Multi-Objective Optimization of Traverse Grinding Operation on D2 Steel Work Rolls Using Evolutionary Algorithm

Grinding is a complex manufacturing process with a large number of interacting variables. The work rolls used in Sendzimir mills were ground in the roll grinding shop to remove the marks formed on the surface of the work rolls during rolling. Since Sendzimir mills were driven by contact friction, the work roll should have suitable roughness for thickness reduction. This paper presents the selection of optimal parameters for the grinding of work rolls by considering three objectives such as, minimizing surface roughness in work rolls, minimizing power required at grinding spindle and maximizing the material removal rate. In this study, six factors such as wheel speed, work speed, traverse speed, infeed, dress depth and dressing lead were considering to develop a response surface model using BoxBehenken design matrix with six central points. Genetic algorithm approaches were used to optimize the three conflicting objectives using weighing sum approach. The decision maker can choose any weightage combinations to satisfy his/ her requirement.