## 4 Experimentation  
### Experimental Setup and Data Acquisition  
Experiments were performed in the Industrial Automation Lab of College of EME, National University of Sciences and Technology, Islamabad, Pakistan. A Denford Cyclone P with a built-in Fanuc 21i-TA control, Computer Numerical Control (CNC) lathe machine was used to perform the turning operation on three types of materials: Aluminum, mild steel and Teflon, with two types of tooltips: Carbide and high-speed steel (HSS). Figure 6 shows the complete experiment categorization. In total, six cases were formed with all the combinations of tools and workpieces used during experimentation. For classification purposes, the acoustic emission signals of the new, used, and worn-out tool were recorded using a standard microphone with a sampling frequency of 44,100 Hz. The turning operation parameters are shown in Table 1.  
Figure 5: Spectrogram generation from time-domain signal [19].  
Figure 7 shows the complete machining and data acquisition process where a workpiece is gripped by a chuck of the CNC machine for turning operation, and the tool holder with different tool types for the selection of tool material and shape can be observed. The typical microphone used as an airborne acoustic emission sensor is placed between the workpiece and tool with a minimal distance between machining location and microphone, in order to acquire the AE signal with the least background noise. The signal is being recorded with a built-in Windows(r) 10 voice recording application through a laptop having a 3.5 mm audio jack.  
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Feed Rate** & **RPM** & **Depth of Cut** \\ \hline
200 mm/min & 1500 rev/min & 1 mm \\ \hline \hline \end{tabular}
\end{table}
Table 1: Turning operation parameters.  
Figure 6: Visual description of experiment group showing all six cases with work-pieces represented by blue boxes and tooltips and their categorization by white boxes.  
Figure 7: (**Left**) View of the whole experimental setup for computer numeric control (CNC) turning operation and data acquisition. (**Right**) Zoomed view of the setup illustrating the details of orientations.  
Figure 8 shows all three types of workpieces on which the turning operation has been performed with two different types of tools. Figures 9 and 10 show all the categories of the carbide and HSS tool utilized as new, used, and worn-out tool conditions. In the literature, flank and cater wear of the tools are mostly discussed, as they occur most during the machining processes and are major factors leading to workpiece surface roughness. The cutting force of a tool affects the tool wear, while interestingly, cutting force itself is dependent on tool condition. The greater the flank wear, the greater the tool and workpiece inter-friction would be, eventually increasing the thermal signature of both surfaces, resulting in higher cutting forces [21]. Cutting force also greatly relies on machining parameters. Higher feed rates and deeper depths of cuts generate a greater cutting force [22], tool wear and workpiece surface roughness [23]. A carbide tool is harder while a HSS tool is tougher; a carbide tool has more abrasion resistance while the HSS tool has more local deformation resistance [24]. On the other hand, workpiece material also greatly affects the tool life [25]. In this experiment, the hardest workpiece material used is mild steel, aluminum being moderate and Teflon being the softest. The worn-out tool category has had artificially induced mechanical fractures through a hammer, while used tool category tools have been in use at the Lab of College before the experimentation performed with considerable usage cycles.