Upload
sentient-science
View
202
Download
0
Tags:
Embed Size (px)
DESCRIPTION
Bearing manufacturers and their customers are seeking solutions to speed time-to-market of new products, increase customer confidence during sales cycles, and generate new revenue streams. Physical testing capabilities and industry standards are important for the product design and validation process. However, some of the bottlenecks such as the cost and time can increase the risk of developing innovations, increase the time-to-market of new products, and cause customer to have low confidence of product performance at new product launch.
Citation preview
Improving Bearing Life and Performance
with Computational Testing
What Business Challenge Exists?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Conceptual Design
Detailed Design Prototype
Physical Testing Launch
Customer Tests Product in the FieldFailure
Could this perform better?
Unexpected Bearing Failures
Bearing Failure Causes System Redesign
- How do I change my bearing recommendation for customers?
- How can I quickly predict root cause and determine solutions?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Smart Testing for New Products
New Product Introduction
- How do I decrease go-to-
market time and cost for new
products?
- How do I maintain customer
confidence in the
performance of these new
products?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Perform More Testing in Budget
New Product Introduction
- How would design changes
to my current product lines
improve market share or
price premium?
- How can I market bearings
for each specific customer
application?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Highlight Competitive Advantage
Competitive Tool for
Performance
- How can I prove my bearing
enhancement to customers?
- How can I highlight my
bearing or enhancement’s
competitive advantage?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Fleet Testing and Reliability
Understand Fleet Level,
Warranty Exposure
• How will my supply chain
decisions or requirements
affect my fleet life?
• What is the optimal bearing
for my operational plan?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Serialized Asset Testing
Understand Serial Level, Duty Cycle Life Extension
• How will changing my real-life operating conditions, remanufacturing, and maintenance extend the life of bearings in the field?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
What Business Challenge Exists?
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Conceptual Design
Detailed Design
PrototypePhysicalTesting
Launch
Customer Tests Product in the FieldFailure
Could this perform better?
Computational Testing – Perform 100’s of tests before prototyping
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
4 Main
Features
Vertical
ApplicationsOnline
Help
Private
Customer
Libraries
Online
Support
DigitalClone Technical Approach
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
1) DigitalClone System™
Loads & Requirements &
System Life
6) DigitalClone Live™ Output
Predict-Acquire-Confirm-
Control
2) DigitalClone Material™
Characterize & Create
Microstructure Model
3)DigitalClone
Component™ Friction, &
Lubrication Surface
Treatments
5) Predict Component
Failure Mode/Failure Life
4) Simulate Stress in
Microstructure - Predict
Crack Initiation &
Propagation
Superfinish
Ground Finish
Patents Pending
Failure Modes Ready for
Implementation
• Micropitting Fatigue
• Bending Fatigue
• Spalling Fatigue
• Fretting Fatigue
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Bearing SpallingGear Pitting
Bending Fatigue Spline Fretting
Failure Modes in R&D
Released 2014
• White Etching
• Metal Wear (Abrasion, Adhesion, Scuffing)
• Corrosion Fatigue
• Composite Delamination
• Coating Degradation
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Corrosion Fatigue and Wear
Composite Laminate
Metal Wear
White Layer Etching
Computational Testing Applications
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Component Lifecycle
Prediction
Assembly/System
Lifecycle Prediction
Fleet Analysis,
Monitoring, & Reporting
Manag
ed S
erv
ices
Saa
S/ A
aaS
Materials
Product Lifecycle
RequirementsDesign &
Test
Manufacture
WarrantyOperate &
MaintainReuse/Retire
Materials
Rotorcraft Gearbox Bearing
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
S-N plot for off-shelve (AISI-52100) and
aerospace-quality (SAE-4620) TGB taper roller
bearings
60
70
80
90
100
110
120
130
140
150
160
1 10 100 1000 10000
% o
f D
esig
n L
oad
L10 Life (Million Revolutions)
CLP AISI-52100 CLP SAE-4620 TIMKEN 52100
75%
100%
125%
150%
75% 100% 108% 115% 125% 140% 150%
Ax
ial
Lo
ad
Radial load
0-0.2 0.2-0.4 0.4-0.6 0.6-0.8
Failure probability for 4620 taper
roller bearing under different load
combinations
Rotorcraft Gearbox Bearing
November 20, 2014
Improving Bearing Life and Performance with Computational Testing17
Some RCF spalls/radial cracks in aerospace-quality bearing (clean steel):
Some RCF spalls/radial cracks in off-shelve bearings (steel with inclusions):
Subsurface cracks
initiated at inclusions
Radial cracksRCF spalls
Surface crack
Turbocharger Hybrid Bearing
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
18Sentient Confidential
300.00
350.00
400.00
450.00
500.00
550.00
600.00
650.00
700.00
750.00
0 10000 20000 30000 40000 50000 60000 70000
Fo
rce (
N)
Shaft speed (rpm)
Inner race Outer race
1300.00
1400.00
1500.00
1600.00
1700.00
1800.00
1900.00
2000.00
0 10000 20000 30000 40000 50000 60000 70000
Pre
ssu
re (
MP
a)
Shaft speed (rpm)
Inner race Outer race
0.00
500.00
1000.00
1500.00
2000.00
2500.00
3000.00
3500.00
4000.00
0 10000 20000 30000 40000 50000 60000 70000
L10 (
Millio
n s
haft
rev
olu
tio
ns)
Shaft speed (rpm)
Turbocharger Hybrid Bearing
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
19Sentient Confidential
19
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
80.00
0 10000 20000 30000 40000 50000 60000 70000
Failu
re r
ate
(%
)
Shaft speed (rpm)
General trends seem logical
Turbocharger Hybrid Bearing
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
20Sentient Confidential
• Miner’s rule:
• Assuming:
• n: total number of shaft revolutions required for failure under the
specified duty cycle
• FS (safety factor) = 1
n = 2579.43 million shaft revolutions3.88E-4 n = 1
Duty
cycle
Gearbox Bearing System
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
• Motivation/Problem: Premature cracking on
wind turbine gearbox bearings (NU232,
NU2326, NU2334, NU2336)
• Sentient Objectives:
– Simulate radial cracking and early failure
– Determine problem areas and best fix
Gearbox Bearing System
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
• Case 1: nominal loading condition with no hoop stressNominal Loading High Loading
No Hoop Stress Case 1 – No Failures Case 2 – Radial Cracks
and Pitting/Spalling
With Hoop
Stress
Case 3 – Spalling/Pitting, No
Radial Cracking
Case 4 – Spalling/Pitting,
Little Subsurface Damage
Gearbox Bearing System
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
#4 #3
#2 #1
Premature failure: including hoop stress
Hoop stress effect
Nominal load
Higher load
Exp. Data (Harris & Barnsby)
Jalalahmadi-Sadeghi
Lundberg-Palmgren Theory
Raje-Sadeghi
S-N data for 52100 cylindrical roller bearing (CRB)
Business Challenge Solution
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Conceptual Design
Detailed Design
PrototypePhysicalTesting
Launch
Customer Tests Product in the FieldFailure
Could this perform better?
Computational Testing – Perform 100’s of tests before prototyping
Business Challenge Solution
November 20, 2014
Improving Bearing Life and Performance with Computational Testing
Conceptual Design
Detailed Design
PrototypePhysicalTesting
Launch
Customer Tests Product in the Field
Computational Testing – Perform 100’s of tests before prototyping
Improving Bearing Life and Performance
with Computational Testing