Micromilling Process Planning and Modeling for Micromold Manufacturing

2007 ◽  
Author(s):  
Atul Dhanorker ◽  
Xinyu Liu ◽  
Tug˘rul O¨zel
Keyword(s):  
Surface Roughness ◽  
Process Planning ◽  
Cutting Forces ◽  
End Milling ◽  
Chip Thickness ◽  
Thickness Effect ◽  
Depth Of Cut ◽  
Formation Mechanisms ◽  
Planning Strategy ◽  
Surface Accuracy

In this paper, a model-based micro-end milling process planning guideline for machining micro mold cavities was proposed. The goal is to facilitate proper selections of the process parameters. Specifically, the axial depth of cut, the feed per tooth are critical in achieving performance objectives in terms of cutting forces, surface accuracy, tool life, etc. To this end, the finite element modeling was used to provide a comprehensive understanding of the underlying science base for the micro-machining (e.g., chip formation mechanisms, minimum chip thickness effect, material deformation flows, stress, strain and temperature distributions). Further, a mechanistic time-domain simulation model was utilized to provide predictive capability in practical machining performance, such as cutting forces, tool vibrations, surface accuracy, and surface roughness. The generalized process planning strategy consists of two steps: roughing and finishing. In roughing, the objective is to control the cutting force within a predefined threshold to prevent premature tool breakage and to maximize the material removal rate. In finishing, the primary objective is to control the form error within the tolerance and to obtain satisfactory surface roughness. The proposed process planning strategy was applied for micro-milling of a mold cavity in AL2024-T6.

Cutting Forces and Surface Roughness in High-Speed End Milling of Ti6Al4V

2013 ◽  
Vol 589-590 ◽  
pp. 76-81
Author(s):  
Fu Zeng Wang ◽  
Jun Zhao ◽  
An Hai Li ◽  
Jia Bang Zhao
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Cutting Forces ◽  
High Speed ◽  
End Milling ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Wide Range ◽  
Radial Depth ◽  
Coated Carbide

In this paper, high speed milling experiments on Ti6Al4V were conducted with coated carbide inserts under a wide range of cutting conditions. The effects of cutting speed, feed rate and radial depth of cut on the cutting forces, chip morphologies as well as surface roughness were investigated. The results indicated that the cutting speed 200m/min could be considered as a critical value at which both relatively low cutting forces and good surface quality can be obtained at the same time. When the cutting speed exceeds 200m/min, the cutting forces increase rapidly and the surface quality degrades. There exist obvious correlations between cutting forces and surface roughness.

Convolution Analysis of Milling Force Pulsation

1994 ◽  
Vol 116 (1) ◽  
pp. 17-25 ◽  
Author(s):  
J.-J. Junz Wang ◽  
S. Y. Liang ◽  
W. J. Book
Keyword(s):  
Cutting Force ◽  
Density Function ◽  
Cutting Forces ◽  
End Milling ◽  
Chip Thickness ◽  
Closed Form Expression ◽  
Thickness Variation ◽  
Depth Of Cut ◽  
Force Model ◽  
Frequency Multiplication

This paper presents the establishment of a closed form expression for the dynamic forces as explicit functions of cutting parameters and tool/workpiece geometry in milling processes. Based on the existing local cutting force model, the generation of total cutting forces is formulated as the angular domain convolution of three cutting process component functions, namely the elementary cutting function, the chip width density function, and the tooth sequence function. The elemental cutting force function is related to the chip formation process in an elemental cutting area and it is characterized by the chip thickness variation, and radial cutting configuration. The chip width density function defines the chip width per unit cutter rotation along a cutter flute within the range of axial depth of cut. The tooth sequence function represents the spacing between flutes as well as their cutting sequence as the cutter rotates. The analysis of cutting forces is extended into the Fourier domain by taking the frequency multiplication of the transforms of the three component functions. Fourier series coefficients of the cutting forces are shown to be explicit algebraic functions of various tool parameters and cutting conditions. Numerical simulation results are presented in the frequency domain to illustrate the effects of various process parameters. A series of end milling experiments are performed and their results discussed to validate the analytical model.

scholarly journals Optimum combination of process parameters to optimize Surface Roughness and Chip Thickness during End Milling of Aluminium 6351-T6 Alloy Using Taguchi Grey Relational Analysis

2017 ◽  
Vol 8 (2) ◽  
pp. 287
Author(s):  
Reddy Sreenivasulu
Keyword(s):  
Surface Roughness ◽  
Grey Relational Analysis ◽  
Feed Rate ◽  
End Milling ◽  
Chip Thickness ◽  
Optimum Combination ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Relational Analysis ◽  
Grey Relational

In any machining operations, quality is the important conflicting objective. In order to give assurance for high productivity, some extent of quality has to be compromised. Similarly productivity will be decreased while the efforts are channelized to enhance quality. In this study,  the experiments were carried out on a CNC vertical machining center (KENT and INDIA Co. Ltd, Taiwan make) to perform 10mm slots on Al 6351-T6 alloy work piece by K10 carbide, four flute end milling cutter as per taguchi design of experiments plan by L9 orthogonal array was choosen to determine experimental trials. Furthermore the spindle speed (rpm), the feed rate (mm/min) and depth of cut (mm) are regulated in these experiments. Surface roughness and chip thickness was measured by a surface analyser of Surf Test-211 series (Mitutoyo) and Digital Micrometer (Mitutoyo) with least count 0.001 mm respectively. Grey relational analysis was employed to minimize surface roughness and chip thickness by setting of optimum combination of machining parameters. Minimum surface roughness and chip thickness obtained with 1000 rpm of spindle speed, 50 mm/min feed rate and 0.7 mm depth of cut respectively. Confirmation experiments showed that Gray relational analysis precisely optimized the drilling parameters in drilling of Al 6351-T6 alloy. 

Investigation of the Dynamics of Microend Milling—Part II: Model Validation and Interpretation

2006 ◽  
Vol 128 (4) ◽  
pp. 901-912 ◽  
Author(s):  
Martin B. G. Jun ◽  
Richard E. DeVor ◽  
Shiv G. Kapoor
Keyword(s):  
Dynamic Model ◽  
End Milling ◽  
Elastic Recovery ◽  
Chip Thickness ◽  
Thickness Effect ◽  
Depth Of Cut ◽  
Minimum Chip Thickness ◽  
Microend Milling ◽  
The Stability ◽  
Cutting Mechanisms

In Part II of this paper, experimental and analytical methods have been developed to estimate the values of the process faults defined in Part I of this paper. The additional faults introduced by the microend mill design are shown to have a significant influence on the total net runout of the microend mill. The dynamic model has been validated through microend milling experiments. Using the dynamic model, the effects of minimum chip thickness and elastic recovery on microend milling stability have been studied over a range of feed rates for which the cutting mechanisms vary from ploughing-dominated to shearing-dominated. The minimum chip thickness effect is found to cause feed rate dependent instability at low feed rates, and the range of unstable feed rates depends on the axial depth of cut. The effects of process faults on microend mill vibrations have also been studied and the influence of the unbalance from the faults is found to be significant as spindle speed is increased. The stability characteristics due to the regenerative effect have been studied. The results show that the stability lobes from the second mode of the microend mill, which are generally neglected in macroscale end milling, affect the microend mill stability significantly.

Experimental Investigations of Cutting Parameters Influence on Cutting Forces and Surface Roughness of Quartz Glass

2013 ◽  
Vol 641-642 ◽  
pp. 367-370
Author(s):  
Gui Qiang Liang ◽  
Fei Fei Zhao
Keyword(s):  
Surface Roughness ◽  
Cutting Force ◽  
Cutting Forces ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Diamond Wheel ◽  
Experimental Investigations ◽  
Depth Of Cut ◽  
Feed Force

Abstract In the present study, an attempt has been made to investigate the effect of cutting parameters (cutting speed, feed rate and depth of cut) on cutting forces (feed force, thrust force and cutting force) and surface roughness in milling of Quartz glas using diamond wheel. The cutting process in the up-cut milling of glass is discussed and the cutting force measured. The cutting force gradually increases with the cutter rotation at the beginning of the cut, and oscillates about a constant mean value after a certain undeformed chip thickness. The results show that cutting forces and surface roughness do not vary much with experimental cutting speed in the range of 55–93 m/min. The suggested models of cutting forces and surface roughness and adequately map within the limits of the cutting parameters considered.

Cutting Force Model for Contour Surface Machining of Gear Indexing Cam with Flat End Milling

2004 ◽  
Vol 471-472 ◽  
pp. 122-126 ◽  
Author(s):  
P.Q. Guo ◽  
Chuan Zhen Huang ◽  
Ping Zhao
Keyword(s):  
Cutting Force ◽  
Cutting Forces ◽  
End Milling ◽  
Chip Thickness ◽  
Depth Of Cut ◽  
Force Model ◽  
Uncut Chip Thickness ◽  
Thickness Change ◽  
Flat End Milling ◽  
Axial Depth

This paper presents a model to predict the cutting forces for flat end milling as machining gear indexing cam. Rotation feeding makes axial depth of cut and uncut chip thickness change during cutting process. The development of the model is based on the analysis of cutting edge expression. According to the existing the relationship of the local cutting force and chip load and assuming the cutter to be divided into a number of differential elements in the axial direction of the cutter, the model is derived by summarising the cutting forces produced by each differential cutter disc engaged in the cut. The equation for calculating uncut chip thickness of differential disc is educed. In order to avoid the complex computing for axial depth of cut of the entire edge, a unit square window function and its criterion are introduced to estimate whether a segment of edge is in engaging range.

An experimental analysis of minimum chip thickness in micro-milling of two different titanium alloys

2020 ◽  
Vol 234 (12) ◽  
pp. 1486-1498 ◽  
Author(s):  
Kubilay Aslantas ◽  
Luqman KH Alatrushi ◽  
Fevzi Bedir ◽  
Yusuf Kaynak ◽  
Nihat Yılmaz
Keyword(s):  
Surface Roughness ◽  
Surface Quality ◽  
Cutting Forces ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Ti6al4v Alloy ◽  
Micro Milling ◽  
Depth Of Cut ◽  
Minimum Chip Thickness ◽  
Burr Width

Micro-milling is a micro-mechanical cutting method used to obtain complex and three-dimensional micro geometries. Micro-cutting tools are used in the manufacturing of micro-components and the type of workpiece is also important for good surface quality and minimum burr. In this study, micro machinability of Ti6Al4V alloy which is used most frequently in micro-component production is compared with Ti5553 alloy. Micro-milling of Ti5553 alloy and comparison of the minimum chip thickness with Ti6Al4V were performed for the first time in this study. Using different cutting parameters, the variation of surface roughness, burr width, and cutting forces were investigated. The cutting tests were carried out on a specially designed and high-precision micro-milling test system using a TiCN-coated two-flute end mill of 0.6 mm diameter. According to the results, minimum chip thickness is approximately 0.3 times the edge radius of the cutting tool and does not vary with the alloy type. At feed rates smaller than the minimum chip thickness, both the cutting forces increase and the surface quality decreases. For both alloys, reduced feed rate and increased depth of cut lead to increased burr width. The burr widths in Ti6Al4V alloy are higher. At the end of the study, the limits of the cutting parameters where plowing occurred for the both alloys are clearly determined. In addition, the limits of the cutting parameter causing plowing have been confirmed by cutting forces, surface roughness, and burr formation.

scholarly journals A surrogate-assisted optimization approach for multi-response end milling of aluminum alloy AA3105

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2419-2439
Author(s):  
Tamal Ghosh ◽  
Yi Wang ◽  
Kristian Martinsen ◽  
Kesheng Wang
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Material Removal Rate ◽  
Cutting Forces ◽  
Material Removal ◽  
End Milling ◽  
Removal Rate ◽  
Cutting Parameters ◽  
Data Driven ◽  
Optimal Cutting Parameters

Abstract Optimization of the end milling process is a combinatorial task due to the involvement of a large number of process variables and performance characteristics. Process-specific numerical models or mathematical functions are required for the evaluation of parametric combinations in order to improve the quality of the machined parts and machining time. This problem could be categorized as the offline data-driven optimization problem. For such problems, the surrogate or predictive models are useful, which could be employed to approximate the objective functions for the optimization algorithms. This paper presents a data-driven surrogate-assisted optimizer to model the end mill cutting of aluminum alloy on a desktop milling machine. To facilitate that, material removal rate (MRR), surface roughness (Ra), and cutting forces are considered as the functions of tool diameter, spindle speed, feed rate, and depth of cut. The principal methodology is developed using a Bayesian regularized neural network (surrogate) and a beetle antennae search algorithm (optimizer) to perform the process optimization. The relationships among the process responses are studied using Kohonen’s self-organizing map. The proposed methodology is successfully compared with three different optimization techniques and shown to outperform them with improvements of 40.98% for MRR and 10.56% for Ra. The proposed surrogate-assisted optimization method is prompt and efficient in handling the offline machining data. Finally, the validation has been done using the experimental end milling cutting carried out on aluminum alloy to measure the surface roughness, material removal rate, and cutting forces using dynamometer for the optimal cutting parameters on desktop milling center. From the estimated surface roughness value of 0.4651 μm, the optimal cutting parameters have given a maximum material removal rate of 44.027 mm3/s with less amplitude of cutting force on the workpiece. The obtained test results show that more optimal surface quality and material removal can be achieved with the optimal set of parameters.

Effects of Insert Nose Radius and Processing Cutting Parameter on the Surface Roughness of Aisi 316 Stainless Steel

2010 ◽  
Vol 447-448 ◽  
pp. 51-54
Author(s):  
Mohd Fazuri Abdullah ◽  
Muhammad Ilman Hakimi Chua Abdullah ◽  
Abu Bakar Sulong ◽  
Jaharah A. Ghani
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Finish ◽  
Feed Rate ◽  
Cutting Speed ◽  
Chip Thickness ◽  
Cutting Parameters ◽  
Depth Of Cut ◽  
Nose Radius ◽  
Aisi 316

The effects of different cutting parameters, insert nose radius, cutting speed and feed rates on the surface quality of the stainless steel to be use in medical application. Stainless steel AISI 316 had been machined with three different nose radiuses (0.4 mm 0.8 mm, and 1.2mm), three different cutting speeds (100, 130, 170 m/min) and feed rates (0.1, 0.125, 0.16 mm/rev) while depth of cut keep constant at (0.4 mm). It is seen that the insert nose radius, feed rates, and cutting speed have different effect on the surface roughness. The minimum average surface roughness (0.225µm) has been measured using the nose radius insert (1.2 mm) at lowest feed rate (0.1 mm/rev). The highest surface roughness (1.838µm) has been measured with nose radius insert (0.4 mm) at highest feed rate (0.16 mm/rev). The analysis of ANOVA showed the cutting speed is not dominant in processing for the fine surface finish compared with feed rate and nose radius. Conclusion, surface roughness is decreasing with decreasing of the feed rate. High nose radius produce better surface finish than small nose radius because of the maximum uncut chip thickness decreases with increase of nose radius.

Parameter Optimization of Ball End Milling Process on Inconel 718 Using RSM and TLBO Algorithm

2015 ◽  
Vol 15 (3) ◽  
pp. 293-300 ◽  
Author(s):  
Nandkumar N. Bhopale ◽  
Nilesh Nikam ◽  
Raju S. Pawade
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Surface Integrity ◽  
Inconel 718 ◽  
Tool Path ◽  
End Milling ◽  
Spindle Speed ◽  
Depth Of Cut ◽  
Ball End Milling

AbstractThis paper presents the application of Response Surface Methodology (RSM) coupled with Teaching Learning Based Optimization Technique (TLBO) for optimizing surface integrity of thin cantilever type Inconel 718 workpiece in ball end milling. The machining and tool related parameters like spindle speed, milling feed, axial depth of cut and tool path orientation are optimized with considerations of multiple response like deflection, surface roughness, and micro hardness of plate. Mathematical relationship between process parameters and deflection, surface roughness and microhardness are found out by using response surface methodology. It is observed that after optimizing the process that at the spindle speed of 2,000 rpm, feed 0.05 mm/tooth/rev, plate thickness of 5.5 mm and 15° workpiece inclination with horizontal tool path gives favorable surface integrity.

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