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Figure 2.3 Noise recognition in machiningAs the cutting process is in a continual state of change due to tool wear, it cannotbe considered time-invariable. Typical wear criteria are average wear land widthand maximum wear land width. Using these criteria it is possible to evaluate theaverage and maximum intensity of wear and implement these data in mathematicalequations or models predicting tool life. When it comes to the analysis of tool wear,it is recognised that the flank wear is of prime concern, so that all tool life testingtechniques have primarily considered this type of wear (Astakhov, 1999). It occurson the flank of the tool below the cutting edge and cannot be avoided. The size ofthe flank wear can be measured as the distance between the top of the cutting edgeand the bottom of the flank wear land. Modern cutting inserts have often chamferedcutting edges, enabling to extend the tool life (Fig. 2.4a). Therefore flank wear canbe recognised both on the cutting edge and on the flank face.At small cutting speeds flank wear is dominating. In Fig. 2.4b the flank wear isindicated by h αw , the width of chamfer by b γ , and the flank angle by a 0 . At the sametime chamfer width b γ decreases, and the corresponding decrease is indicated by b γwα .At average cutting speeds, over built-up edge formation limits, a notch is formedat the rake face. The depth of notch is small and the rake angles γ o1 and γ o2 remainthe same. The first phase is shortening both from rake and flank faces. The chamferwidth decreases during machining at the flank and rake faces. Usually cementedcarbide tools should be replaced when the average width of the flank wear landreaches 0.3 mm (by ISO 3685-1977) when wear land is uniform, or 0.6 mm whencutting edge is chipped.γo1bγγο2bγwαhαwαoFigure 2.4 An unworn cutter with chamfer honing (a), and a worn cutter at small cuttingspeeds (b)18
However, it should be noticed that at high speeds the significance of rake wearrises, causing crater formation on the face of tool (see Paper I). By normalmachining the crater will gradually enlarge, causing the rake angle to increase, untilit breaks through a part of the cutting edge, as wedge angle has been decreased.Intensities of flank and rake wear can be used for tool life estimation. Suchmeasurement can be realised with a video system, as a conventional microscope isunable to take into account eroded edge parts. Thus a more precise tool lifeprediction is also made feasible.Realization of monitoring can be achieved by building up a set of local networks.It involves integration of elaborated technical solutions, monitoring of technologicalparameters in the network, and generalization of gathered data for complementingthe Reliability and Operations Monitoring System (R/OMS) (see Fig. 2.5).Figure 2.5 Planned data flows in the Intelligent Machining Unit2.2. Experimental setup for process analysis by electronic image processingElectronic image processing systems are used in different branches of industry.They deliver objective test results that can be reproduced at any time. Camcordersare being replaced by digital video cameras (DVCs). Thanks to progress insemiconductor technology, DVC performance has improved dramatically. Movingimages can be input to computers with DVCs. Analog video camera will soon bereplaced with DVCs because of various advantages of the digital equipment.Industrial CCD cameras used for cutting process investigations have severaldrawbacks. First, they need permanent electric supply through an AC adapter.Further, there has to be permanent connection to a video recorder or a computer.When the distance between the camera and the computer is bigger than 100 meters,the signal is to be amplified (Zebala, 1999).19
Page 1 and 2: THESIS ON MECHANICAL AND INSTRUMENT
Page 3 and 4: MASINA- JA APARAADIEHITUS E283
Page 5 and 6: PREFACEThe mankind of the 21 st cen
Page 7 and 8: Paper I............................
Page 9 and 10: XII. Riives, J., Papstel, J., Otto,
Page 11 and 12: 1. INTRODUCTION1.1. BackgroundManuf
Page 13 and 14: database by a query; c. Search of t
Page 15 and 16: Porter’s Diamond Model task an on
Page 17: Figure 2.1 Use of modelling in prod
Page 21 and 22: Figure 2.6 Depth of field/magnifica
Page 23 and 24: 2.3. Prediction of machining accura
Page 25 and 26: uFy=ybsinptyOl 1ulFAϕFigure 2.10 C
Page 27 and 28: is2.5. Dynamical model with two deg
Page 29 and 30: According to de Moivre’s formulaw
Page 31 and 32: constant of the lathe. Figure 2.11
Page 33 and 34: Analogically, test results and resu
Page 35 and 36: Figure 3.1 Model checking in an ope
Page 37 and 38: Figure 3.3 A snapshot of Uppaal mod
Page 39 and 40: Figure 3.5 FMS at TUTM9M8M4M1M2M7M5
Page 41 and 42: Turning and milling operations can
Page 43 and 44: 4. MODELS FOR MONITORING THE RESOUR
Page 45 and 46: As assumptions to solve the queries
Page 47 and 48: Regarding co-operation networks the
Page 49 and 50: • The system offers dynamic and u
Page 51 and 52: Figure 4.5 Associations in the Inno
Page 53 and 54: An enterprise-centred mapping and a
Page 55 and 56: Better efficiency and transparency
Page 57 and 58: institutions: in enterprises of div
Page 59 and 60: 1. Tehnoloogiaseadme tasemel on loo
Page 61 and 62: REFERENCESAltintas, Y. (2000). Manu
Page 63 and 64: Russo, M.F. (1999). Automating Scie
Page 65 and 66: Paper IIAryassov, G., Otto, T., Gro
Page 67 and 68: Paper IVOtto, T., Papstel, J., Riiv
Page 69 and 70:
ELULOOKIRJELDUS (CV)1. IsikuandmedE
Page 71 and 72:
CURRICULUM VITAE (CV)1. Personal da
Page 73 and 74:
DISSERTATIONS DEFENDED ATTALLINN UN
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