Intelligent Machining & Process Control :
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INTELLIGENT MACHINING & PROCESS CONTROL : Cost optimization in machining Tool wear monitoring • Practical tool wear metrology • Continuous optimization Process stability monitoring • Acoustic and vibration monitoring • LabVIEW based signal processing
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Cost optimization in machining Tool wear monitoring Practical tool wear metrology Continuous optimization Process stability monitoring Acoustic and vibration monitoring LabVIEW based signal processing. Intelligent Machining & Process Control :. Team: . - PowerPoint PPT Presentation
Transcript of Intelligent Machining & Process Control :
INTELLIGENT MACHINING & PROCESS CONTROL :Cost optimization in machining
• Tool wear monitoring• Practical tool wear metrology• Continuous optimization
• Process stability monitoring • Acoustic and vibration monitoring• LabVIEW based signal processing
Sponsor: General Dynamics - OTSCoach: Dr. Tim DalrympleLiaison Engineer: Mr. Keith Brown
William Dressel (ISE)Kevin Pham (EE)Steven Stone (CSC)Sean Sullivan (ME)Phan Vu (ME)
Team:
MACHINELOGIC
Pipe Coupling
Minimize work piece costDetermine tool cost
○ Monitor wear and end of life○ Implement practical metrology
Determine machining costBalance the process to minimize cost
blackbetty420.com
Project Goals & Objectives MACHINELOGIC
Project Goals & Objectives Provide feedback to digital manufacturing
frameworkDevelop data acquisition systemAutomate data and error loggingMonitor machine stability: chatter
detection
MACHINELOGIC
Minimizing Work Piece CostCp = Cfix + Cm + Ct
Cp = Cost per partCfix = Fixed cost associated with the cost of the materialCm = Machining cost Ct = Tooling cost related to tool life and tool change time
T = C (v)p (fr)q
T = Tool lifev = Cutting speedfr = Feed rateC, p, and q = Constants
MACHINELOGIC
Minimizing Cost ProcedureRearrange Cost per part equation:
Take partial derivatives:
Optimal cutting speed:
𝐶𝑝𝑎𝑟𝑡 = 𝑐𝑓𝑖𝑥𝑒𝑑 +ሺ𝜋𝐷𝑚𝐿ሻቆ𝑟𝑚𝑣𝑓𝑟+ 𝑡𝑐ℎ𝑟𝑚 +𝐶𝑡𝑒𝐶𝑣−𝑝+1𝑓𝑟−𝑞+1ቇ
𝜕𝐶𝑝𝑎𝑟𝑡𝜕𝑣 = ሺ𝜋𝐷𝑚𝐿ሻቈ− 𝑟𝑚𝑣2𝑓𝑟+𝑡𝑐ℎ𝑟𝑚 +𝐶𝑡𝑒𝐶𝑓𝑟−𝑞+1 ሺ𝑝−1ሻ𝑣𝑝−2 = 0
𝜕𝐶𝑝𝑎𝑟𝑡𝜕𝑓𝑟 = ሺ𝜋𝐷𝑚𝐿ሻ− 𝑟𝑚𝑣𝑓𝑟2+𝑡𝑐ℎ𝑟𝑚 +𝐶𝑡𝑒𝐶𝑣−𝑝+1 ሺ𝑞−1ሻ𝑓𝑟𝑞−2൨= 0
𝑣𝑜𝑝𝑡 = ቈ𝐶𝑟𝑚
ሺ𝑝−1ሻሺ𝑡𝑐ℎ𝑟𝑚 +𝐶𝑡𝑒ሻ𝑓𝑚𝑎𝑥𝑞 1/𝑝
MACHINELOGIC
Determining Tool Life Through Flank Wear Width
Microscope: Dino-Lite® Wyko Profilometer
Device Cost: $400
Device Cost: $180,000
MACHINELOGIC
Tool Wear Analysis Results
MACHINELOGIC
Calculating Optimum Machining Parameters
Nominal Cutting Speed
Nominal Feed Rate
6338 in/min .02 in/rev
Suggested Cutting Speed
Suggested FeedRate
6972 in/min(~110%) .02 in/rev
Optimal Cutting Speed
Optimal Feed Rate
9066 in/min .02 in/rev
Nominal SuggestedOptimal
MACHINELOGIC
Machining Controller Solution INPUT SYSTEM OUTPUT
Human Machine Interface
Data Acquisition System
Computer
LabVIEW
Analyze Data
Human Machine Interface
Log Data
MACHINELOGIC
Power
Vibration
Audio
OKUMA LC-40 Lathe
Load Controls UPC
CM100 Microphone Kistler Accelerometer
MACHINELOGIC
Prototype GUIMACHINELOGIC
Chatter Detection: Variance
MACHINELOGIC
Chatter Detection: FFT
Model boring bar as fixed-pinned cylinder Calculate natural frequency 1st mode = 3047 Hz Sample signal at 10 kHz Nyquist frequency of 5 kHz
𝝎𝒏= 𝜷𝟐𝟐𝝅ඨ 𝑬𝑰𝝆𝑨𝒄𝑳𝟒
MACHINELOGIC
Chatter Detection: FFTMACHINELOGIC
Signal Process Analog Filtering
Blue – Sampled Frequency Red - Aliased Frequencies
MACHINELOGIC
Sallen-Key Gain in passband: 1
Gain at cutoff (7kHz): 1/2
Design & Test: Low Pass Filter
MACHINELOGIC
Low Pass Filter ResultsMACHINELOGIC
Initial Investment
Cost Per Unit
Units Ordered
Total Investment
Cost Saved
Per Part
Parts Produced Per Shift1
Parts Produced Per Year2
Cost Saved
Per Year2 R.o.I.Prototype Investment $20,000 $12,808 1 $32,808 $0.29 56 13,351 $3,894 11.9%
Industry Level Investment
$106,000 $8,893 6 $159,358 $0.29 340 80,110 $23,365 14.7%
1 Based on 10 hour shift2 Based on one shift per day, 235 work days per year
Initial Investment
Cost Per Unit
Units Ordered
Total Investment
Cost Saved
Per Part
Parts Produced Per Shift1
Parts Produced Per Year2
Cost Saved
Per Year2 R.o.I.
Prototype Investment $20,000 $12,808 1 $32,808 $0.29 58 13,749 $9,362 28.5
%
Industry Level Investment
$106,000 $8,893 6 $159,358 $0.29 351 82,494 $56,173 35.2%
Roughing Operations Optimized with Suggested Machining Parameters
All Operations Optimized
Return on InvestmentMACHINELOGIC
Initial Investment
Cost Per Unit
Units Ordered
Total Investment
Cost Saved
Per Part
Parts Produced Per Shift1
Parts Produced Per Year2
Cost Saved
Per Year2 R.o.I.Prototype Investment $20,000 $12,808 1 $32,808 $0.29 56 13,351 $3,894 11.9%
Industry Level Investment
$106,000 $8,893 6 $159,358 $0.29 340 80,110 $23,365 14.7%
1 Based on 10 hour shift2 Based on one shift per day, 235 work days per year
Initial Investment
Cost Per Unit
Units Ordered
Total Investment
Cost Saved
Per Part
Parts Produced Per Shift1
Parts Produced Per Year2
Cost Saved
Per Year2 R.o.I.
Prototype Investment $20,000 $12,808 1 $32,808 $0.29 58 13,749 $9,362 28.5
%
Industry Level Investment
$106,000 $8,893 6 $159,358 $0.29 351 82,494 $56,173 35.2%
Roughing Operations Optimized with Suggested Machining Parameters
All Operations Optimized
Return on InvestmentMACHINELOGIC
Initial Investment
Cost Per Unit
Units Ordered
Total Investment
Cost Saved
Per Part
Parts Produced Per Shift1
Parts Produced Per Year2
Cost Saved
Per Year2 R.o.I.Prototype Investment $20,000 $12,808 1 $32,808 $0.29 56 13,351 $3,894 11.9%
Industry Level Investment
$106,000 $8,893 6 $159,358 $0.29 340 80,110 $23,365 14.7%
1 Based on 10 hour shift2 Based on one shift per day, 235 work days per year
Initial Investment
Cost Per Unit
Units Ordered
Total Investment
Cost Saved
Per Part
Parts Produced Per Shift1
Parts Produced Per Year2
Cost Saved
Per Year2 R.o.I.
Prototype Investment $20,000 $12,808 1 $32,808 $0.29 58 13,749 $9,362 28.5
%
Industry Level Investment
$106,000 $8,893 6 $159,358 $0.29 351 82,494 $56,173 35.2%
Roughing Operations Optimized with Suggested Machining Parameters
All Operations Optimized
Return on InvestmentMACHINELOGIC
Conclusion Cost savings achieved through higher
cutting speeds
Limited by stability issuesData acquisition system can help address
stability issuesAcoustic data more suitable for detecting
chatter
MACHINELOGIC
Recommendations for Future Develop alternative for LabVIEW Store logged data in database Automatically handle chatter through
lathe control panel Continue tool wear analysis
Automate tool wear measuring process Continue power data analysis
MACHINELOGIC
Questions?
Special Thanks to: IPPD Program General Dynamics Dr. Dean Bartles Dr. Keith Stanfill Mr. Keith Brown Dr. Tim Dalrymple Dr. John Schueller Mr. Gun Lee
