Nowadays, die manufacturing industries prefer eco-friendly machining, i.e., high-speed turning for hardened AISI S7 tool steel followed by the conventional grinding process. The effectiveness of this eco-friendly turning depends on selection of appropriate process parameters, which decides the surface integrity of machined components. Hence, the first objective of present research work is to optimize the turning parameters for lower cutting force, machining temperature, surface roughness and higher material removal rate simultaneously using grey relational analysis (GRA). ANOVA utilized to identify the significant effect of each turning parameter on the response variables. Secondly, the effects of turning parameters such as tool nose radius (R n), cutting speed (V c), feed rate (V f) and depth of cut (d c) on tool wear and finished surface topography were studied through scanning electron microscopy (SEM) and atomic force microscope (AFM). Optimal turning parameters for multi-performance responses were R n : 1.2 mm, V c : 450 m/min, V f : 0.05 mm/rev and d c : 0.2 mm. The confirmation test was conducted on the optimal parameter level. According to ANOVA, depth of cut was the major influencing factor on all response variables. AFM and SEM micrograph indicated that excellent surface quality with lower surface roughness (S a : 64.21 nm and S q : 90.34 nm) was observed at higher cutting speed. Flank and crater wear were observed in cutting tool faces owing to thermo-mechanical loading. Different wear mechanisms like abrasion, adhesion, built-up edge formation and chipping hammering were found in the alumina-mixed ceramic insert at higher cutting speed and depth of cut.

In this paper, a method of quantitative evaluation of surface roughness based on computer vision system is presented. A low cost computer vision system consisting of flat bed desktop scanner connected to personal computer (PC) is used. A large number of surface specimens such as EN-8, EN-9, cast iron, copper, brass, aluminium, C-20, C-45 steel etc. were carefully prepared by using various machining processes like planing, shaping, turning, milling, grinding, polishing etc. to generate a database of surface specimens with different lay-types and surface roughness values. This database is evaluated for conventional surface roughness parameters like Rt, Ra, Rq and for RGB colour component values at each pixel over the digital images of these produced surfaces. By using the technique of multiple linear regression analysis, the conventional roughness values and colur component values were correlated with each other to form a multiple linear regression equation for Rt. The value of surface roughness Rt obtained for a given specimen using this equation was then crosschecked and confirmed with the results obtained by using conventional method for the same specimen. When any test surface is introduced for surface roughness evaluation, the developed method relates the colour component values obtained from its surface image, to the conventional values like Rt, Ra, Rq. In addition to this, surface topographical representation and summits are also presented. Using this method even the evaluation of the surface roughness in the nano-metre level can be carried out to fulfill the requirements of experimental field of 0.001 to 50 microns.

Belt conveyor is the transportation of material from one location to another. Belt conveyor has high load carrying capacity, large length of conveying path, simple design, easy maintenance and high reliability of operation. Belt conveyor system is also used in material transport in foundry shop like supply and distribution of molding sand, molds and removal of waste. In this paper the study is carried out on DISA pattern moulding machine to meet the requirement of higher weight castings. The DISA machine is having the capacity of 100 moulds per hour. The mould size and density of material is given parameters. The present discussion aims to design the conveyor system used for cooling of mold, which includes speed, motor selection, belt specification, shaft diameter, pulley, idler spacing, gear box selection, with the help of standard practice and these results are verified with the belt comp software.

Resistance spot welding is the most preferred and widely used method for joining metal sheets in automotive and many other industrial assembly operations. The body of a car is typically joined by thousands of spot welds. One of the many geometrical factors affecting the final geometrical outcome of the metal part assemblies is the welding process considering welding sequence used when the parts are welded together. The spot welds guarantee the strength of the car, but their positions also affect the geometrical quality of subassemblies and the final product. In practice, the positions of the weld points often deviate from nominal position. By analyzing industrial scanning data, deviations of spot weld positions are found to be of magnitudes up to 19 mm. In this paper, the influence of variation in position of spot welds is investigated with respect to geometrical quality, by simulating and analyzing the geometrical variation of an A-pillar assembly.

The aim of this paper is to achieve optimisation of spot welding sequence to minimise the distortion of a sheet metal assembly. The distortion of the assembly involving number of spot welds is different for different sequences of welding The assembly consists of sheet metal components which are joined by using various welding sequence schemes. The components are manufactured in quantity and welding with various sequences. After welding the distortions in an assembly due to welding sequence change are worked out and compaired. The sequence with minimum distortion is suggested a solution for the quality manufacturing with minimum distortion induced in it.