Cirp icme 17 vibration robotic_milling_v2

CIRP ICME ‘17
11th CIRP International Conference on
INTELLIGENT COMPUTATION IN
MANUFACTURING ENGINEERING
19 - 21 July 2017, Ischia, Naples, Italy
Vibration analysis of robotic milling tasks
Marco Leonesioa, Enrico Villagrossia, Manuel Beschia,
Alberto Marinia, Giacomo Bianchia, Nicola Pedrocchia,
Lorenzo Molinari Tosattia, Vladimir Grechishnikovb, Yuriy
Ilyukhinb, Alexander Isaevb
aCNR - Institute of Industrial Technology and Automation (ITIA)
Via Corti, 12 – 20133 Milano
bMoscow State Technological University Stankin, Moscow, Russia

CIRP ICME ‘17
INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING
Marco Leonesio, Enrico Villagrossi et al.. Vibration analysis of robotic milling tasks
Content
• Robotic milling context
• Problem statement
• Static and dynamic robot posture analysis
• Experimental results

CIRP ICME ‘17
In principle, industrial robots (IRs) could be an excellent alternative for machining, being
both flexible and cheap (if compared to a CNC machine). Unluckily they exhibit 2 main
defects:
- Low positioning accuracy;
- Low static and dynamic disturbance rejection (deflection under process force and
vibration onset).
Typical robot machining operations
Robotic milling context
Polishing Deburring Milling

CIRP ICME ‘17
Problem statement
 Robot pose-dependent stiffness (static and dynamic), which often deteriorates the
overall accuracy and surface integrity, suggests the possibility to exploit DoFs
redundancy to carry out a process-aware pose optimization;
 So far, in literature robot pose optimization has been based on deformation indices
that take into account the sole static deformation.
A preliminary study is required to verify if a pose selection criterion based on EE static
stiffness maximization satisfies the complementary objective of increasing dynamic
stiffness to improve surface quality.

CIRP ICME ‘17
Robot: Comau N16 (6 axes, payload 16Kg)
Spindle: ISEL UFM 1050 (rated power: 1.05kW, max. speed: 25000rpm, max. torque: 0.32Nm)
Sensors: 2 triaxial accelerometers (close to the tool and close to robot flange)
Setup description

CIRP ICME ‘17
Setup description
Depth of Cut [mm]: 1.5
Spindle speed [rpm]: 13000
Feedrate [mm/min]: 1080
Width of Cut [mm]: 6
Tool diameter [mm]: 8
N. flutes: 2
Down milling
Material: Al 6082

CIRP ICME ‘17
Static and dynamic robot posture analysis
Redundant DoF
The rotation around tool axis is a «useless» DoF, because it is redundant with respect to
spindle rotation. Therefore, it can be exploited to optimize robot posture.

CIRP ICME ‘17
Elastic joint
model
    1T
ee J
 
K J q K J q  ,ee ee K K x
Pose-dependent EE stiffness
q: joint coordinates; x: EE «useful» coordinates; KJ: diagonal matrix of joint compliance;
J(q): jacobian;
Robot elasticity has been modeled through
lumped torsional springs at joint level.
1 2 6: ( , ,..., )J j j jdiag k k kK
 : i
j
x
q
 
  
  
J q
Mapping q into x and θ

CIRP ICME ‘17
Compliance index
fee: average milling force;
  max arg maxz CP

 
   2
TTdef
ee ee ee ee T T
C ee ee
ee ee
d d
P   
K f K fx x
v K K v
f f
  min arg minz CP

 
ee
ee

f
v
f Max. Pc Min. Pc
Vfeed x θZ = 85deg θZ = -85deg
Vfeed y θZ = -85deg θZ = -30deg
Pose 2 displ. [mm] Pose 1 displ. [mm]
Vfeed x 0.118 0.0571
Vfeed y 0.125 0.119
(Compute by Altintas’ model)

CIRP ICME ‘17
Experimental modal analysis in Pose 1 (the most rigid)
  /0 0 1
xx xy xz
o yx yy yz x y
zx zy zz
G G G
G G G G
G G G
 
 
  
 
  
v
Oriented transfer function

CIRP ICME ‘17
Experimental modal analysis in Pose 1 (the most rigid)
The most important
resonances from surface
inegrity point of view

CIRP ICME ‘17
Tool tip dynamic compliance has been measured both in Pose 1 & Pose 2
It can be observed that the dynamic compliance peaks are located at a frequency that
is much lower that the Tooth Passing Frequency (433Hz). Hence, the vibration onset
can be ascribed only to robot/process transient phenomena and not to chatter and/or
forced vibration induced by steady cutting force.
Nothing significant at higher frequency

CIRP ICME ‘17
A Dynamic Compliance Index (PDC) is proposed for ranking robot poses in terms of
vibration susceptibility, dual to the static one. The idea is to evaluate the vibration RMS as
the integral of the power spectrum
       
1 Ndef
xxDC xx i i yy i i
i
P G G G G
N
   
 
 
1
2
0.8386 N/mm (Pose 1)
0.6544 N/mm (Pose 2)
Pos
Pos
DC
DC
P
P


Pose 2 displ. [mm] Pose 1 displ. [mm]
Vfeed x 0.118 0.0571
Vfeed y 0.125 0.119
PDC indications contradict Pc
indications …

CIRP ICME ‘17
Experimental results
-X #2 -X #1
+Y #1
+Y #2
+X #1 +X #2
-Y #2
-Y #1

CIRP ICME ‘17
Accelerations and roughness measurements generally agree with PDC indications: Pose 2
is the preferable from the dynamic point of view.

CIRP ICME ‘17
Unlike EE accelerations, dynamic components of joints velocity are higher for Pose 2. It is
worth noting that a higher involvement of the joint motion entails a higher vibrational
energy dissipation by the velocity control loop.
Joints velocity

CIRP ICME ‘17
Conclusions
 The tests executed have shown that the dynamic behavior of the robot and spindle
must be taken into account when the vibrations and the surface roughness are
considered as performance factors;
 A scalar performance factor has been proposed, the “Dynamic Compliance Index”, that
considers the average dynamic compliance power spectrum on a significant frequency
range. The index, computed for the different robot poses, shows an appreciable
correlation to the measured level of vibration at the EE and to the surface roughness;
 Further analyses will be performed on the high frequency region, where spindle
dynamics produce a paramount effect that could impair tool life and threaten spindle
bearings integrity.

CIRP ICME ‘17
INTELLIGENT COMPUTATION IN
MANUFACTURING ENGINEERING
THANK YOU!
Vibration analysis of robotic milling tasks
Marco Leonesioa, Enrico Villagrossia, Manuel Beschia, Alberto Marinia,
Giacomo Bianchia, Nicola Pedrocchia, Lorenzo Molinari Tosattia, Vladimir
Grechishnikovb, Yuriy Ilyukhinb, Alexander Isaevb
aCNR - Institute of Industrial Technology and Automation (ITIA)
Via Corti, 12 – 20133 Milano
bMoscow State Technological University Stankin, Moscow, Russia

Cirp icme 17 vibration robotic_milling_v2

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