Robotic total hip arthroplasty is a procedure in which a milling operation is performed on the femur followed by insertion of a prosthetic implant. Although surgeons operate the robots, they do not control the choice of robotic tools and cutting strategies of the robot. Toolpath parameters, such as feedrate, tool geometry, and spindle speeds, govern the cutting forces of the robot. This research covers a methodological approach for finding optimal parameters such that cutting forces and surgical times are reduced. Many different types of orthopedic surgical burs were retrofitted into an advanced computer numerically controlled (CNC) machine, and the characteristics of each tool were evaluated. A simulation cutting model was then developed to find the parameters that could remove the most material in the fastest amount of time without violating any of the safety constraints of surgery. The new methodology proposed not only finds the theoretical optimal parameters but also expedites the process of finding sufficient parameters for orthopedic surgery.

References

References
1.
Paul
,
H. A.
,
Bargar
,
W. L.
,
Mittestadt
,
B.
,
Musits
,
B.
,
Taylor
,
R.
,
Kazanzides
,
P.
,
Zuharas
,
J.
,
Williamson
,
B.
, and
Hanson
,
W.
,
1992
, “
Development of a Surgical Robot for Cementless Total Hip Arthroplasty
,”
Clin. Orthop. Relat. Res.
,
285
, pp.
57
66
.http://journals.lww.com/corr/abstract/1992/12000/development_of_a_surgical_robot_for_cementless.10.aspx
2.
Lundskog
,
J.
,
1972
, “
Heat and Bone Tissue. An Experimental Investigation of the Thermal Properties of Bone Tissue and Threshold Levels for Thermal Injury
,”
Scand. J. Plast. Reconstr. Surg. Suppl.
,
9
, pp.
1
80
.
3.
Sugita
,
N.
, and
Mitsuishi
,
M.
,
2009
, “
Specifications for Machining the Bovine Cortical Bone in Relation to Its Microstructure
,”
J. Biomech.
,
42
(
16
), pp.
2826
2829
.
4.
Plaskos
,
P. C.
,
Hodgson
,
A.
, and
Lavallée
,
S.
,
2005
, “
Safety and Accuracy Considerations in Developing a Small Sterilizable Robot for Orthopaedic Surgery
,”
IEEE International Conference on Robotics and Automation
(
ICRA 2005
), Apr. 18–22, pp.
942
947
.
5.
Sugita
,
N.
,
Nakajima
,
Y.
, and
Mitsuishi
,
M.
,
2008
, “
Dynamic Controlled Milling Process in Bone Cutting Machine for Orthopedic Surgery
,”
Trans. Soc. Instrum. Control Eng.
,
44
(
4
), pp.
377
383
.
6.
Denis
,
K.
,
Van Ham
,
G.
,
Vander Sloten
,
J.
,
Van Audekercke
,
R.
,
Van Der Perre
,
G.
,
De Schutter
,
J.
,
Kruth
,
J.-P.
,
Bellemans
,
J.
, and
Fabry
,
G.
,
2001
, “
Influence of Bone Milling Parameters on the Temperature Rise, Milling Forces and Surface Flatness in View of Robot-Assisted Total Knee Arthroplasty
,”
Int. Congr. Ser.
,
1230
, pp.
300
306
.
7.
Plaskos
,
C.
,
2003
, “
Modelling and Optimization of Bone-Cutting Forces in Orthopaedic Surgery
,”
Med. Image Comput. Comput. Assist. Intervention
,
2878
, pp.
254
261
.
8.
Altintas
,
Y.
,
2000
,
Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design
,
Cambridge University Press
,
Cambridge, UK
.
9.
Budak
,
E.
,
Altintas
,
Y.
, and
Armarego
,
E. J. A.
,
1996
, “
Prediction of Milling Force Coefficients From Orthogonal Cutting Data
,”
ASME J. Manuf. Sci. Eng.
,
118
(
2
), pp.
216
224
.
10.
BoneSim Laboratories
,
2014
, “
BoneSim—Products and Properties
,”
BoneSim Laboratories
,
Cassopolis, MI.
11.
Sardinas
,
R. Q.
,
Mengana
,
J. E. A.
, and
Davim
,
J. P.
,
2009
, “
Multi-Objective Optimisation of Multipass Turning by Using a Genetic Algorithm
,”
Int. J. Mater. Prod. Technol.
,
35
(
1/2
), pp.
134
144
.
12.
Inoue
,
T.
,
Sugita
,
N.
,
Mitsuishi
,
M.
,
Saito
,
T.
,
Nakajima
,
Y.
,
Yokoyama
,
Y.
,
Fujiwara
,
K.
,
Abe
,
N.
,
Ozaki
,
T.
,
Suzuki
,
M.
,
Kuramoto
,
K.
,
Nakashima
,
Y.
, and
Tanimoto
,
K.
,
2010
, “
Optimal Control of Cutting Feed Rate in the Robotic Milling for Total Knee Arthroplasty
,”
2010 Third IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
, pp.
215
220
.
13.
Kianmajd
,
B.
,
Carter
,
D.
, and
Soshi
,
M.
,
2016
, “
A Novel Toolpath Force Prediction Algorithm Using CAM Volumetric Data for Optimizing Robotic Arthroplasty
,”
Int. J. Comput. Assisted Radiol. Surg.
,
11
(
10
), pp.
1871
1880
.
14.
Schreuder
,
H.
, and
Verheijen
,
R.
,
2009
, “
Robotic Surgery
,”
BJOG
,
116
(
2
), pp.
198
213
.
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