Hybrid adaptive control of CNC drilling for enhancement of tool life and surface quality

The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process

(2019) Aitor Duo et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Monitoring of drill runout using Least Square Support Vector Machine classifier

(2019) J. Susai Mary et al.   MEASUREMENT

Experimental investigations and empirical modeling for optimization of surface roughness and machining time parameters in micro end milling using Genetic Algorithm

(2018) S.P. Leo Kumar   MEASUREMENT

Accuracy of a new online method for measuring machining parameters in milling

(2018) E. Leal-Muñoz et al.   MEASUREMENT

Adaptive control by multi-objective optimisation for drilling process with fuzzy inference system and neural predictive controller

(2017) J Susai Mary et al.   INSIGHT

Multi response optimization of cutting parameters in drilling of AISI 304 stainless steels using response surface methodology

(2016) M Balaji et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE

Development of an Adequate Online Tool Wear Monitoring System in Turning Process Using Low Cost Sensor

(2012) Jaharah A. Ghani et al.  

Advanced monitoring of machining operations

(2010) R. Teti et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

Fuzzy-logic control of cutting forces in CNC milling processes using motor currents as indirect force sensors

(2010) Dohyun Kim et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

An experimental investigation on monitoring of crater wear in turning using ultrasonic technique

(2009) D. Dinakaran et al.   INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE

An Adaptive Fuzzy Controller for Constant Cutting Force in End-Milling Processes

(2008) Chengying Xu et al.   JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME