Issue
Int. J. Simul. Multidisci. Des. Optim.
Volume 12, 2021
Advances in Modeling and Optimization of Manufacturing Processes
Article Number 27
Number of page(s) 10
DOI https://doi.org/10.1051/smdo/2021025
Published online 29 October 2021

© T. Sekine, Published by EDP Sciences, 2021

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

1 Introduction

Surface topography is one of the vital factors in product features. The manufacturing technologies are being continuously required to create a value-added surface in many industries such as automobile, aerospace, and electronic device. Against the background of industrial demands, a lot of contributions have been made from various perspectives [14]. Among them, a machined surface in milling is attracting persistent attention from industrial society and researchers [511]. The major factors affecting a machined surface has been gradually revealed and considered mostly as cutting parameters, thermal parameters, dynamic parameters, machine tool parameters, tool properties, and workpiece properties [12]. As the technical findings, controlling surface topography in milling enables us to add the surface to a functional property [13,14]. It is also well known that optimizing a path interval in tool path generation can improve not only surface topography but also a balance between cost and product quality in milling [15,16]. The methodologies to determine a single optimum point have been mostly developed based on an algebraic equation derived from geometrical analysis of milling process.

There exist two path intervals on a surface machined by milling. The one is a path interval along the feed direction of a tool, and the other is a path interval along the cross-feed direction of a tool. Path interval determination have mostly focused on the latter [17,18]. Scallop height acts as a dominant factor in the prediction of path interval. Although there are various kinds of tools for milling in these days, typical tool tip geometries have been studied so far in path interval determination with various machining situations [1923]. Among them, multi-axis flat and filleted end milling requires the elaborate treatments according to a machining situation. There are four general classifications of the situations in multi-axis filleted end milling [24]. The derivation of geometrical relationships tends to be unachievable with the two-dimensional expression for the cutting edge geometry, whereas that of three-dimensional (3D) expression entails mathematical complexities according to intersection problems of 3D geometries [25]. A novel procedure to overcome the complexities was reported with respect to an accurate prediction of path interval in filleted end milling with a tool inclination [26]. The results represented that introducing a reference point was important to estimate a path interval correctly in the 3D consideration.

It is crucial to optimize a milled surface topography in high level through selecting suitable machining parameters in milling. There are a variety of methodologies aimed at a point-based optimization of machining parameters in milling [2731]. Cutting force is one of the high-interest topics to enhance finish surface quality and to avoid tool failure. Lazoglu et al. proposed a feedrate scheduling technique based on their force model [32]. Habibi et al. also reported a computationally-inexpensive approach minimizing flute engagement to adjust tool orientation for optimizing surface errors in five axis ball end milling [33]. Moreover, cutter/workpiece engagement is an important factor to figure out suitable processing parameters. Zhang et al. investigated an optimization of tool orientation in 5-axis ball-end milling through a model of cutter/workpiece engagement [34]. Chip thickness is theoretically modeled to estimate the other machining factors. Lotfi et al. gave a model of instantaneous undeformed chip thickness [35]. Residual stress in machined surface is also a measure to optimize processing parameters; in addition, Masmiati and Sarhan revealed an effect of cutting parameters on residual stress in machined surfaces [36]. Although there are dominant processing parameters' optimizations from various perspectives, a few comprehensive strategies have been proposed to determine machining conditions in filleted end milling. The one based on path interval determination has been scarcely reported so far in practice.

The purpose of this study is to demonstrate theoretical approaches useful for practical determination of machining conditions affecting machined surface topography in filleted end milling. Tool orientation is intensively investigated in particular. The remainder of this paper is organized as follows. Section 2 describes geometrical description of multi-axis filleted end milling. Then, multi-layer approach will be explained to determine a suitable path interval in Section 3. The other theoretical approaches for several dominant processing parameters will also be given in Section 4. The demonstration and discussion are made in Section 5. Finally, conclusion and future work are presented in Section 6.

2 Geometrical description of filleted end milling

Several coordinate systems is firstly provided to express a machining state of filleted end milling. Henceforth, an axis of a coordinate system is invariably denoted by a normalized vector. This study introduces three coordinate systems as shown in Figure 1. These right-handed coordinate systems are labelled as G, M, and T. G coordinate system comprises X, Y, Z axes, whose components are (1, 0, 0), (0, 1, 0), and (0, 0, 1), respectively. M coordinate system is also defined based on a surface to be machined. MZ is a unit surface normal on a workpiece. MY is orthogonal to MX, and it is oriented to the scanning direction of a tool; moreover, MY can be obtained from the cross product of MX and MZ.

Two sections are instantaneously set to consider the other coordinate system and inclination angles in filleted end milling. The one is a section based on the scanning direction of a tool (i.e., MZMX plane), while the other is a section based on the cross-feed direction perpendicular to the scanning direction (i.e., MZMY plane). Let these planes be scanning section and cross-feed section, respectively. T coordinate system can be expressed using the two sections. The position of TZ corresponds to that of the rotational axis of a tool, and the direction is oriented to the shank side of tool. As illustrated in Figure 2, tool inclination angle θ denotes the angle between MZ and TZ. TX is geometrically calculated as a vector perpendicular to TZ. The direction depends on the directional relationship between TZ and MZ. Specifically, the angle between TX and MXMY plane is inevitably set to be θ. Then, TY can be obtained from the cross product of TX and TZ.

The angles θs and θc are additionally introduced to derive θ. As shown in Figure 3, θs is the inclination angle on scanning section, designating the angle between MZ and the orthogonal projection of TZ onto scanning section. Likewise, θc is the inclination angle on cross-feed section, indicating the angle between MZ and the orthogonal projection of TZ onto cross-feed section. Counter clockwise rotation is the positive rotational direction of θs and θc.

Given that M coordinate system coincides completely with G coordinate system for simple modeling of filleted end milling, θs and θc can be calculated as follows:(1) (2)where TZx, TZy, and TZz are three components of TZ in each axis of G coordinate system. Since TZ is given as a normalized vector,(3)

Hence, equations (1) and (2) can lead to the following components of TZ:(4) (5)

Substituting equations (4) and (5) to equation (3) provides the following formula:(6)

Accordingly, the angle θ can be offered as an inverse trigonometric function with TZz:(7)

Figure 4 illustrates the positional relationship of two cutting edges in filleted end mill. Although there exist various kinds of cutting edge geometry, this study focuses on a filleted end mill with two flutes and without a helix angle of cutting edges. With reference to Figure 4, a cutting point on a cutting edge in T coordinate system TPe can be calculated as follows: when dae ≥ R − Rcr,(8)and when dae < R − Rcr,(9)

It should be careful that clockwise rotation is the positive rotational direction of ξ and ζ. Common end mills have a number of cutting edges, so that ξ depends on the number of cutting edges nce. In the case that the angular position of a cutting edge overlaps TX axis, ξ can be derived as a simple form:(10)where m is an assigned number of a cutting edge. From the above explanation, a cutting point on a cutting edge Pe can be calculated through the following formula:(11)where RT is coordinate transformation matrix, providing a transformation from T to O coordinate system; moreover, Ptc is an instantaneous tool center shown in Figure 4a, depending on a tool path up until a present position. The geometrical description explained in this section assumes a filleted end mill without a helix angle of cutting edges, while it can effortlessly apply to the common, commercial ones through dividing a tool into small disk elements.

thumbnail Fig. 1

Three coordinate systems in filleted end milling.

thumbnail Fig. 2

Two instantaneous sections and tool inclination angle θ between MZ and TZ.

thumbnail Fig. 3

Inclination angles θs and θc.

thumbnail Fig. 4

Typical tool profile and cutting edges' position.

3 Multi-layer approach

This section describes a novel procedure for theoretical estimation of machined surface topography. Multi-layer approach is introduced as a careful, effectual selection procedure with path interval determination. There are two path intervals associated with a machined surface topography after milling. The one is a path interval in cross-feed direction, and the other is a path interval in feed direction. Let each path interval be path interval Lc and feed interval Lf, respectively. From these definitions, scallop heights can also be given as scallop height hc and feed mark's height hf, respectively.

Considering a variation of the tool orientation for determining a path interval Lc, a variety of the tool orientation derived from a tool geometry projected onto an instantaneous section can be classified into four cases according to θs and θc [24]. The possible situations in 3D geometry can be considered thoroughly based on a tool inclination angle θ. This section mainly deals with filleted end milling under the case that θ ≠ 0.

3.1 Multi-layer concept derived from path interval determination

Two path intervals commonly express a distance between adjacent tool centers in a tool trajectory. Although a path interval in cross-feed direction Lc can be generally calculated as a point-to-point distance, this study focuses mainly on Lc/2. This variable indicates a distance from a tool center to an expediential section located with a predetermined scallop height hc. Figure 5 illustrates several radii, i.e. R, Rb, and Rcr, of filleted end mill with a tool inclination angle θ. A torus is used to express machining states in the cutting edge geometry of filleted end mill.

A machining situation of cutting edge geometry is given in Figure 6, and a torus is used as a model of cutting edge. The coordinate systems in Figure 6 are identical to the ones in Figure 1. The direction of YT axis is the same as that of Y axis, and tool feed direction coincides with the direction of X axis. There are several planes, i.e. a designed surface, workpiece's surface, and two pseudo planes regarding a scallop height hc and a feed mark's height hf. The distance of two planes is situationally changeable in accordance with a variation of designed surface topography. ns is given as a surface normal in each surface and plane. The direction of ns changes depending on the orientation of reference surface or plane.

thumbnail Fig. 5

An assigned torus and several radii.

thumbnail Fig. 6

An assigned torus and several radii.

3.2 Path interval determination in a cross-feed direction

Figure 7 shows the pseudo-code of path interval determination in filleted end milling [26]. The algorithm focuses on hc pseudo plane as an exemplified explanation, whereas the computational process is similarly available for workpiece's surface. In the algorithm, a torus has inclination θ and contacts at a point on a designed surface. When a section as an exact circle is cut out from the torus, there exist three positional relationships between a torus section and hc pseudo plane. The one is an intersection between a torus section and hc pseudo plane, while there exists a positional relationship without an intersection. The other situation is a single contact point between a torus section and hc pseudo plane.

The notation P, t, and u indicate a positional vector in 3D space, a tangent vector at each torus section's center, and a directional vector. Each subscript of these vectors is mainly associated with the positional relationships between a torus section and hc pseudo plane. The subscript base is used for Pbase and tbase which express vectors at torus section's center with a contact point between the torus and a designed surface. Moreover, the distance between Pbase and a designed surface is completely equal to Rcr. The subscript ap is used to express an arbitrary position. γ is an angular parameter for determining an arbitrary position on a circle with Rb. Rearranging the following formula can provide the initial value of γ designated as γap in Figure 7:(12)

A search range in iterative calculation is introduced along a circle with Rb. Pap is an arbitrary position on the circle. Pstart and Pend are temporarily provided as the starting and ending point of search range, respectively. Pstart is a position vector when γ = 0, while Pend is a position vector when γ = 0.5π. A position vector of Pap can be easily derived through rotating Pbase around ZT axis. Moreover, a tangent vector tap can be also calculated using tbase in the same manner. Figure 8 illustrates some variables in a torus section at Pap. Php indicates a positional vector on hc pseudo plane. A direction cosine η between tap and hc pseudo plane can be obtained by the following equation:(13)

A distance ds between Pap and Php can be given as follows:(14)

The subscript scp means a single contact point between a torus section and h pseudo plane. Pscp and tscp are obtained through updating Pap and tap in iterative calculation, which is the first do-while statement in Figure 7. ε is set as the convergence condition of iterative calculation. The second iterative calculation in Figure 7 can ascertain an intersection between a torus section and hc pseudo plane. Through finding out the farthest intersection from the tool center point, the algorithm can provide a suitable path interval Lc/2.

thumbnail Fig. 7

Computational algorithm for determining Lc/2 [26].

thumbnail Fig. 8

Some variables associated with a torus section.

3.3 Path interval determination in a feed direction

Feed interval Lf and feed mark's height hf have been scarcely studied so far. The interval is closely associated with feed per tooth ft. A tool moves along with X axis, and the direction of TX–TZ plane includes a contact point between a torus and a designed surface. Here, let ω be the rotational angle between X axis and TX–TZ plane. The rotation is about Z axis. Then, the following formula can be made to calculate a feed interval:(15)where ft is feed per tooth. Moreover, feed mark's height hf can be mathematically expressed in the same manner to path interval determination in ball end milling.

4 Estimation of the other dominant processing parameters

A milled surface topography can be directly and indirectly affected by the other dominant processing parameters, so that the effectual selection procedures for determining these parameters are also indispensable to obtain a decent topography. With the aim of optimal parameters' selection, this section provides the some theoretical procedures in filleted end milling. Note that the following calculations are unalterably given for one cutting edge during one rotation of a tool.

4.1 Maximum frictional distance

Frictional distance is a critical factor to predict tool wear at the cutting edge. It also has an influence on a machined surface feature. The following formula can provide the maximum length:(16)

In the above formula, αfd is obtained from an arccosine calculation for a scalar product of uscp and −TZ. Moreover, a rotational angle around TZ axis βfd is utilized as the one between TX–TZ plane and a center of torus section having a contact point with a workpiece's surface. Each angle can be extracted as partial results arising inevitably and functionally in the execution of computational algorithm.

4.2 Maximum contact arc length

Contact arc length is defined based on a cutting-related part in a cutting edge, so that it is also an important factor in considering tool surface damage and a machined surface feature. The maximum length can be expressed:(17)

where αcal is easily identified from an angle calculation using Rcr and the depth of cut ddoc which means a distance between a designed surface and workpiece's surface principally. In contrast, αhf can be computed from an angle calculation based on a feed mark's height hf. The execution of computational algorithm including a partial result arising inevitably and functionally can also offer the angle.

4.3 Maximum cutting speed

It is well known that cutting speed has actual impact on both tool surface damage and cutting force. The following expression can be made to estimate the maximum cutting speed:(18)

where s is a spindle speed in cutting process, and αcs is easily identified using the depth of cut ddoc. The execution of computational algorithm with partial functions can instantaneously compute the angle.

4.4 Average uncut chip thickness

Uncut chip thickness is one of the vital factors having great impact on cutting force. It is undoubted that uncut chip thickness affects tool surface damage in practice since cutting force directly depends on material removal rate in machining process. The following formula enables us to calculate the average value:(19)

where αuct indicates an angular parameter for determining an arbitrary position on a cutting edge. In addition, βuct designates an angle between TX axis and GYGZ plane, and the rotation is about TZ axis. The above formula can estimate an uncut chip thickness at any position on a cutting edge. As a brief estimation, an average uncut chip thickness tave was computed in a cutting edge's rotational position where the instantaneous cutting load and area were the largest in both measures, and three angles of αuct were considered for the calculation. The first angle was obtained based on the depth of cut ddoc. The second angle was set to 5 deg. a priori. Finally, their median was also set to the third angle, and the average calculation was conducted with tuct obtained using these angles.

5 Demonstration and discussion

This section describes a demonstration of the estimation approaches proposed above. Especially, we investigated influence of tool orientation on each dominant processing parameter in filleted end milling. The discussion will be given after visualizing characteristics of these parameters. The machining conditions used in the demonstration are shown in Table 1. The tool diameter of end mill was set on the basis of a commonly-used size, and the tool had two straight cutting edges. The unit of angle was set as deg. to aid an intuitive understanding.

The influence of tool orientation on θ is shown in Figure 9. In the figure, each curve for respective θs in graph legends represented increasing tendency with increasing θc in any case. The increasing tendency gradually diminished with increasing θs. Moreover, the differences between each curve became smaller with increasing θc. The results indicated that the variation of θ depended largely on the larger one of two angles θs and θc. As a numerical example, when θs = 20 deg. and θc = 5 deg., the value of θ is 20.52 deg. It was obvious that the effect of θc on the value of θ was extremely small.

The influence of tool orientation on Lc is given in Figure 10. In the figure, each curve for respective θs in graph legends showed decreasing tendency with increasing θc in any case. The decreasing tendency gradually reduced with increasing θs, and an asymptotical behaviour could be observed in any curve. Moreover, the differences between each curve became drastically smaller with increasing θc. The results clearly expressed that the value of Lc was independent of tool orientation in the case of θ having an angle more than 10 deg. To take a numerical example, when θc = 20 deg., the values of Lc were 0.22 mm for θs with 5 deg., 0.24 mm for θs with 10 deg., and 0.26 mm for θs with 20 deg. From the numerical values, the differences in each condition were small. What should be careful here is that these difference would vary according to a pre-determined condition of hc.

The influence of tool orientation on Lf is displayed in Figure 11. In the figure, each curve for respective θs in graph legends represented decreasing tendency with increasing θc in any case. Unlike the decreasing tendency of Lc, that of Lf mildly weakened with increasing θs. The differences between each curve became larger with increasing θc, whereas it can be presumed that there existed the limit of Lf in the case of θ having an angle more than 20 deg. The results revealed that the changing tendency of Lf was completely different from that of Lc. In contrast, it was distinctive that Lf became completely equal in any case without θc. In other words, the fact means that these intersection condition between a torus section and hf pseudo plane coincided perfectly despite the difference in θs.

The influence of tool orientation on slfd is shown in Figure 12. In the figure, each curve for respective θs in graph legends represented decreasing tendency with increasing θc in any case. They can be seemingly observed as straight decline. Moreover, the differences between each curve became gradually smaller with increasing θc. The results denoted that the values of slfd appeared to converge towards a certain value with increasing θc. As an example of numerical results, when θc = 20 deg., the values of slfd were 4.82 mm for θs with 5 deg., 4.71 mm for θs with 10 deg., and 4.32 mm for θs with 20 deg. Numerically, the values of slfd are likely to become convergent in the case of θc with more than 20 deg.

The influence of tool orientation on slcal is given in Figure 13. In the figure, each curve for respective θs in graph legends represented decreasing tendency with increasing θc in any case. The differences between each curve became larger with increasing θc, whereas it could be presumed that there existed the limit of slcal in the case of θc having an angle more than 20 deg. The results indicated that contact arc length was largely unaltered in any case. They also implied that the intersection conditions between a torus section and workpiece's surface were almost identical despite the difference in θ. In the pre-determined condition of ddoc, the values of slcal were 0.95 mm in any case when θc = 0 deg. In addition, when θc = 20 deg., they were 0.91 mm for θs with 5 deg., 0.92 mm for θs with 10 deg., and 0.93 mm for θs with 20 deg. From the numerical values, there was little difference in each tool orientation.

The influence of tool orientation on vcs is represented in Figure 14. In the figure, each curve for respective θs in graph legends showed increasing tendency with increasing θc in any case. The increasing tendency gradually diminished with increasing θs. Moreover, the differences between each curve became smaller with increasing θc. As a numerical example, when θs = 20 deg. and θc = 5 deg., the value of vcs was 47.92 m/min. Likewise, when θs = 5 deg. and θc = 20 deg., the value of vcs was 47.92 m/min. In the two machining states, θ was 20.52 deg. It was obvious from the results that the value of vcs was completely identical under the same θ.

The influence of tool orientation on tave is displayed in Figure 15. In the figure, each curve for respective θs in graph legends indicated decreasing tendency with increasing θc in any case. The differences between each curve became larger with increasing θc, whereas it can be presumed that there existed the limit of tave in the case of θc having an angle more than 20 deg. The results implied that an instantaneous cutting force acting on a cutting edge decreased with increasing θ. With reference to the variation of tave, the decreasing rate would be especially prominent in the small value of θs.

Wojciechowski et al. reported several relationships between three average forces in cutting process and average uncut chip thickness under some inclination angles in ball end milling [37]. From their results, tangential and radial average forces increased with increasing average uncut chip thickness, whereas axial one decreased in the same condition. In addition, the changing tendencies of three average forces became moderate with increasing an inclination angle. They also provided that there were precipitous variations of average forces within an inclination angle less than 15 deg. In contrast, the variations had a little change when an inclination angle was more than 15 deg. It was also denoted that a width of flank wear depended on an amount of average forces.

Budak and Ozlu investigated some relationships between cutting forces and feed rates in machining process [38]. The results showed that a cutting force increased with increasing a feed rate. In addition, an amount of cutting force depended on a depth of cut.

Bouzakis et al. studied some relationships between tool orientation and surface roughness in ball end milling [39]. Their results revealed that oblique plunge up and down milling were extremely desirable tool orientations in terms of surface roughness and cutting force. Especially, oblique plunge up milling was recommended from the experimental results obtained using some materials. Moreover, surface roughness around 10 deg. could stay as the smallest value.

As one possible conclusion from the results and findings described above, optimal angle of θ is in a range of 15–20 deg. in filleted end milling without θc. This condition can achieve both high production efficiency and decent surface feature since two path intervals Lc and Lf are theoretically large. Oblique plunge up milling is also recommended highly under the condition of a tool inclination along a tool feed direction.

Table 1

The machining conditions in filleted end milling.

thumbnail Fig. 9

Influence of θs and θc on θ.

thumbnail Fig. 10

Influence of θs and θc on Lc.

thumbnail Fig. 11

Influence of θs and θc on Lf.

thumbnail Fig. 12

Influence of θs and θc on slfd.

thumbnail Fig. 13

Influence of θs and θc on Lcal.

thumbnail Fig. 14

Influence of θs and θc on vcs.

thumbnail Fig. 15

Influence of θs and θc on tave.

6 Conclusions

In this study, theoretical approaches were demonstrated to determine machining conditions affecting machined surface topography in filleted end milling. After geometrical description was explained to model multi-axis filleted end milling, multi-layer approach and the other theoretical approaches were proposed to obtain decent surface topography generated in filleted end milling. The analytical example focusing on tool orientation was given with discussion. As a result, some characteristics of theoretical approaches were revealed with visual evidences. The findings led to one possible conclusion that optimal angle of θ was in a range of 15–20 deg. without θc. Oblique plunge up milling is also recommended highly under the condition of a tool inclination along a tool feed direction.

As a future work, the further detailed analysis will be conducted in a wide variety of conditions, and the experimental verification will be made to evaluate validity and applicability of theoretical approaches proposed in this study.

Nomenclature

X, Y, Z : global, stationary coordinate system (O coordinate system)

MX, MY, MZ : M coordinate system

TX, TY, TZ : T coordinate system

θ: tool inclination angle [rad]

θs: tool inclination angle in feed direction [rad]

θc: tool inclination angle in cross-feed direction

R: tool radius

R: corner radius of cutting edge

Rb: major radius of torus

Ptc : tool center

Pe : a cutting point on a cutting edge

TPe : a cutting point on a cutting edge in T coordinate system

RT : transformation matrix

ψ: positional angle in a filleted part on a cutting edge [rad]

ξ: initial angle between TY and each cutting edge [rad]

ζ: rotational angle of a cutting edge [rad]

nce: the number of cutting edges

Lc: path interval in cross-feed direction [mm]

Lf: path interval in feed direction [mm]

hc: scallop height [mm]

hf: feed mark's height [mm]

Pbase, Pstart, Pend : a positional vector

Pap, Pscp, Php : in each applicable part

tbase, tap, tscp : a tangent vector in each applicable part

ns: surface normal

mscp, uscp: a directional vector in each applicable part

γ: an angular parameter for determining an arbitrary position on a circle with Rb [rad]

η: a direction cosine between tap and an applicable surface or plane

ds: a distance between Pap and Php [mm]

ft: feed per tooth [mm/tooth]

ω: the rotational angle between X axis and TX − TZ plane [rad]

Slfd: maximum frictional distance [mm]

Slcal: maximum contact arc length [mm]

vcs: maximum cutting speed [m/min]

tuct: uncut chip thickness [mm]

tave: average uncut chip thickness [mm]

αfd, βfd, αcal, αhf: an angular parameter

αcs, αuct, βuct: at each applicable part [rad]

Acknowledgments

The authors would like to thank the financial support provided by OSG Fund, Shotoku Science Foundation, and the research grant from Faculty of Science and Technology, Seikei University.

References

  1. P.G. Benardos, G.C. Vosniakos, Predicting surface roughness in machining: a review, Int. J. Mach. Tools Manuf. 43, 833–844 (2003) [Google Scholar]
  2. C. Lu, Study on prediction of surface quality in machining process, J. Mater. Process. Technol. 205, 439–450 (2008) [Google Scholar]
  3. S.G. Croll, Surface roughness profile and its effect on coating adhesion and corrosion protection: a review, Prog. Org. Coat. 148, 105847 (2020) [Google Scholar]
  4. S.J. Zhang, S. To, S.J. Wang, Z.W. Zhu, A review of surface roughness generation in ultra-precision machining, Int. J. Mach, Tools Manuf. 91, 76–95 (2015) [Google Scholar]
  5. H.L. Fisher, J.T. Elrod, Surface finish as a function of tool geometry and feed − a theoretical approach, Microtechnic 25, 175–178 (1971) [Google Scholar]
  6. W.A. Kline, R.E. DeVor, I.A. Shareef, The prediction of surface accuracy in end milling, ASME. J. Eng. Ind. 104, 272–278 (1982) [Google Scholar]
  7. K-H. Fuh, C-F. Wu, A proposed statistical model for surface quality prediction in end milling of Al alloy, Int. J. Mach Tools Manuf. 35, 1187–1200 (1995) [Google Scholar]
  8. H. Paris, G. Peigne, R. Mayer, Surface shape prediction in high speed milling, Int. J. Mach, Tools Manuf. 44, 1567–1576 (2004) [Google Scholar]
  9. Y. Mizugaki, K. Kikkawa, H. Terai, M. Hao, T. Sata, Theoretical estimation of machined surface profile based on cutting edge movement and tool orientation in ball-nosed end milling, CIRP Annals. 52, 49–52 (2003) [Google Scholar]
  10. T. Sekine, T. Obikawa, M. Hoshino, Establishing a novel model for 5-axis milling with filleted end mill, J. Adv. Mech. Des. Syst. Manuf. 6, 296–309 (2012) [Google Scholar]
  11. T. Sekine, T. Obikawa, Novel path interval determination in 5-axis flat end milling. Appl. Math. Model. 39, 3459–3480 (2015) [Google Scholar]
  12. A.M. Khorasani, M.R.S. Yazdi, M.S. Safizadeh, Analysis of machining parameters effects on surface roughness: a review, Int. J. Comput. Mater. Sci. Surf. Eng. 5, 68–84 (2012) [Google Scholar]
  13. T. Matsumura, S. Takahashi, Micro dimple milling on cylinder surfaces, J. Manuf. Process. 14, 135–140 (2012) [Google Scholar]
  14. I. Perez, A. Madariaga, P.J. Arrazola, M. Cuesta, D. Soriano, An analytical approach to calculate stress concentration factors of machined surfaces, Int. J. Mech. Sci. 190, 106040 (2021) [Google Scholar]
  15. Y. Quinsat, L. Sabourin, C. Lartigue, Surface topography in ball end milling process: description of a 3D surface roughness parameter, J. Mater. Process. Technol. 195, 135–143 (2008) [Google Scholar]
  16. R.B. Käsemodel, A.F. de Souza, R. Voigt, I. Basso, A.R. Rodrigues, CAD/CAM interfaced algorithm reduces cutting force, roughness, and machining time in free-form milling. Int. J. Adv. Manuf. Technol. 107, 1883–1900 (2020) [Google Scholar]
  17. Y.K. Choi, A. Banerjee, J.W. Lee, Tool path generation for free form surfaces using Bézier curves/surfaces, Comput. Ind. Eng. 52, 486–501 (2007) [Google Scholar]
  18. T. Obikawa, T. Sekine. A higher-order formula of path interval for tool-path generation, Int. J. Autom. Technol. 5, 663–668 (2011) [Google Scholar]
  19. L.T. Tunc, Smart tool path generation for 5-axis ball-end milling of sculptured surfaces using process models, Robot. Comput. Integr. Manufactur. 56, 212–221 (2019) [Google Scholar]
  20. G.M. Mladenovic, L.M. Tanovic, K.F. Ehmann, Tool path generation for milling of free form surfaces with feedrate scheduling, FME Trans. 43, 9–15 (2015) [Google Scholar]
  21. T. Sekine, T. Obikawa, Novel path interval determination in 5-axis flat end milling, Appl. Math. Model. 39, 3459–3480 (2015) [Google Scholar]
  22. D. Plakhotnik, B. Lauwers, Computing of the actual shape of removed material for five-axis flat-end milling, Comput. Aided Des. 44, 1103–1114 (2012) [Google Scholar]
  23. S. Segonds, P. Seitier, C. Bordreuil, F. Bugarin, W. Rubio, J.M. Redonnet, An analytical model taking feed rate effect into consideration for scallop height calculation in milling with torus-end cutter, J. Intell. Manuf., 30, 1881–1893 (2019) [Google Scholar]
  24. T. Sekine, T. Obikawa, M. Hoshino, Establishing a novel model for 5-axis milling with filleted end mill, J. Adv. Mech. Des. Syst. Manufactur. 6, 296–309 (2012) [Google Scholar]
  25. T. Sekine, A 3D geometrical consideration of path interval in filleted end milling, J. Jpn. Soc. Abras. Technol. 60, 515–519 (2016) (in Japanese) [Google Scholar]
  26. T. Sekine, A computational algorithm for path interval determination in multi-axis filleted end milling, Adv. Sci. Technol. Res. J. 14, 198–205 (2020) [Google Scholar]
  27. R.A. Mali, T.V.K. Gupta, J. Ramkumar, A comprehensive review of free-form surface milling- Advances over a decade, J. Manufactur. Process. 62, 132–167 (2021). [Google Scholar]
  28. I. Mukherjee, P.K. Ray, A review of optimization techniques in metal cutting processes, Comput. Ind. Eng. 50, 15–34 (2006) [Google Scholar]
  29. A.M. Khorasani, M.R.S. Yazdi, M.S. Safizadeh, Analysis of machining parameters effects on surface roughness: a review, Int. J. Comput. Mater. Sci. Surf. Eng. 5, 68–84 (2012). [Google Scholar]
  30. I. Perez, A. Madariaga, P.J. Arrazola, M. Cuesta, D. Soriano, An analytical approach to calculate stress concentration factors of machined surfaces, Int. J. Mech. Sci. 190, 106040 (2021) [Google Scholar]
  31. R.B. Käsemodel, A.F. de Souza, R. Voigt, I. Basso, A.R. Rodrigues, CAD/CAM interfaced algorithm reduces cutting force, roughness, and machining time in free-form milling, Int. J. Adv. Manuf. Technol. 107, 1883–1900 (2020) [Google Scholar]
  32. I. Lazoglu, S.E.L. Khavidaki, A. Mamedov, H. Erdim, Process optimization via feedrate scheduling in milling. In: The International Academy for Production Engineering, edited by L. Laperrière, G. Reinhart, CIRP Encyclopedia of Production Engineering. Springer, Berlin, Heidelberg (2014) [Google Scholar]
  33. M. Habibi, Z.M. Kilic, Y. Altintas, Minimizing flute engagement to adjust tool orientation for reducing surface errors in five-axis ball end milling operations, ASME. J. Manuf. Sci. Eng. 143, 021009 (2021) [Google Scholar]
  34. X. Zhang, J. Zhang, X. Zheng, B. Pang, W. Zhao, Tool orientation optimization of 5-axis ball-end milling based on an accurate cutter/workpiece engagement model, CIRP J. Manufactur. Sci. Technol. 19, 106–116 (2017) [Google Scholar]
  35. S. Lotfi, B. Rami, B. Maher, D. Gilles, B. Wassila, An approach to modeling the chip thickness and cutter workpiece engagement region in 3 and 5 axis ball end milling, J. Manuf. Process. 34, 7–17 (2018) [Google Scholar]
  36. N. Masmiati, A.A.D. Sarhan, Optimizing cutting parameters in inclined end milling for minimum surface residual stress − Taguchi approach, Measurement 60, 267–275 (2015) [Google Scholar]
  37. S. Wojciechowski, R.W. Maruda, P. Nieslony, G.M. Krolczyk, Investigation on the edge forces in ball end milling of inclined surfaces, Int. J. Mech. Sci. 119, 360–369 (2016) [Google Scholar]
  38. E. Budak, E. Ozlu, Development of a thermomechanical cutting process model for machining process simulations, CIRP Ann. 57, 97–100 (2008) [Google Scholar]
  39. K.D. Bouzakis, P. Aichouh, K. Efstathiou, Determination of the chip geometry, cutting force and roughness in free form surfaces finishing milling, with ball end tools, Int. J. Mach. Tools Manufact. 43, 499–514 (2003) [Google Scholar]

Cite this article as: Tsutomu Sekine, Theoretical approaches for determining machining conditions affecting a machined surface topography in filleted end milling, Int. J. Simul. Multidisci. Des. Optim. 12, 27 (2021)

All Tables

Table 1

The machining conditions in filleted end milling.

All Figures

thumbnail Fig. 1

Three coordinate systems in filleted end milling.

In the text
thumbnail Fig. 2

Two instantaneous sections and tool inclination angle θ between MZ and TZ.

In the text
thumbnail Fig. 3

Inclination angles θs and θc.

In the text
thumbnail Fig. 4

Typical tool profile and cutting edges' position.

In the text
thumbnail Fig. 5

An assigned torus and several radii.

In the text
thumbnail Fig. 6

An assigned torus and several radii.

In the text
thumbnail Fig. 7

Computational algorithm for determining Lc/2 [26].

In the text
thumbnail Fig. 8

Some variables associated with a torus section.

In the text
thumbnail Fig. 9

Influence of θs and θc on θ.

In the text
thumbnail Fig. 10

Influence of θs and θc on Lc.

In the text
thumbnail Fig. 11

Influence of θs and θc on Lf.

In the text
thumbnail Fig. 12

Influence of θs and θc on slfd.

In the text
thumbnail Fig. 13

Influence of θs and θc on Lcal.

In the text
thumbnail Fig. 14

Influence of θs and θc on vcs.

In the text
thumbnail Fig. 15

Influence of θs and θc on tave.

In the text

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