The Size Effect in Micromachining

Abstract

The world is experiencing a growing demand for miniaturised products. Micro-milling, using carbide micro tools has the potential for direct, economical manufacture of micro parts from a wide range of workpiece materials. However, in previous studies several critical issues have been identified that preclude the direct application of macro machining knowledge in the micro domain through simple dimensional analysis. The research presented in this thesis focused on some of the areas that require development of the scientific knowledge base to enable determining improved microscale cutting performance. In the mechanical micro machining of coarse grained materials, the programmed undeformed chip thickness can be lower than the length scale of the workpiece grains. Moreover, when the microstructure of such materials is composed of more than one phase, the micro cutting process can be undertaken at a length scale where this heterogeneity has to be considered. Driven by this challenge, the material microstructure ?size effect? on micro-machinability of coarse grain steel materials was investigated in this PhD. In this regard, a predominantly single phase ferritic workpiece steel material and another workpiece material with near balanced ferrite/pearlite volume fractions was studied over a range of feedrates. The results suggested that for micro machined parts, differential elastic recovery between phases leads to higher surface roughness when the surface quality of micro machined multiphase phase material is compared to that of single phase material. On the other hand, for single phase predominantly ferritic materials, reducing burr size and tool wear are major challenges. In micro machining the so called ?size effect? has been identified as critical in defining the process performance. However, an extensive literature search had indicated that there was no clear reported evidence on the effect of process variables on driving this size effect phenomenon. It is often assumed in literature that the un-deformed chip thickness was the main factor driving the size effect. This limit manufactures to only altering the feedrate to try and influence size effect. To explore the significance of a range of inputs variables and specifically, cutting variables on the size effect, micro cutting tests were conducted on Inconel 718 nickel alloy. Taguchi methodology along with signal processing techniques were applied to micro milling acoustic emission signals to identify frequency/energy bands and hence size effect specific process mechanism. The dominant cutting parameters for size effect characteristics were determined by analysis of variance. These findings show that despite most literature focussing on chip thickness as the dominant parameter on size effect, the cutting velocity is a dominant factor on size effect related process performance. This suggests that manipulating the cutting speed can also be a very effective strategy in optimising surface finish in micro machining and in breaking the lower limit of micro machining.In micro machining the lower limit of the process window is set by the minimum chip thickness. Identifying this limit is thus important for establishing the process window. Process windows are valuable guidelines for industrial selection of cutting conditions. Additionally, understanding factors that influence the value of minimum chip thickness is even more important for progressing micro machining capability to the nano-scale machining regime. For this reason, in this PhD study, acoustic emission signatures emanating from microscale milling of six different workpiece materials were characterised to identify the rubbing mode and this enabled the identification of the threshold conditions for occurrence of minimum chip thickness. The minimum chip thickness predicted by this novel approach compares reasonably well to the values that exist in published literature. Additionally, the decomposition of raw acoustic signal allowed the determination of energy levels corresponding to deformation mechanisms. The PhD work provides significant and new knowledge on the utility and importance of acoustic emission signals in characterising chip formation in micro machining. A novel method for determining the minimum chip thickness was developed, micro machining chip formation mechanisms were identified and the machinability of coarse grained multiphase material is presented.