from trial-and-error to predictive machining · vestas wind turbine crashed due to wear of brake...
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From trial-and-error to predictive machining
Ramin [email protected]
Assistant Professor, Engineering Department, Aarhus University Global Manufacturing Festival12 April 2018
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Who we are-What we do
Surface Mechanics Group (SMG)A junior group, started on September 2017
Kai ZaoOlivier Fichefeux Ramin Aghababaei
God made the bulk; the surface was invented by the devil
Advanced computer simulationsand fundamental experiments
on surface phenomena
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Outline
● Surface phenomena: what, why, and where?
● Introduction to Art and science of machining
● Machining simulations: challenges and opportunities
● A new physics-based machining simulator
● Perspective and future road map
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Surface material removal process
Subtractive machiningControlled material removal
WearUnwanted/uncontrolled material removal
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Danish emission inventory for particulate matterNERI No. 189, Ministry of environment, 2003
Vestas wind turbine crashed due to wear of brake systemHornslet, 2008
14k ton Heavy Metal Emissions 2-4% GDP lost due to friction and wear
Technical report from Risø DTUDecember 2008
No.
failu
re/(
turb
ine*
year
)
1993 1998 2005
Germany
Denmark
Brake and tyre wear and road abrasion
Why are these important?
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Danish emission inventory for particulate matterNERI No. 189, Ministry of environment, 2003
Vestas wind turbine crashed due to wear of brake systemHornslet, 2008
14k ton Heavy Metal Emissions 2-4% GDP lost due to friction and wear
Technical report from Risø DTUDecember 2008
No.
failu
re/(
turb
ine*
year
)
1993 1998 2005
Germany
Denmark
Brake and tyre wear and road abrasion
8% downtime in machining process
Billions DKK on tool wear
Why are these important?
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Wear-induced problem
Danish emission inventory for particulate matterNERI No. 189, Ministry of environment, 2003
Vestas wind turbine crashed due to wear of brake systemHornslet, 2008
14k ton Heavy Metal Emissions 2-4% GDP lost due to friction and wear
Technical report from Risø DTUDecember 2008
No.
failu
re/(
turb
ine*
year
)
1993 1998 2005
Germany
Denmark
Brake and tyre wear And road abrasion
8% downtime in machining
Billions DKK on tool wear
Control and reduce wear means saving material, energy, money and environment
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Art and science of machining
https://www.youtube.com/watch?v=JoVQAn7Suto
Chemistry
Engineering
Physics
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Hand drawn sketch of the chip formation, Mallock
Art and science of machining
1881 2011
• Very old yet challenging problem
• Substantial scientific progress (mainly empirical)
• Lack of predictions(surface finish, chip geometry, tool life, …)
• Computer simulations?
Electro-slag remelting
Mild steel ESR steel
Substrateproperties
Coatingproperties
Tool geometry
In-situ microscopic chip formation, 2011
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Challenges in computer simulations of machining
Crack nucleation and propagationYoung modulus
Shear modulus
Hardness
Fracture toughness
Plastic yielding
Strain hardening
Heat capacity
Heat conductance
Rate sensitivitySurface adhesion
Surface roughnessChemistry
Mass
Wettability
Melting temperature
corrosion capacityThermal conductivity
SolubilityFatigue resistance
Microstructures
Contact, friction and wear
Nonlinear deformation
Negligible contributionfrom computer simulations
due to these complexities
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State of the art in machining simulations
Flat surface
No subsurface damage
No toolwear
Valid Jomaa et al., (2017) Québec, Canada
Computer simulations can provide information about
• Machining performance (chipping mechanisms, temperature, forces)
• Properties of machined surface(surface finish, subsurface damage, )
• Anticipate tool wear
• Evolution of force and stress in substrates and tools
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New simulation technique
Aghababaei et al. (2016) Nature Communications, (2017) PNAS, (2018) PRL
Novelties:
• Robust/accurate in computation
• Enable simultaneous modeling of friction, plasticity and fracture
• and it can PREDICT!
Needs further developments:
• Reduce computational expenses
• Extend for a wider range of materials
• Develop a graphical user interface
Scientists solve a long-standing mystery about wear
Researchers simulate wear of materials as they rub together
Researchers have putforth a unified framework
for simulating wear
Fine particles come into greater focus
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Origins of loose wear particles
Aghababaei et al. (2016) Nature Communications, (2017) PNAS, (2018) PRL
Smoo
then
ing
Parti
cle
form
atio
n
1 mm
100 µm 0
3
6
9
12
15
0 50 100 150
Fric
tion
forc
e, N
Sliding distance, um
0
10
20
30
40
50
0 1 2 3Fric
tion
forc
e, N
Sliding distance, mm
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3nm
Superlow friction (tribofilm)
12 nm
Superhigh friction Superhigh friction ~ 1
200 μm
Superlow friction ~ 0.001
200 μm50 nm
DLC coating, when does it work?
200 nm
Fontaine, (2005) Thin Solid Films, Bouchet et al.,(2015) Carbon
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Application to machiningInput parameters:
● Substrate and tool physical properties(young modulus, yielding point, fracture toughness, etc)
● Contact condition between tool and specimen(adhesion, friction, slipping, etc)
● Tool geometry and attacking angle
● Cutting velocity
● Initial surface condition
● Running temperature
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Output:
● Chipping mechanism
● Surface roughness
● Underneath damage
● Force profile and angle
● Tool wear
● Temperature
Physics-based machining simulation
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Single crystal Al machining: [111] planeSingle crystal Al machining: [100] plane
[100]
[010]
[001][110]
[111]
[11-2]
Preliminary simulation results …
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Small details control the machining performance
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Computational predictive machining
●Surface roughness evolution
●Underneath damage
●Chipping mechanisms
●Tool wear
●Force profile evolution
Surface roughness
Underneath damageTool wear
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Next direction: composite machining
Fiber pull out Buckling and fracture Delamination
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Summary
● Machining is a multi-physics phenomena
● Predictive/Precision machining: details matter
● TOMI (τομή, cutting in Greek)a newborn physics-based machining simulator
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perspective and future development
● Develop a graphical user interface (GUI)
● Create on-line platform at AU
● Develop a wide material library
● Extend for complex microstructures
● Further scientific/performance advancement
● Extend for simulating surface treatments (e.g. shot peening, abrasion)
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From trial-and-error to predictive machining
Ramin [email protected]
Assistant Professor, Engineering Department, Aarhus University Global Manufacturing Festival12 April 2018