Optimization of Cutter Life DSES 6070 HV5 Professor Gutierrez-Miravete By: Frank Gibilisco.

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Optimization of Cutter Life DSES 6070 HV5 Professor Gutierrez-Miravete By: Frank Gibilisco

Problem Statement Determine optimal cutter life for 2.000 diameter RNC end mill exposed to a variety of cutting conditions

Assumptions Feed & Speed held constant  Torque controlled machining Operator held constant  Reduce risk of measurement error Each operation will have a failure point  cutter application requires multiple cutters to complete one operation.  Run time is such that replacement is mandatory to reduce risk of damage to part or machine. Cutter Failure Modes 1)Cutter broken 2)Cutter chipped 3)Cutter excessive wear

Methodology Data Collection  30 part sample Minitab / Excel  Best-fit distributions Maple  Verify reliability statistics

Discussion Best Fit Distribution  Weibull vs. Lognormal  Lognormal is used as a repair distribution  Weibull – general distribution with many applications Reliability Statistics  MTTF: 82.711 min  Shape: 4.41186  Scale: 90.739

Results Maple Calculations  Verified Minitab data using shape/scale parameters from Minitab  MRL (@t=60 min) = 28.7 min Interpretation  MTTF: 82.711 min  Consider increasing cutter time limit on machine  Potential savings (\$30000 per year) with process improvements Baseline - 500 cutters ordered per year \$220 per cutter Plot of Survival Function (R)

Conclusions Reliability  MTTF > time limits set by experience  Torque value – limited effect Next steps  Determine effects of changing torque values to utilize available horsepower on machine  Determine effect of new vs. regrind cutters on optimal cutter life / business strategy

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