Fuzzy Logic-Based Prediction of Drilling-Induced Temperatures at Varying Cutting Conditions along with Analysis of Chips Morphology and Burrs Formation

Abstract

Friction and plastic deformation at the tool–chips interaction during a dry drilling process results in temperature rise and promotes tool wear and surface roughness. In most of the components produced in industries, a drilling process is used to make a hole for final assembly. Therefore, knowledge of temperatures produced during drilling operation at various machining input parameters is required for the best quality product. A fuzzy logic-based algorithm is developed to predict the temperature generated in the drilling process of AISI 1018 mild steel. The algorithm used speed and feed rate of the drill bit as input parameters to the fuzzy domain. A set of rules was used in the fuzzy domain to predict maximum temperature produced in the drilling process. The developed algorithm is simulated for various input speed and feed rate parameters and was verified through the maximum temperature measured during drilling of the studied material at selected speed–feed combinations. Experiments were conducted to validate the results of developed fuzzy logic-based algorithm by using non-contact infrared pyrometer for drilling of AISI 1018 steel. A good agreement between the predicted and experimentally measured maximum temperature was observed with an error less than 6%. It is found that temperature increases with increase in cutting speed and feed rate. Size of roll back burr formation at the hole perimeter significantly increases with increase in drill speed and feed rate. Segmental continuity in spiral or helix chips morphology is more at low feed and high cutting speed. Chip radius increases with increase in feed rate and results in damaging of the machined surface and causes burr formation while the radius decreases with cutting speed along with improved hole surface finish.