Geometrical accuracy of microfeatures in micromilling is strictly related with the choice of cutting parameters. Their correct selection is a challenging task in particular when the target feature geometry is a high aspect ratio feature with tight tolerance requirements. Metallic micromilled pins are adopted in many different industrial applications as in the micromold technology field, in the microelectromechanical systems, and in the biomedical devices and their geometrical accuracy represents a fundamental property for their functionality. This work outlines the connection between the achieved geometrical accuracy and the micromilling parameters and cutting strategies on pins with diameter = 100 μm and height = 2 mm (i.e., aspect ratio = 20). Pin geometrical error features are extracted from three-dimensional optical measurements and then correlated with cutting parameters to support machining process setup. A proper fitting based on Chebyshev functions is applied and a statistical analysis assesses the importance of each deviation component in relation to the imposed cutting conditions. The proposed methodology fills the specific lack in the literature domain about micropin machining and can easily extend to different types of geometrical microfeatures. Finally, correlation between part geometrical errors and machining forces is analyzed. Cutting force analysis is adopted in conventional machining for implementing online geometrical errors assessment or compensation methods. However, this study confirms that the applicability of this approach in high aspect ratio pin micromilling is prevented from the predominant scale-effects and the large part bending that generates a low direct correlation between forces and part geometrical errors.

References

References
1.
Gietzelt
,
T.
,
Eichorn
,
L.
, and
Schubert
,
K.
,
2008
, “
Manufacturing of Microstructures With High Aspect Ratio by Micromachining
,”
Microsyst. Technol.
,
14
(9), pp.
1525
1529
.
2.
Masuzawa
,
T.
,
2000
, “
State of the Art of Micromachining
,”
CIRP Ann. Manuf. Technol.
,
49
(
2
), pp.
473
488
.
3.
Dornfeld
,
D.
,
Min
,
S.
, and
Takeuchi
,
Y.
,
2006
, “
Recent Advances in Mechanical Micromachining
,”
CIRP Ann. Manuf. Technol.
,
55
(2), pp.
745
768
.
4.
Huang
,
Y.
,
Zhang
,
X.
, and
Xiong
,
Y.
,
2012
, “
Finite Element Analysis of Machining Thin-Wall Parts: Error Prediction and Stability Analysis
,”
Finite Element Analysis—Applications in Mechanical Engineering
, Vol.
392
,
InTech
, Rijeka, Croatia.
5.
Bolsunovskiy
,
S.
,
Vermel
,
V.
,
Gubanov
,
G.
,
Kacharava
,
I.
, and
Kudryashov
,
A.
,
2013
, “
Thin-Walled Part Machining Process Parameters Optimization Based on Finite-Element Modeling of Workpiece Vibrations
,”
14th CIRP Conference on Modeling of Machining Operations
(
CIRP CMMO
), Vol.
8
, pp.
276
280
.
6.
Bang
,
Y. B.
,
Lee
,
K. M.
, and
Oh
,
S.
,
2005
, “
Five-Axis Micromilling Machine for Machining Micro Parts
,”
Int. J. Adv. Manuf. Technol.
,
25
(9), pp.
888
894
.
7.
Bordatchev
,
E. V.
,
Tauhiduzzaman
,
M.
,
Kugler
,
T.
,
Katz
,
A.
, and
Bohr
,
R.
,
2013
, “
Demonstration of Advanced Capabilities of 5-Axis Micromilling: Geometries With High-Aspect Ratio and/or Optical Surface Quality
,”
ICOMM 8th International Conference on MicroManufacturing
, Victoria, BC, Canada, pp.
357
362
.
8.
Annoni
,
M.
,
Rebaioli
,
L.
, and
Semeraro
,
Q.
,
2015
, “
Thin Wall Geometrical Quality Improvement in Micromilling
,”
Int. J. Adv. Manuf. Technol.
,
79
(5), pp.
881
895
.
9.
Annoni
,
M.
,
Colosimo
,
B. M.
,
Pagani
,
L.
,
Rebaioli
,
L.
, and
Semeraro
,
Q.
,
2014
, “
Geometrical Quality Improvement of High Aspect Ratio Micromilled Pins
,”
Transactions of the North American Manufacturing Research Institution of SME
, Detroit, MI, June 9–13, pp. 524–531.
10.
Benardos
,
P. G.
,
Mosialos
,
S.
, and
Vosniakos
,
G. C.
,
2006
, “
Prediction of Workpiece Elastic Deflections Under Cutting Forces in Turning
,”
Rob. Comput. Integr. Manuf.
,
22
(5–6), pp.
505
514
.
11.
Lopez de Lacalle
,
L. N.
,
Lamikiz
,
A.
,
Sanchez
,
J. A.
, and
Fernandez de Bustos
,
I.
,
2006
, “
Recording of Real Cutting Forces Along the Milling of Complex Parts
,”
Mechatronics
,
16
(
1
), pp.
21
32
.
12.
Marsh
,
E. R.
,
Moerlein
,
A. W.
,
Deakyne
,
T. R. S.
, and
Van Doren
,
M. J.
,
2008
, “
In-Process Measurement of Form Error and Force in Cylindrical-Plunge Grinding
,”
Precis. Eng.
,
32
(
4
), pp.
348
352
.
13.
Li
,
P.
,
Zdebski
,
D.
,
Langen
,
H. H.
,
Hoogstrate
,
A. M.
,
Oosterling
,
J. A. J.
,
Schmidt
,
R. H. M.
, and
Allen
,
D. M.
,
2010
, “
Micromilling of Thin Ribs With High Aspect Ratios
,”
J. Micromech. Microeng.
,
20
(
11
), p.
115013
.
14.
Liu
,
X.
,
Devor
,
R. E.
, and
Kapoor
,
S. G.
,
2006
, “
An Analytical Model for the Prediction of Minimum Chip Thickness in Micromachining
,”
ASME J. Manuf. Sci. Eng.
,
128
(
2
), pp.
474
481
.
15.
Jemielniak
,
K.
, and
Arrazola
,
P. J.
,
2008
, “
Application of AE and Cutting Force Signals in Tool Condition Monitoring in Micro-Milling
,”
CIRP J. Manuf. Sci. Technol.
,
1
(
2
), pp.
97
102
.
16.
Rusu
,
R. D.
, and
Cousins
,
S.
,
2011
, “
3D is Here: Point Cloud Library (PCL)
,”
IEEE International Conference on Robotics and Automation
(
ICRA
), Shanghai, China, May 9–13.
17.
Fischler
,
M. A.
, and
Bolles
,
R. C.
,
1981
, “
Random Sample Consensus: A Paradigm for Model Fitting With Applications to Image Analysis and Automated Cartography
,”
Communications of the ACM
,
24
(
6
), pp.
381
395
.
18.
Venables
,
W. N.
, and
Ripley
,
B. D.
,
2002
,
Modern Applied Statistics With S
,
Springer
, Berlin, p.
498
.
19.
Johnson
,
R. A.
, and
Wichern
,
D. W.
,
1988
,
Applied Multivariate Statistical Analysis
,
Prentice-Hall
,
Upper Saddle River, NJ
.
20.
Montgomery
,
D. C.
,
2006
,
Design and Analysis of Experiments
,
Wiley
, New York.
21.
Colosimo
,
B. M.
, and
Pacella
,
M.
,
2011
, “
Analysing the Effect of Process Parameters on the Shape of 3D Profiles
,”
J. Qual. Technol.
,
43
(3), pp. 169–195.http://asq.org/qic/display-item/index.html?item=33609
22.
ISO
,
2011
, “
Geometrical Product Specifications (GPS)—Straightness—Part 1: Vocabulary and Parameters of Straightness
,” International Organization for Standardization, Geneva, Switzerland, Standard No. 12780-1:2011.
23.
Colosimo
,
B. M.
,
Pacella
,
M.
, and
Semeraro
,
Q.
,
2008
, “
Statistical Process Control for Geometric Specifications: on the Monitoring of Roundness Profiles
,”
J. Qual. Technol.
,
40
(1), pp.
1
18
.http://asq.org/qic/display-item/index.html?item=24017
24.
Henke
,
R. P.
,
Summerhaysb
,
K. D.
,
Baldwinc
,
J. M.
,
Cassoub
,
R. M.
, and
Brownd
,
C. W.
,
1999
, “
Methods for Evaluation of Systematic Geometric Deviations in Machined Parts and Their Relationships to Process Variables
,”
Precis. Eng.
,
23
(
4
), pp.
273
292
.
25.
Donald
,
R. J.
,
Schonlau
,
M.
, and
Welch
,
W. J.
,
1998
, “
Efficient Global Optimization of Expensive Black-Box Functions
,”
J. Global Optim.
,
13
(4), pp.
455
492
.
You do not currently have access to this content.