The present research employs the statistical tool of Response surface methodology (RSM) to evaluate the machining characteristics of carbon nanotubes (CNTs) coated high-speed steel (HSS) tools. The methodology used for depositing carbon nanotubes was Plasma-Enhanced Chemical Vapor Deposition (PECVD). Cutting speed, thickness of cut, and feed rate were chosen as machining factors, and cutting forces, cutting tooltip temperature, tool wear, and surface roughness were included as machining responses. Three-level of cutting conditions were followed. The face-centered, Central Composite Design (CCD) was followed to conduct twenty number of experiments. The speed of cutting and rate of feed have been identified as the most influential variables over the responses considered, followed by the thickness of cut. The model reveals the optimized level of cutting parameters to achieve the required objectives. The confirmation experiments were also carried out to validate the acceptable degree of variations between the experimental results and the predicted one.

In this study, the uncertainty of measurement paths was estimated using selected statistical methods. Specifically, temperature measurements obtained from contact temperature sensors used in a heat transfer test section were investigated. The experiments utilized a drywell temperature calibrator, thermoelements (types K, J, N, and T), and a data acquisition station. Additionally, a certified Pt-100 resistance sensor connected to the temperature meter was considered during measurements. The temperature range for the selected measurement points was 0.3 to 100 °C, covering both increasing and decreasing temperatures. To calculate the expanded uncertainty, both the uncertainty propagation method and the Monte Carlo method were employed. The results were analyzed and found to be similar.