Abstract
Based on a cost analysis, a method of identifying and predicting optimum replaced grinding wheel diameter (De.op) in a surface grinding operation for 9CrSi steel material was developed in this study. The De.op value was determined by minimizing the cost function. An experimental design was set up, and a computational program was developed to perform the experiment in order to calculate the De.op value. Furthermore, the impact of the grinding process parameters such as the initial grinding wheel diameter, the grinding wheel width, the total dressing depth, the Rockwell hardness of the workpiece, the radial grinding wheel wear per dress, and the wheel life on the De.op value were investigated. Moreover, the impacts of the cost components such as the machine tool hourly rate and the grinding wheel cost on the De.op value were given. Based on that, a mathematical model was proposed to determine the De.op value. The predicted De.op value was also verified by an experiment. The obtained result shows that the difference between the experimental De.op value and the predicted De.op value is within 1.7%, indicating that the mathematical model proposed in the study is reliable.
Highlights
Grinding is an operation applied in almost every type of manufacturing process
Previous research works have studied the problem of optimizing technology parameters in order to enhance quality and productivity in grinding processes
The relevance to the optimization of grinding and dressing parameters has been proposed for maximizing the material removal rate [3], minimizing the grinding time [6], as well as minimizing the dressing and grinding costs [7]
Summary
Grinding is an operation applied in almost every type of manufacturing process. The grinding process is extensively used during finishing operations for discrete components [1,2]. Previous research works have studied the problem of optimizing technology parameters in order to enhance quality and productivity in grinding processes. The relevance to the optimization of grinding and dressing parameters has been proposed for maximizing the material removal rate [3], minimizing the grinding time [6], as well as minimizing the dressing and grinding costs [7] These works have implemented optimization problems with different grinding methods such as external cylindrical grinding [4,8,9], surface grinding [10,11,12,13,14,15], and internal grinding [16]. In a recent study [9], Pi et al presented a cost optimization method for internal cylindrical grinding operations. The research results will help manufacturers solve the problem of selecting conditions for initial technological parameters since they allow manufacturers to determine and set up optimal parameters of pre-machining grinding conditions to increase the economic and technical effectiveness of the grinding process
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