This is an open access article distributed under the CC BY 4.0
Volume 20 article 971 pages: 634-643
In the case of highly precise flat surfaces, surface roughness and flatness tolerance (FL) play virtual roles and directly cause the performance of the parts. In general, both surface roughness and FL are required at the minimum value. Grinding is needed in order to finish the surface. However, sometimes in specific grinding conditions, this could not be achieved. Hence, it is imperative to select the grinding conditions that satisfy both parameters to be considered “minimum”. This problem is commonly known as multi-criteria decision making (MCDM). However, choose a method to determine the weights for the criteria sometimes makes the decision-makers confused because each method of determining the weights finds different sets of the weight values. Along with that, for each method of determining the weight, the ranking results of the alternatives may also be changed. Using an MCDM method without specifying weights for the criteria eliminates this problem. Collaborative Unbiased Rank List integration (CURLI) is one of the multi-criteria decision making methods that do not need to determine the weights for the criteria. In this research, we not only applying CURLI method to multi-criteria decision making, but also developing detailed steps to apply. This work has not been done before even for the authors who proposed it. Using this method for multi-criteria decision-making, the grinding process has determined the abrasive grain size, workpiece velocity, feed rate and depth of cut to ensure that the surface roughness and FL are kept to a minimum.
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