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Optimization of Cutter Life

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

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Optimization of Cutter Life

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

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

  3. 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 • Cutter broken • Cutter chipped • Cutter excessive wear

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

  5. 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

  6. 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)

  7. 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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