An experimental investigation of the effects of machining parameters on environmentally friendly grinding process

Grinding is a precision machining process which is widely used in the manufacture of components requiring fine tolerances and smooth finishes. Grinding is recognized as one of the most environmentally unfriendly manufacturing processes. The use of Minimum Quantity Lubrication (MQL) is of great significance in conjunction between large cutting fluids application and dry machining. It can reduce the amount of frictional heat generation and provide some cooling in the tool-workpiece interface and hence keep the workpiece temperatures lower than those in a completely dry machining. The ability to predict surface roughness and grinding force is important to many aspects of grinding process optimization, monitoring, and control. This paper presents the predictive modeling of surface roughness and grinding force based on a new semi-analytical model, and design and analyses of experiment, as a function of the grinding parameters, wheel types and coolant-lubricant properties. In addition, MQL oil flow rate, air pressure and nozzle distance to the grinding zone are adopted for evaluation by full factorial design of experiments. In this case, a 22 × 41 mixed full factorial design has been selected considering the number of factors used in the present study. The main effects of factors and interactions were considered in this paper, and regression equations were derived using response surface methodology (RSM).