OPTIMIZATION OF VARIOUS PARAMETERS RELATED TO GLASS SCRATCHES REMOVING CHEMICAL COMPOSITION

Glass is a common material in a world who's daily uses are in every person's life, is given by some simple examples like drinking vessels, insulation, windows, displays and optical fibers. By modified the glass surface it is possible to change the performance of the entire glass object, generally known as Surface Engineering. In my work a new efficient algorithm is used to remove mark and scratches with the help of composition of chemicals. Glass scratch and repair has been revolutionized with innovative techniques specially designed to meet our needs. Several glass scratches and or damaged glass due to mineral deposits can now be removed with composition of chemicals. Scratches on auto glass, window glass, glass furniture, glass door and innovative construction scratches glass can now be repaired with the help of composition of chemicals. Glass manufacturers, construction developers, property maintenance establishments and any independent technician can remove unwanted glass scratches and glass damage efficiently and effectively. Grey based Taguchi methodology was adopted to achieve the said objectives. Three factors L- 9 orthogonal array was used to plan the experiments with each of 27 experiments conducted twice. A chemical composition was used to conduct the experiments. Width of the scratches can be remove with the help of the chemical composition on the glass jar or beaker and also to see the width of scratch remove with the help of microscope and time is to be calculated with the help of stop watch. S/N ratios and grey relational coefficients of width and time period were separately calculated, optimal setting of control parameters and finally the expected single valued grey relational grade was calculated whose value was 0.7. Confirmation experiments under optimal setting of control parameters were conducted to verify the expected value of grey relational grade which was found out to be 0.7. Rubbing Alcohol with 66.15 % contribution was the most significant factors followed by Bug Spray with 07.90 % and salt with 0.09% contribution using ANOVA. It was thus clear that all of these factors have significant contributions towards the two performance characteristics.