Estimation of minimum chip thickness for multi-phase steel using acoustic emission signals
14 Jul 2010-pp 197-200
TL;DR: In this article, the authors proposed a methodology to determine the value of minimum chip thickness by analysing acoustic emission (AE) signals generated in orthogonal machining experiments conducted in micro milling.
Abstract: The determination of minimum chip thickness is important for establishing the lower limit of the feasible process window in micro mechanical machining for a given tool and workpiece material. The minimum chip thickness is encountered in micro milling operations owing to the variation in chip load as predicted by the chip density function. This study proposes a methodology to determine the value of minimum chip thickness by analysing acoustic emission (AE) signals generated in orthogonal machining experiments conducted in micro milling. Cutting trials were performed on a near balanced ferrite/pearlite microstructure (AISI 1045 steel) with a range of undeformed chip thicknesses spanning across the tool edge radius. The characteristics of AE r.m.s signals were studied for conditions when the tool was rubbing the workpiece. This base signal signature was used to study and contrast AE signals to other machining parameters. This study enabled the identification of threshold conditions for occurrence of minimum chip thickness. The value of minimum chip thickness predicted by this new approach compares reasonably well with that existing in published literature.
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24 Oct 2011
TL;DR: In this article, the authors proposed a methodology to determine the value of minimum chip thickness by analysing acoustic emission (AE) signals generated in orthogonal machining experiments conducted in micro-milling.
Abstract: In micro-machining, determination of the minimum chip thickness is of paramount importance, as features having dimensions below this threshold cannot be produced by the process. This study proposes a methodology to determine the value of minimum chip thickness by analysing acoustic emission (AE) signals generated in orthogonal machining experiments conducted in micro-milling. Cutting trials were performed on workpiece materials ranging from non-ferrous (copper and aluminium), ferrous (single- and multiphase steel) to difficult-to-cut (titanium and nickel) alloys. The characteristics of AErms signals and chip morphology were studied for conditions when the tool was rubbing the workpiece. This provided a foundation to contrast AE signals captured at higher feed rates. This study enabled the identification of threshold conditions for the occurrence of minimum chip thickness. The values of minimum chip thickness predicted by this new approach compare reasonably well with the published literature.
34 citations
Dissertation•
09 Mar 2011
TL;DR: In this paper, the authors investigated the effect of micro-machinability of coarse grain steel materials on micro-cutting performance and found that the cutting velocity is a dominant factor on size effect related process performance.
Abstract: The world is experiencing a growing demand for miniaturised products. Micro-milling, using carbide micro tools has the potential for direct, economical manufacture of micro parts from a wide range of workpiece materials. However, in previous studies several critical issues have been identified that preclude the direct application of macro machining knowledge in the micro domain through simple dimensional analysis. The research presented in this thesis focused on some of the areas that require development of the scientific knowledge base to enable determining improved microscale cutting performance. In the mechanical micro machining of coarse grained materials, the programmed undeformed chip thickness can be lower than the length scale of the workpiece grains. Moreover, when the microstructure of such materials is composed of more than one phase, the micro cutting process can be undertaken at a length scale where this heterogeneity has to be considered. Driven by this challenge, the material microstructure ?size effect? on micro-machinability of coarse grain steel materials was investigated in this PhD. In this regard, a predominantly single phase ferritic workpiece steel material and another workpiece material with near balanced ferrite/pearlite volume fractions was studied over a range of feedrates. The results suggested that for micro machined parts, differential elastic recovery between phases leads to higher surface roughness when the surface quality of micro machined multiphase phase material is compared to that of single phase material. On the other hand, for single phase predominantly ferritic materials, reducing burr size and tool wear are major challenges. In micro machining the so called ?size effect? has been identified as critical in defining the process performance. However, an extensive literature search had indicated that there was no clear reported evidence on the effect of process variables on driving this size effect phenomenon. It is often assumed in literature that the un-deformed chip thickness was the main factor driving the size effect. This limit manufactures to only altering the feedrate to try and influence size effect. To explore the significance of a range of inputs variables and specifically, cutting variables on the size effect, micro cutting tests were conducted on Inconel 718 nickel alloy. Taguchi methodology along with signal processing techniques were applied to micro milling acoustic emission signals to identify frequency/energy bands and hence size effect specific process mechanism. The dominant cutting parameters for size effect characteristics were determined by analysis of variance. These findings show that despite most literature focussing on chip thickness as the dominant parameter on size effect, the cutting velocity is a dominant factor on size effect related process performance. This suggests that manipulating the cutting speed can also be a very effective strategy in optimising surface finish in micro machining and in breaking the lower limit of micro machining.In micro machining the lower limit of the process window is set by the minimum chip thickness. Identifying this limit is thus important for establishing the process window. Process windows are valuable guidelines for industrial selection of cutting conditions. Additionally, understanding factors that influence the value of minimum chip thickness is even more important for progressing micro machining capability to the nano-scale machining regime. For this reason, in this PhD study, acoustic emission signatures emanating from microscale milling of six different workpiece materials were characterised to identify the rubbing mode and this enabled the identification of the threshold conditions for occurrence of minimum chip thickness. The minimum chip thickness predicted by this novel approach compares reasonably well to the values that exist in published literature. Additionally, the decomposition of raw acoustic signal allowed the determination of energy levels corresponding to deformation mechanisms. The PhD work provides significant and new knowledge on the utility and importance of acoustic emission signals in characterising chip formation in micro machining. A novel method for determining the minimum chip thickness was developed, micro machining chip formation mechanisms were identified and the machinability of coarse grained multiphase material is presented.
20 citations
Cites background or methods from "Estimation of minimum chip thicknes..."
...In prior investigation [173], it was reported that AE signal produced in ploughing dominated zone was influenced by the thermal activation associated with the toolworkpiece interaction in the tertiary deformation zones....
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...In a prior study [173], the authors demonstrated the effectiveness of this method to determine the hmin of multiphase steel....
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Dissertation•
01 Jul 2012
TL;DR: In this paper, the impact of micro-slot milling of high carbon, high chromium hardened AISI D2 cold work tool steel using 05mm diameter coated (TiAlN) tungsten carbide end mills were carried out Performance was assessed in terms of tool life/tool wear, surface roughness, cutting forces, burr formation, slot geometry accuracy and workpiece surface integrity.
Abstract: Investigations into micro-slot milling of high carbon, high chromium hardened AISI D2 cold work tool steel using 05mm diameter coated (TiAlN) tungsten carbide end mills were carried out Performance was assessed in terms of tool life/tool wear, surface roughness, cutting forces, burr formation, slot geometry accuracy and workpiece surface integrity The influence of operating parameters (cutting speed, feed rate and depth of cut) on tool life, surface roughness, burr width and cutting forces was evaluated using full factorial experiment design Analysis of results included main effects plot and calculation of percentage contribution ratios (PCR) for each of the primary variable factors and their interactions were assessed via analysis of variance (ANOVA) The test array was further extended to allow for implementation of Response Surface Methodology (RSM) analysis in order to optimise tool life and surface roughness Dual-response (cutting speed and feed rate) contours of metal removal rate and tool life/surface roughness were generated from the respective model equations These were further developed to identify combinations of cutting speed and feed per tooth for the best tool life/surface roughness at specific metal removal rates Finally, the impact of coatings and tool geometry on tool life and workpiece surface roughness was investigated
16 citations
Cites methods from "Estimation of minimum chip thicknes..."
...[105] employed an acoustic emission technique in order to estimate the minimum chip thickness when micro machining a multi phase steel....
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TL;DR: In this article, the influence of two different types of inclusions on tool wear, cutting forces, chip formation, burr formation, and surface finishing of the machined specimens are explored.
Abstract: For the manufacturing of micro molds, usually, the same sort of materials is used as for conventional machining. However, phenomena that occur when the depth of cut approaches the cutting edge radius have to be considered. This paper presents experimental investigations on tool life tests of micromilling processes. TiAlN-coated cemented carbide tools are applied on three different mold steels for plastic injection molding. The influences of two different types of inclusions are explored on tool wear, cutting forces, chip formation, burr formation, and surface finishing of the machined specimens.
2 citations
Cites background from "Estimation of minimum chip thicknes..."
...5 % of the tool edge radius [9]....
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TL;DR: In this article, a kind of micro milling model which can describe the deformation of high temperature, high strain and high strain rate of material behavior and reflect the size effect is established.
Abstract: Micro milling is a hot research field of advanced manufacturing technology at present. In this paper, a kind of micro milling model which can describe the deformation of high temperature, high strain, high strain rate of material behavior and reflect the size effect is established based on the characteristics of micro milling. And the finite element method is used to simulate the micro milling process. The change of flow stress and temperature and the formation of chip are analyzed for micro milling the workpiece material AISI 1045. At last, the micro milling force is predicted.
References
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TL;DR: In this article, the relationship between the cutting edge radius and the minimum cutting thickness was analyzed, and the effect of cutting edge sharpness on the machined surface integrity was investigated.
Abstract: The diamond tool sharpness is a primary factor affecting the cutting deformation and the machined surface quality in diamond cutting process. In this paper, the relationship between the cutting edge radius and the minimum cutting thickness was analyzed. Cutting tests of aluminium alloys with two diamond tools of different sharpness were performed in order to investigate the effect of cutting edge sharpness on the machined surface integrity. Experimental results show that the surface roughness, microhardness, residual stress and the dislocation density of the machined surface layer vary with the cutting edge radius.
331 citations
TL;DR: In this paper, the prerequisites for the micro-cutting of steel using tungsten carbide tools and the interaction between the properties of the materials and the process parameters on the manufacturing result are identified.
Abstract: Due to its hardness, single crystal diamond is the preferred tool material for micro-cutting. As diamond has a very high affinity to iron, micro-cutting is mostly limited to the machining of non-ferrous materials like brass, aluminum, copper or electroless nickel. The particular material properties of steel make it a very important material for extending the field of micro-technology applications. This paper discusses the prerequisites for the micro-cutting of steel using tungsten carbide tools and the interaction between the properties of the materials and the process parameters on the manufacturing result. Further fields of research are identified. The possibilities of this approach are exemplified on microstructured molds.
325 citations
"Estimation of minimum chip thicknes..." refers background in this paper
...Weule et al emphasized strong contribution of material properties on the minimum chip thickness [14]....
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...The value of minimum chip thickness also proves useful in identifying optimal cutting conditions since it influences cutting forces [15], tool wear, surface roughness [7, 14], burr formation [16, 17], process stability....
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TL;DR: In this paper, the authors examined the surface generation process in the micro-endmilling of both single-phase and multiphase workpiece materials and developed a surface generation model to predict the surface roughness for the slot floor centerline.
Abstract: This paper examines the surface generation process in the micro-endmilling of both single-phase and multiphase workpiece materials. We used 508 μm dia endmills with edge radii of 2 and 5 μm to machine slots in ferrite, pearlite, and two ductile iron materials at feed rates ranging from 0.25 to 3.0 mm/flute. A surface generation model to predict the surface roughness for the slot floor centerline is then developed based on the minimum chip thickness concept. The minimum chip thickness values were found through finite element simulations for the ferrite and pearlite materials. The model is shown to accurately predict the surface roughness for single-phase materials, viz., ferrite and pearlite. Two phenomena were found to combine to generate an optimal feed rate for the surface generation of single-phase materials: (i) the geometric effect of the tool and process geometry and (ii) the minimum chip thickness effect. The surface roughness measurements for the ductile iron workpieces indicate that the micromilling surface generation process for multiphase workpiece materials is also affected by the interrupted chip-formation process as the cutting edge moves between phases resulting in burrs at the phase boundaries and the associated increases in surface roughness.
310 citations
"Estimation of minimum chip thicknes..." refers background or methods in this paper
...The minimum chip thickness has been estimated previously using experimental [2], analytical modelling [3-5] and simulation techniques [6, 7] and suggested to lie between 5% and 40% of the tool edge radius....
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...The value of minimum chip thickness also proves useful in identifying optimal cutting conditions since it influences cutting forces [15], tool wear, surface roughness [7, 14], burr formation [16, 17], process stability....
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01 Oct 2009-Precision Engineering-journal of The International Societies for Precision Engineering and Nanotechnology
TL;DR: In this paper, the size effect in micromilling hardened tool steel was observed by studying the effect of the ratio of undeformed chip thickness to the cutting edge radius on process performance, and how this ratio drove the specific cutting force, surface finish and burr formation in micro-scale machining.
Abstract: The market for freeform and high quality microdies and moulds made of steel is predicted to experience a phenomenal growth in line with the demand for microsystems. However, micromachining of hardened steel is a challenge due to unpredictable tool life and likely differences in process mechanism compared to macro-scale machining. This paper presents an investigation of the size effect in micromilling of H13 hardened tool steel. In this case, the size effect in micromilling hardened tool steel was observed by studying the effect of the ratio of undeformed chip thickness to the cutting edge radius on process performance. The paper explores how this ratio drives the specific cutting force, surface finish and burr formation in micro-scale machining. In addition, the effect of different microend mill geometry on product quality was explored. The paper provides a valuable insight into optimum micro-scale machining conditions for obtaining the best surface finish and minimizing burr size.
306 citations
"Estimation of minimum chip thicknes..." refers background in this paper
...In micro-scale cutting, when undeformed chip thickness is less than the minimum chip thickness, only elastic recovery of workpiece material will take place (no material is removed in a form of chip) [1]....
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TL;DR: In this paper, an analytical model has been developed to predict the minimum chip thickness values, which are critical for the process model development and process planning and optimization, and the model accounts for the effects of thermal softening and strain hardening on the minimum chips thickness.
Abstract: In micromachining, the uncut chip thickness is comparable or even less than the tool edge radius and as a result a chip will not be generated if the uncut chip thickness is less than a critical value, viz., the minimum chip thickness. The minimum chip thickness effect significantly affects machining process performance in terms of cutting forces, tool wear, surface integrity, process stability, etc. In this paper, an analytical model has been developed to predict the minimum chip thickness values, which are critical for the process model development and process planning and optimization. The model accounts for the effects of thermal softening and strain hardening on the minimum chip thickness. The influence of cutting velocity and tool edge radius on the minimum chip thickness has been taken into account. The model has been experimentally validated with 1040 steel and A16082-T6 over a range of cutting velocities and tool edge radii. The developed model has then been applied to investigate the effects of cutting velocity and edge radius on the normalized minimum chip thickness for various carbon steels with different carbon contents and A16082-T6.
250 citations
"Estimation of minimum chip thicknes..." refers background or methods or result in this paper
...Liu et al highlighted the influence of cutting velocity, thermal softening and strain hardening as well as tool edge radius on the minimum chip thickness of a material [3]....
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...The minimum chip thickness has been estimated previously using experimental [2], analytical modelling [3-5] and simulation techniques [6, 7] and suggested to lie between 5% and 40% of the tool edge radius....
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...These results are in agreement with the value of minimum chip thickness available in the literature for steel workpiece material [3, 4]....
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