The development of an end-milling process depth of cut monitoring system

Efforts to manage end-milling cutter-tool life depend upon the accuracy of the information used in the assessment of the work done. This presents a problem in many instances because the measurement of cutting-related parameters is difficult, especially when the operations being undertaken do not form part of a repeated manufacturing cycle. This paper presents a methodology utilising ultrasonic sensors for the real-time monitoring of the depth of cut arising during end-milling operations. The paper outlines the architecture of a tool condition monitoring system based upon state of the art microcontrollers. It then considers how depth of cut information can be integrated into such a system in order to support effective end-mill tool-life management functions.

[1]  Roger Ivor Grosvenor,et al.  A review of the evolution of microcontroller-based machine and process monitoring , 2005 .

[2]  Changqing Liu,et al.  Robustness improvement of tool life estimation assisted by a virtual manufacturing cell , 2006 .

[3]  D. E. Dimla,et al.  Sensor signals for tool-wear monitoring in metal cutting operations—a review of methods , 2000 .

[4]  H. Shao,et al.  A cutting power model for tool wear monitoring in milling , 2004 .

[5]  Jin Jiang,et al.  Erratum to: State-of-the-art methods and results in tool condition monitoring: a review , 2005 .

[6]  Frank Lemke,et al.  Modeling tool wear in end-milling using enhanced GMDH learning networks , 2008 .

[7]  Yusuf Altintas,et al.  In-process detection of tool breakages using time series monitoring of cutting forces , 1988 .

[8]  Isa Yesilyurt,et al.  End mill breakage detection using mean frequency analysis of scalogram , 2006 .

[9]  Roger Ivor Grosvenor,et al.  Sweeping filters and tooth rotation energy estimation (TREE) techniques for machine tool condition monitoring , 2006 .

[10]  Roger Ivor Grosvenor,et al.  A Microcontroller-Based Milling Process Monitoring and Management System , 2007 .

[11]  Debasis Sengupta,et al.  Cutting force-based real-time estimation of tool wear in face milling using a combination of signal processing techniques , 2007 .

[12]  Romero-Troncoso René de Jesús,et al.  Driver current analysis for sensorless tool breakage monitoring of CNC milling machines , 2003 .

[13]  P. C Tseng,et al.  The intelligent on-line monitoring of end milling , 2002 .

[14]  Roger Ivor Grosvenor,et al.  Machine tool condition monitoring using sweeping filter techniques , 2007 .

[15]  Zhang Deyuan,et al.  On-line detection of tool breakages using telemetering of cutting forces in milling , 1995 .

[16]  Sohyung Cho,et al.  Tool breakage detection using support vector machine learning in a milling process , 2005 .

[17]  K Szwajka Laboratory versus industrial cutting force sensor in tool condition monitoring system , 2005 .

[18]  S. F. Yu,et al.  A predicted modelling of tool life of high-speed milling for SKD61 tool steel , 2005 .

[19]  Min-Yang Yang,et al.  In-process prediction of cutting depths in end milling , 1999 .

[20]  Bernhard Sick,et al.  ON-LINE AND INDIRECT TOOL WEAR MONITORING IN TURNING WITH ARTIFICIAL NEURAL NETWORKS: A REVIEW OF MORE THAN A DECADE OF RESEARCH , 2002 .

[21]  Mathieu Ritou,et al.  A new versatile in-process monitoring system for milling , 2006, 1309.3915.

[22]  A. Geddam,et al.  A multi-sensor approach to the monitoring of end milling operations , 2003 .

[23]  Feng Ding,et al.  End milling tool breakage detection using lifting scheme and Mahalanobis distance , 2008 .

[24]  Gi Dae Kim,et al.  In-Process Tool Fracture monitoring in Face Milling Using Spindle Motor Current and Tool Fracture Index , 2001 .

[25]  Zhenhu Liang,et al.  Complexity measure of motor current signals for tool flute breakage detection in end milling , 2008 .

[26]  Yusuf Altintas,et al.  The identification of radial width and axial depth of cut in peripheral milling , 1987 .

[27]  A. M. Bassiuny,et al.  Flute breakage detection during end milling using Hilbert–Huang transform and smoothed nonlinear energy operator , 2007 .

[28]  Paul W. Prickett,et al.  Multi-band infinite impulse response filtering using microcontrollers for e-Monitoring applications , 2007, Microprocess. Microsystems.

[29]  Amin Al-Habaibeh,et al.  A new approach for systematic design of condition monitoring systems for milling processes , 2000 .