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In the current scenario of automotive manufacturing industries, high quality and zero rejection is the point of concern. Most of the companies are using six sigma methodology to optimize the quality of the product. Shainin has proposed many competent designs of experiment (DOE) tools to identify the root cause of product variation so that optimization can be done at six sigma level. In this study, DMAIC (Define-Measure & Analysis-Improve-Control) technique along with Shainin DOE tools is applied. The component search tool is used to identify the root cause of the rear fender offset at motorbike assembly line. Assembly process is found responsible for variation during hypothesis testing. Further investigation revealed that bracket hole diameter is required to be modified. Better (B) vs Current (C) tool is applied for validation of product performance.

Minimum quantity lubrication (MQL) is a traditional and worldwide accepted method for machining. To achieve better economy, environment and human wellness, MQL is preferred instead of flood cooling technique. In this study, the MQL method is applied during face milling of Al-6061using TiN coated carbide inserts. Coolant flow rate (CFR) along with cutting velocity and feed per revolution is selected as input process parameters to optimize the surface finish. In the design of experiments (DOE), Taguchi L9 orthogonal array is chosen for experimentation. Signal to noise (S/N) based on ‘smaller the better’ (surface finish) is calculated for each experiment. Analysis of means is applied to evaluate the optimum settings of input parameters. Significance and contribution of each parameter are evaluated by using analysis of variance (ANOVA). Results of ANOVA show that feed per revolution has a major contribution of 69.947% on surface finish.