Millions of holes are produced in many industries where efficient drilling is considered the key factor in their success. High-quality holes are possible with the proper selection of drilling process parameters, appropriate tools, and machine setup. This paper deals with the effects of drilling parameters such as spindle speed and feed rate on the chips analysis and the hole quality like surface roughness, hole size, circularity, and burr formation. Al7075-T6 alloy, commonly used in the aerospace industry, was used for the drilling process, and the dry drilling experiments were performed using high-speed steel drill bits. Results have shown that surface roughness decreased with the increase in spindle speed and increased with the increase in the feed rate. The hole size increased with the high spindle speed, whereas the impact of spindle speed on circularity error was found insignificant. Furthermore, short and segmented chips were achieved at a high feed rate and low spindle speed. The percentage contribution of each input parameter on the output drilling parameters was evaluated using analysis of variance (ANOVA).

This paper deals with an experimental investigation of hole quality in Al2024-T3, which is one of the aerospace alloys used in aircraft fuselage skin due to its high level of resistance to fatigue crack propagation. The experiments are conducted with 6 mm uncoated carbide and HSS drill bits using a CNC machine under dry conditions and different drilling parameters. The characteristics of the hole quality are investigated in terms of its perpendicularity, cylindricity, circularity and hole size. An ANOVA (analysis of variance) and Pareto charts are used to analyze the effects of the drilling parameters on the hole quality. The hole quality is also assessed using a digital microscope to observe the formation of hole burrs. Moreover, scanning electron microscopy is also used to investigate the inside-hole surface defects. Further investigations are carried out using optical microscopy to inspect the post-drilling tool condition at high drilling parameters. The results show that hole quality reduces as the feed rate and spindle speed increase. However, from the ANOVA results and Pareto charts, the influence of the feed rate on the hole quality is found to be insignificant. At the same time, the type of drill bit material shows the highest percentage of contribution affecting the hole quality, following the spindle speed. The HSS drill bit shows more adhesion and built-up edges than the uncoated carbide drill bit. There were more burrs formed at the hole edges when the holes were drilled with uncoated HSS drill bits. In the same way, the SEM analysis reveals more surface deformation and damage defects inside the hole walls of holes drilled using the uncoated HSS drill bit.

The Weibull algorithm is one of the most accurate tools for forecasting and estimating wind energy potential. Two main parameters of the Weibull algorithm are the ‘Weibull shape’ and ‘Weibull scale’ factors. There are six different numerical methods to estimate the two Weibull parameters. These six methods are the empirical method of Justus (method 1), the empirical method of Lysen (method 2), the maximum likelihood method (method 3), the modified maximum likelihood method (method 4), the energy pattern factor method (method 5) and the graphical method (method 6). Many commercial wind energy software programs use the Weibull algorithm, and these six methods are used to calculate the potential wind energy at a given site. However, their accuracy is rarely discussed, particularly regarding wind data height. For this purpose, wind data measured for a long period (six years) at real sites are introduced. The wind data sites are categorized into three levels, i.e., low, medium, and high, based on wind data measurement height. The analysis shows that methods 1 and 2 are the most accurate methods among all six methods at low and medium heights. The number of errors increases with the height of these two methods. Methods 3 and 4 are the most suitable options for larger heights, as these scenarios have minimal error. The present study’s findings can be used in various fields, e.g., wind energy forecasting and wind farm planning.

The drilling process plays a crucial role in the assembly process of modern‐day manufactories. One of the major causes of component rejection during drilling operations is the incorrect selection of spindle speed and feed rate. Therefore, this study aimed to investigate the impact of process factors such as spindle speed and feed rate on torque, thrust force, temperature surface roughness, and chip formation during the drilling of AISI 1020 mild steel. A combination of finite element modeling and experimental investigation was employed to achieve the process. Specifically, the commercially available finite element software, Deform 3D, was used for simulation. The modeling results were then compared and validated with the experimental data. A high‐speed steel drill bit was utilized during the modeling and experimentation. The spindle speed was varied at 330, 410, and 510 rpm, while the feed rates were set at 0.12, 0.2, and 0.3 mm/rev. The study’s findings suggest that the spindle speed has an inverse relationship with thrust force, torque, and surface roughness, whereas it has a direct relationship with temperature. Conversely, the feed rate directly correlates with thrust force, torque, temperature, and surface roughness. Additionally, an analysis of the chips produced during the experiments revealed the impact of the cutting conditions on chip formation. The study results showed a 2–10% discrepancy between the experimental and simulation data. The ANOVA results indicated that the feed rate contributes the most to thrust force and torque, with a percentage contribution of 61.73% and 59.87%, respectively, followed by spindle speed, with a percentage contribution of 37.09% and 38.89%, respectively. Furthermore, temperature influences spindle speed the most, followed by feed rate, with percentage contributions of 67.75% and 31.11%, respectively. Moreover, the feed rate’s percentage contribution to surface roughness is higher than the spindle speed, with a contribution of 66.20% and 32.18%, respectively.