A Statistical Optimization Model for the Erosive Wear of Organic Coatings Due to Blast-Cleaning With Copper Slag and Steel Grit

Abstract This article is concerned with statistical investigations into the removal of organic protective coating systems from steel substrates through compressed-air blast cleaning. A tribological system for the solid particle erosion is presented. Response parameters include cleaning rate and grit consumption, and the results are statistically interpreted based on the design of experiments and analysis of variance. Four factors are varied, namely, static air pressure, nozzle diameter, grit size, and valve opening degree. Two grit materials, steel grit and copper slag, are considered. The cleaning rate increases with increasing air pressure and, for copper slag, nozzle diameter, and with decreasing grit size. The valve opening degree and nozzle diameter (for steel grit) exhibit a more complex behavior with optimum values for maximum cleaning rates. The effects of the factors depend strongly on the grit type. However, air pressure is the only significant factor for steel grit, and nozzle diameter, air pressure, and valve opening degree are extremely significant factors for copper slag. Grit size is insignificant for both grit types. Values for the optimum grit flowrates are lower for steel grit (40–50%) compared with copper slag (75%). A four-parameter full quadratic regression model is found to be capable of statistically describing the relationships in the scope of the evaluation effort. An optimization procedure for steel grit, based on a desirability function approach, delivers a set of optimum factor combinations.