Combining both subtractive and additive process on a single platform has significant advantages. However, there are two important aspects need to be taken into consideration for this process hybridization. First aspect is the integration of two different control systems for two processes and second aspect is maximizing workpiece alignment accuracy during the changeover step. This research attempts to assimilate both of these processes and propose a new design of hybrid machine with the purpose of overcoming the drawbacks related with different control panel and misalignment issues. Fused deposition modeling (FDM) is considered as the RP process in this study. A new innovative design for hybrid system, consisting of CNC machining and FDM, was proposed in this study. One of the aspects of the design consist of installing the CNC cutting spindle and the heat extruder of FDM on a rotary stage and using the IR sensors which makes the mechanism simpler and overcomes the problem of misalignment. The rotary stage has also given the advantage of using the 3-axis machine as a 4-axis machine. The other feature of this research was the single control panel for both CNC machining and FDM operation. The case studies undertaken in this research demonstrated that the proposed hybrid system can conduct three-axis machining on a completed FDM part or trim the surface of the parts with two different layers fabricated by FDM to achieve more accurate dimensions or better surface finish. Several objects were produced with different layer thickness for example 0.1 mm, 0.15 mm and 0.2 mm. About 99.87% accurate dimension was achieved after CNC grinding operation. Finally, dimensional accuracy was improved by 92% when the FDM part is compared with the final part after grinding operation. At the same time average surface roughness (Ra) was reduced by 90%. It was also observed that layer thickness plays a role on the dimensional accuracy and best accuracy is achieved with the minimum layer thickness (0.1 mm).