APPLYING MULTI-CRITERIA DECISION)MAKING METHODS FOR CUTTING OIL SELECTION.

Many machining processes would not be possible with)out the presence of cutting oils. There are many different types of cutting oils on the market today, each with different properties. The difference of oils is manifested in many parameters such as viscosity, combustion tempera)ture, recyclability, pollution tendency, stability, price, etc. Choosing the best oil is a difficult and tedious task for customers. In this work, we present the results of a study on the selection of cutting oil using multi-criteria decision-making (MCDM) methods. The selection of the best oil is made on the basis of ranking of seven different types. Two MCDM methods used in this study are Proximity Indexed Value (PIV) and Collaborative Unbiased Rank List Integration (CURLI). This two methods have been used to rank cutting oils. These are two methods with com)pletely different characteristics. When using the PIV method, it is necessary to standardize the data and deter)mine the weights for the criteria. Meanwhile, if using the CURLI method, these two tasks are not needed. In addi)tion, three different weight methods were also used to calculate the weights for the criteria including EQUAL, Rank Order Centroid weight (ROC weight) and Rank Sum weight (RS weight). These three methods have been used to determine the weights for the criteria of cutting oil. The PIV method was used three times corresponding to three different weight methods. The results showed that out of the four ranking results (three using the PIV method and one using the CURLI method), the same best oil was unanimously identified. It is recommended that the CURLI me)thod should be used if weighting of criteria and data nor)malization are not desired. [ABSTRACT FROM AUTHOR]