23
From trial-and-error to predictive machining Ramin Aghababaei [email protected] Assistant Professor, Engineering Department, Aarhus University Global Manufacturing Festival 12 April 2018

From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

  • Upload
    others

  • View
    5

  • Download
    0

Embed Size (px)

Citation preview

Page 1: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

From trial-and-error to predictive machining

Ramin [email protected]

Assistant Professor, Engineering Department, Aarhus University Global Manufacturing Festival12 April 2018

Page 2: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 3: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 4: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Surface material removal process

Subtractive machiningControlled material removal

WearUnwanted/uncontrolled material removal

Page 5: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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?

Page 6: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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?

Page 7: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 8: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Art and science of machining

https://www.youtube.com/watch?v=JoVQAn7Suto

Chemistry

Engineering

Physics

Page 9: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 10: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 11: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 12: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 13: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 14: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 15: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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

Page 16: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Output:

● Chipping mechanism

● Surface roughness

● Underneath damage

● Force profile and angle

● Tool wear

● Temperature

Physics-based machining simulation

Page 17: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Single crystal Al machining: [111] planeSingle crystal Al machining: [100] plane

[100]

[010]

[001][110]

[111]

[11-2]

Preliminary simulation results …

Page 18: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Small details control the machining performance

Page 19: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Computational predictive machining

●Surface roughness evolution

●Underneath damage

●Chipping mechanisms

●Tool wear

●Force profile evolution

Surface roughness

Underneath damageTool wear

Page 20: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Next direction: composite machining

Fiber pull out Buckling and fracture Delamination

Page 21: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

Summary

● Machining is a multi-physics phenomena

● Predictive/Precision machining: details matter

● TOMI (τομή, cutting in Greek)a newborn physics-based machining simulator

Page 22: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

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)

Page 23: From trial-and-error to predictive machining · Vestas wind turbine crashed due to wear of brake system. Hornslet, 2008. 14k ton Heavy Metal Emissions . 2-4% GDP lost due to friction

From trial-and-error to predictive machining

Ramin [email protected]

Assistant Professor, Engineering Department, Aarhus University Global Manufacturing Festival12 April 2018