A comprehensive tool-wear/tool-life performance model in the ...

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ARTICLE IN PRESS P.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886 879 controlled manner in a flow of compressed air that is completely vaporized by the heat generated in the cutting process. MWF can be reduced up to 10,000 times compared to traditional flood cooling providing a significant environmental and occupationally impact. Unfortunately, the application of NDM is very difficult due to several factors. First, NDM can be applied in a variety of applications and offers a broad operating range. Users of NDM have the option to select a wide range of pressures, volumetric flow rates, nozzle configurations and MWF types. Depending on the parameter selection, various results (positive and negative) have been reported which is summarized in Table 1. In all cases, the range of operation in NDM has a tremendous effect on the application and offers a much smaller process window than traditional flood cooling. Second, models to predict machining performance through parameter selection do not exist for NDM. The wide spread use and application of NDM has been slowed mainly due to three unanswered delivery parameter questions: 1. How much MWF should be applied? 2. Where and how do I apply the MWF? 3. What type of MWF should I apply? Thus, there is a need to develop a scientific approach in selecting the optimal delivery parameters and cutting conditions for machining performance that considers both the cutting mechanics and the mist spray delivery. It is the goal of this work to develop, validate and apply a performance-based model in NDM that answers those delivery questions. The use of a model will also serve to Table 1 Literature review in NDM detailing varying results associated with operating range Area Description of previous work Process range Comment Health and safety Brinksmeier and Brockhoff [10] observed in oscillating grinding that NDM should only be used with an air suction due to aerosol concentration levels. The work of Gressel [15] reinforced earlier findings quantitatively by completing experiments while turning and drilling steel. His work demonstrated that concentrations exceeded NOISH REL (recommended exposure limits) limits. Marksberry [13] indicated that air pressure, MWF volumetric flow rates and MWF type have a profound effect on concentrations. MWF volumetric flow rates should stay below 200 ml/h with pressures below 0.034 MPa (5 psi) to prevent total mass particulate from reaching the 5 mg/m 3 REL when using oil-based MWFs. Water soluble MWFs can employ a larger process window at double to triple the MWF rates and pressures. Pressure: 0.6 MPa (87 psi), MWF rate: 30 ml/h Pressure: not cited, MWF rate: 660 ml/h Pressure: 0.034 MPa (5 psi), MWF rate: 200 ml/h Need air suction due to aerosol concentration levels when using NDM. NDM exceeded NOISH REL limits. NDM is safe if pressures are low and MWF rates are low. Process Heisel et al. [11] stated that nozzle location in NDM has less importance on tool-life/tool-wear when machining steel. Wakabayashi et al. [12] concluded that NDM provided almost equivalent advantages compared to flood cooling when machining steel using dual nozzles at the rank face and flank face. Marksberry [14] indicated that nozzle position has a direct effect on the process and greatly depends on the chip flow path and the nozzle to cutting tool to workpiece relationship. Nozzle position: flank, rank, chip Nozzle position: flank, rank Nozzle position: flank, rank, chip Nozzle position is not a sensitive control variable. Multiple nozzle positions aimed at the rank and flank face provide benefit. Obstructions from the workpiece, chip flow path and cutting geometry greatly affect NDM effectiveness. Machining performance Scandiffio [16] observed that NDM did not offer any improvement over conventional flood cooling when turning steel at high cutting speeds. Rahman et al. [17] demonstrated that NDM could provide comparable results to flood when milling at low feed rates, low speeds and depths of cut. Chen et al. [18] observed that tool-wear could be reduced over dry machining in turning stainless. Marksberry [14] completed work that shows that tool-wear/ tool-life can be greatly improved by the use of NDM up to four times compared to dry machining when machining steel when directed at the dominate tool-wear pattern. Process: turning steel Process: milling steel Process: turning stainless Process: turning steel Tool-wear did not improved compared to flood cooling using NDM. Tool-wear did not improved compared to flood cooling using NDM. Tool-wear improved over dry machining using NDM. Tool-wear improvement greatly depends on the cutting geometry and machining application.
880 ARTICLE IN PRESS P.W. Marksberry, I.S. Jawahir / International Journal of Machine Tools & Manufacture 48 (2008) 878–886 reduce machining cost associated in NDM and lesson the environmental impact of manufacturing operations. 2. Machining modeling background Several attempts have been made to develop methods [19–23] for accurately predicting the effects of machining operations over the past several decades. A common approach for assessing machining performance is toolwear/tool-life. Tool-wear/tool-life is one of the most significant and necessary parameters required for process planning and total machining economics. A review of numerous theoretical and experimental techniques for predictive assessment of tool-wear and tool-life reveals that eight different types of tool-wear/tool-life relationships are commonly being used for dry machining, as shown in Table 2. The trend in tool-wear/tool-wife modeling has been to extend Taylor’s basic equation. This is mainly due to the direct relationship between cutting speed and tool-wear/ tool-life. This relationship holds true for all machining operations and is considered as a basis for more advanced models. Currently, a model does not exist for NDM and no attempts have been made to extend dry machining toolwear/tool-life models. It is the author’s goal in this work to select the most appropriate dry machining model and extend it for NDM. The appropriate selection of a dry machining model for extension to NDM depends on various factors. First, it is important that the model be robust to accommodate a wide range of machining parameters and applications. The model should be easily modified and practical for industry applications where complete machining data is not available. Lastly, the model should be accurate, repeatable and suited for industrial use where experimental constants can be generated without using sophisticated equipment; such as tool dynameters to calculate forces, high-speed film to understand complicated chip flow paths and electron microscopes to determine residual stress patterns and material structure. Table 2 Summary of tool-wear and tool-life models for dry machining No. Tool-life/tool-wear equation Determination of constants 1 Taylor’s basic equation: VT n ¼ C C and n are experimentally determined and currently available from many reference sources 2 Taylor’s reference-speed based equation: V=V R ¼ðT R =TÞ n n is experimentally determined and currently available from many reference sources 3 Taylor’s extended equation: T ¼ C 2 =ðV P f q d r Þ All constants (C 2 , p, q and r) are experimentally determined 4 Temperature-based tool-life equation: yT n ¼ C 3 n is found between 0.01 and 0.1 and C 3 is experimentally determined 5 Taylor’s extended equation including cutting conditions and tool geometry: C /½ðcot b tan aÞ n Fða; bÞ 1= 1 Š 6 Taylor’s extended equation including cutting conditions and workpiece hardness: T ¼ C 4 V n f m d P r q s t i u j x 7 Taylor’s extended equation including cutting conditions and workpiece hardness: V ¼ C 5 =ðT m f y d x ðBHN=200Þ n Þ 8 Taylor’s extended equation including chip groove effect factor and a tool coating effect factor: The influence of a and b can be theoretically determined as partial contribution to Taylor’s constant C Requires excessive toollife testing to determine all constants (C 4 , n, m, p, q, t, u and x) All constants (C 5 , m, y, x and n) are experimentally determined Comment Most widely used equation; however, C and n apply to a particular tool–workpiece combinations n applies only to particular tool–workpiece combinations Gives better accuracy than Taylor’s basic equation, but more toollife tests are required Although the equation is set only on an empirical basis, it is not convenient for practical use in the shop floor environment A complicated relationship between toollife and rake/clearance angles It is claimed that the data for setting up the equation are generated from both laboratory and industrial sources It is claimed to be a good approximation for toollife ranges of 10–60 min Ref. Mills and Redford [24], Schey [25] Mills and Redford [24] Niebel et al. [26], Hoffman [27] Quinto [28], Oxley [29] Lau et al. [22] Venkatesh [21] Wang and Wysk [30], Hoffman [27] T ¼ T R W g ðV R =VÞ W cð1=nÞ ; where W c ¼ n=n c and W g ¼ km=f n 1 d n 2 Constants (k, n 1 , n 2 and n c ) are experimentally determined; m is the machining operation effect factor (with m ¼ 1 considered for turning)Extends the Taylor-type equation to include two new factors: tool coating effect factor and chip-groove effect factor. Equation also includes the effects of feed, depth of cut and cutting speed.Jawahir et al. [31], Li et al. [32]
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