Surface texturing is a process of fabricating specific patterns on a surface to enhance surface properties such as friction, contact area, air aspiration, wear, hydrophobicity, etc. Fabricating surfaces with planned micro features is an effective method to improve tribological performance of the interacting surfaces. Laser surface texturing process is one of the best suitable processes for producing micro-patterns. Micro textures are imparted on HSS discs using CO₂ laser, varying the shape and dimensions of the resulting dimples affecting the frictional coefficient and wear. Experiments have been accomplished to determine effects of textural variations such as areal density of dimples, dimple shape, area of dimples and depth of dimples on the Coefficient of Friction (COF) and Wear. Effects of lubrication conditions (Dry and Wet), pin material (MS, SS, EN31), applied load (25N, 50N, 75N) and Sliding velocity (400 rpm, 800 rpm and 1200 rpm) are evaluated on COF and Wear. Tests have been performed on pin-on-disk apparatus along guidelines of Taguchi L18 Orthogonal Array, keeping constant sliding distance of 940 m (about 10,000 cycles). Experimentally, it is found that wet lubricated, circular shaped dimples, with areal density 7.5%, dimple area 0.09 mm² with MS material pin provides best results. This experimental analysis has been performed to test the applicability, efficiency and reliability of the textured surfaces.

A high strength-to-weight ratio, stiffness, fatigue resistance, a low coefficient of thermal expansion, and tailorable properties make glass-fibre-reinforced plastic (GFRP) a popular choice for a wide range of applications, including aircraft structures, automobile chassis, and shipbuilding. However, milling GFRP composites is challenging because of their heterogeneous nature and two-phase structure, which lead to high cutting forces and delamination. A statistical experiment was carried out using the Taguchi design of experiments to investigate the effect of machining settings on GFRP composite performance metrics such as surface delamination, surface roughness, and material removal rate. The L27 orthogonal array was used for the experiment, and it served as the foundation for the choice of material, input variables, levels, and output response variables. The experiment’s outcomes were analysed using MINITAB software® 18 Version and the Analysis of Variance (ANOVA) method. Based on the signal-to-noise (S/N) ratio, the ideal conditions were selected, and confirmation studies were carried out to ensure their applicability. In order to identify the ideal circumstances for the manufacturing and machining parameters, the data were normalised to a range from zero to one. To overcome the difficulties involved in milling GFRP composites, a thorough investigation and optimisation of the manufacturing process factors and machining settings is essential.

There is a manufacturing system where several parts are processed through machining workstations and later assembled to form final products. In the event of disruptions such as machine failure, the original flow-shop schedule needs to be revised and/or rescheduled. In such a scenario, rescheduling methods based on right-shift rescheduling and affected operations rescheduling work very well. Here in this study, the deviation of the make-span of the revised schedule from the original schedule is used as a performance measure. We have proposed three rescheduling methods. There are multiple factors that influence the performance of the rescheduling methodology. One of them is the make-span deviation of the schedule, and the factors influencing it are optimality of the initial solution, failure duration, deviation of make-span, rescheduling method, size, and instant of failure. The initial schedule and problem size depend on the flow-shop manufacturing system for which scheduling is performed, but the method of rescheduling depends on the decision as to which rescheduling methodology is to be selected. Computations are performed using full factorial experimentation. We also observed that right-shift rescheduling is the preferred rescheduling method in the majority of situations. In contrast, the affected operation rescheduling method is also equally suitable when the initial solution is created using modified bottleneck minimum idleness.