Modelling of physical vapour deposition (PVD) process on cutting tool using response surface methodology (RSM)

摘要

The Physical Vapour Deposition (PVD) magnetron sputtering process is one of thewidely used techniques for depositing thin film coatings on substrates for variousapplications such as integrated circuit fabrication, decorative coatings, and hard coatingsfor tooling. In the area of coatings on cutting tools, tool life can be improved drasticallywith the application of hard coatings. Application of coatings on cutting tools for variousmachining techniques, such as continuous and interrupted cutting, requires differentcoating characteristics, these being highly dependent on the process parameters underwhich they were formed. To efficiently optimise and customise the deposited coatingcharacteristics, PVD process modelling using RSM methodology was proposed. The aimof this research is to develop a PVD magnetron sputtering process model which can predictthe relationship between the process input parameters and resultant coating characteristicsand performance. Response Surface Methodology (RSM) was used, this being one of themost practical and cost effective techniques to develop a process model. Even thoughRSM has been used for the optimisation of the sputtering process, published RSMmodelling work on the application of hard coating process on cutting tool is lacking.This research investigated the deposition of TiAlN coatings onto tungsten carbidecutting tool inserts using PVD magnetron sputtering process. The input parametersevaluated were substrate temperature, substrate bias voltage, and sputtering power; the output responses being coating hardness, coating roughness, and flank wear (coatingperformance). In addition to that, coating microstructures were investigated to explain thebehaviour of the developed model. Coating microstructural phenomena assessed were;crystallite grain size, XRD peak intensity ratio I111/I200 and atomic number percentageratio of Al/Ti.Design Expert 7.0.3 software was used for the RSM analysis. Three processmodels (hardness, roughness, performance) were successfully developed and validated.The modelling validation runs were within the 90% prediction interval of the developedmodels and their residual errors compared to the predicted values were less than 10%. Themodels were also qualitatively validated by justifying the behaviour of the outputresponses (hardness, roughness, and flank wear) and microstructures (Al/Ti ratio,crystallographic peak ratio I111/1200, and grain size) with respect to the variation of theinput variables based on the published work by researchers and practitioners in this field.The significant parameters that influenced the coating hardness, roughness, andperformance (flank wear) were also identified. Coating hardness was influenced by thesubstrate bias voltage, sputtering power, and substrate temperature; coating roughness wasinfluenced by sputtering power and substrate bias; and coating performance was influencedby substrate bias.The analysis also discovered that there was a significant interaction between thesubstrate temperature and the sputtering power which significantly influenced coatinghardness, roughness, and performance; this interaction phenomenon has not been reportedin previously published literature. The correlation study between coating characteristics,microstructures and the coating performance (flank wear) suggested that the coatingperformance correlated most significantly to the coating hardness with Pearson coefficientof determination value (R2) of 0.7311. The study also suggested some correlation betweencoating performance with atomic percentage ratio of Al/Ti and grain size with R2 value of0.4762 and 0.4109 respectively.