A Review on Tool Flank Wear Monitoring by Tool Condition Monitoring System using Various Approaches

Raghavendra M J, Srinivas Institute of Technology, Mangalore-574 143, Karnataka; Dr. Ramachandra C G ,Srinivas Institute of Technology, Mangalore-574 143, Karnataka; Dr. T.R. Srinivas ,S.J College of Engineering, Mysore-570 006,Karnataka; PrashanthPai ,P.A College of Engineering, Mangalore-574153,Karnataka

Tool Condition Monitoring; Signal and Acquisition Processing; Acoustic Emission; Vibration Signals, Turning

Increasing demands of process automation for un-manned manufacturing attracted many researchers in the field of on-line monitoring of machining processes. In view of this, extensive research work is taking place world-wide in the area of on-line tool condition monitoring system. Tool wear is the most undesirable characteristic of machining processes as it adversely affects the tool life, which is of foremost importance in metal cutting owing to its direct impact on the surface quality of the machined surface, and its dimensional accuracy, and consequently, the economics of machining operations.Tool wear has negative effects on surface quality, dimensional precision of work piece, and may even cause a harmful effect on safe operation of total machining system. According to the research, about 20% machine downtime is caused by the tool wear.In addition, the cost of cutting tool and tool changing is about 3–12% of the total machining cost and method for on-machine tool progressive monitoring of tool flank wear by processing the turned component. Therefore, methods for cutting tool wearin an over view of the maximum use of cutting tools. With an effective monitoring system, the wear and damages to the machine tool, downtime, lead time and scrapped components can be avoided. This paper provides brief overview on tool condition monitoring.
    [1] I.P.S. Ahuja, J.S. Khamba, (2008) "Total productive maintenance: literature review and directions", International Journal of Quality& Reliability Management, Vol.25 Iss: 7, pp.709 - 756. [2] Tamer H. Haddad and Dr. Ayham A.M. Jaaron,“The Applicability of Total Productive Maintenance for Healthcare Facilities: an Implementation Methodology”,Vol. 1, Issue 1 (Apr. - Jun. 2015). [3] C. Liu, G.F. Wang∗Z.M. Li “Incremental learning for online tool condition monitoring usingEllipsoid ARTMAP network model”35 (2015) 186–198. [4] Samik Dutta, Surjya K. Pal, Ranjan Sen. “Progressive tool flank wear monitoring by applying discretewavelet transform on turned surface images”77 (2016) 388–401. [5] Ricardo R. Mouran, Márcio B. da Silva, Álisson R. Machado, Wisley F. Sales “The effect of application of cuttingfluid with solid lubricant insuspension during cutting of Ti-6Al-4V allo”332-333 (2015) 762–771. [6] Mehdi Nouria, Barry K. Fussell,n, Beth L. Zinit, Ernst Linder “Real-time tool wear monitoring in milling using a cutting conditionindependent method”89 (2015) 1–13. [7] Aliustaoglu C, Ertunc HM, Ocak H. Tool wear condition monitoring using a sensor fusion model based on fuzzy inference system. Mechanical Systems and Signal Processing 2009; 23:539–546. [8] DimlaSr DE, Lister PM. On-line metal cutting tool condition monitoring. I: force and vibration analyses, International Journal of Machine Tools & Manufacture 2000; 40:739–768. [9] Li X. A brief review: acoustic emission method for tool wear monitoring during turning. International Journal of Machine Tools and Manufacture 2002; 42 (2):157–165. [10] H. Chelladurai. K. Jain&N. S. Vyas “Development of a cutting tool condition monitoring systemfor high speed turning operation by vibrationand strain analysis” (2008) 37:471–485. [11] Adam G. Rehorn • Jin Jiang • Peter E. Orban “State-of-the-art methods and results in tool condition monitoring” (2005) 26: 693–710. [12] Ahmet Cakan “Real-time monitoring of flank wear behavior of ceramicutting tool in turning hardened steels” (2011) 52:897–903. [13] FranciČuš - UrošŽuperl* “Real-Time Cutting Tool Condition Monitoring in Milling”57(2011)2, 142-150. [14] X. Q. Chen&H. Z. Li “Development of a tool wear observer model for online toolcondition monitoring and control in machiningnickel-based alloys”(2009) 45:786–800. [15] Satyanarayana Kosaraju& Venu Gopal Anne&Bangaru Babu Popuri “Online tool condition monitoring in turning titanium (grade 5) using acoustic emission: modeling” (2013) 67:1947–1954. [16] A. Siddhpura&R. Paurobally “A review of flank wear prediction methods for tool conditionmonitoring in a turning process” 2013) 65:371–393. [17] Xiaozhi Chen.Beizhi Li “Acoustic emission method for tool condition monitoringbased on wavelet analysis”33: (2007) 968–976. [18] Alan Hase&MasakiWada&ToshihikoKoga&Hiroshi Mishina “The relationship between acoustic emission signals and cuttingphenomena in turning process” (2014) 70:947–955. [19] Feng Ding&Zhengjia He “Cutting tool wear monitoring for reliability analysisusing proportional hazards model” (2011) 57:565–574. [20] NitinAmbhorea*, Dinesh Kambleb, SatishChinchanikar, Vishal Wayal “Tool condition monitoring system: A review”2 (2015) 3419 – 3428. [21] P Kulandaivelu, Senthil Kumar and S Sundaram, “Wear monitoring of single point cutting tool using acousticemission techniques”Vol. 38, Part 2, April 2013, pp. 211–234.
Paper ID: GRDJEV01I040011
Published in: Volume : 1, Issue : 4
Publication Date: 2016-04-01
Page(s): 7 - 13