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TRAM3 Aerospace Conference
Machining: A Dynamic FuturePresented by:Dr. Sam Turner Head of Machining AMRC.Dr. Thomas S. Delio, President MLI
TRAM3 Aerospace ConferenceThursday, September 12, 2012IMTS 2012, McCormick Place, Chicago IL
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• Trends– Near Net Shape.– Smart Machining.– Difficult to machine materials.– Extreme geometries.
• Influence of Dynamics– Always present– Chatter– Surface finish– Part tolerance
Machining in a Dynamic World
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• Probably one of the most researched but least adopted and implemented area of machining technology of the last 50 years.– Thousands of papers written in the last 20-30 years.– Only a handful of instances where some aspect of it has been applied.
• Non-uniform cutter designs.• Spindle Speed control strategies.• Tuned and passive damper systems.
• When applied it is usually ad-hoc and not in a directed or intentionally deterministic fashion.– Non-uniform designs may be simply randomized initially and then
iterated and not designed for a particular application.– Modal analysis of machine tools is frequently performed during machine
design and prototyping but does not necessarily take into account anticipated machine application and operating conditions.
• However, things are changing and directed dynamic design is becoming more prevalent.
– Can be somewhat analogous to other technologies like feed control.
Machining Dynamics: The Past
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Is it always successfully applied? Check out the show……….
Several booths where machiningwas occurring high vibration levels were obvious
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• Acknowledge, Implement and Integrate dynamics across the machining process.– Process Planning
• Pre-machined form (near net geometry).• Machining System selection.
• Process Parameter Selection (First Part Correct)• Part Path Planning/Verification (Vibration and Tolerance prediction and
control)
– Smart Machining• Detect deviations from designed process behavior.• Diagnose process and determine source of deviations. • Correct source not symptoms and avoid numerous corrections.• Provide temporary solution(s) by adjusting process parameters.
• Result• Directed dynamic design.• Repeatable processes.• Robust to uncertainty
Vision: Use of Dynamics in Machining
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• Development of Chatter and Machining Vibration Theory– 1950’s: Original chatter/vibration theory and concepts, feedback and regenerative chatter.
• 1954 Tlusty (directionality); and 1959 Tobias (non-linearity)• First practical applications
– 1970 Dynamic testing of machine tools, U.M.I.S.T. Manchester, Tlusty– 1970’s Face-milling, sensor detection University of Aachen, Weck, – Late 1970’s Spindle Speed variation Takemura, Sakisaka, Hoshi, Sexton
• First High Speed Spindle Developments– Late 70’s-80’s Air Force Research, PRDA programs.– 1987 SETCO High-Speed, High-Power, Highly Stable Milling Spindle, 1990’s Fisher 40/40,,
others.• Time Domain Simulations and Machining System Analysis
– 1980’s McMaster University Tlusty, Altintas; others.– 1990’s Cutting Performance Analyzer, MLI, ANSI B5.54 Chapter 7 dynamic testing.
• Automated control and active damping systems– 1980’s and 1990’s Audio detection and improved feed back algorithm’s and first commercial
applications.– University of Florida with Tlusty, Smith, Delio, Zamudio, Cobb, Stern, Winfough
– 1992 U.S. Patent 5,170,358 (integrated chatter feedback control)– 1996 U.S. Patent 5,518,347 “Tuned damping system for suppressing vibrations during machining”– 2000 U.S. Patent 6,085,121 and International Patents, “Method for recommending
dynamically preferred speeds for machining”
Brief History50’s Theory 70’s Practical
Application80’s‐90’s High Speed
Spindles
80’s‐90’s Time Domain Simulations
and Machining Analysis
90’s – 2000’s Automated control and active damping
systems.
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• 1970 UMIST, Specifications and Tests on Metal Cutting Machine Tools• 1975, 1976 Weck, et. al., and Gather University of Aachen:
– Face Milling systems– Prior knowledge of system dynamics required.
• 1974-1978, Takemura et. al., Hoshi et. al., Sexton et. al., Inamura et. al.– Spindle Speed Variation.– Suppressed or lessen chatter, did not fully eliminate it.
• 1987 Cofer University of Florida– Chatter and vibration detections
• Not spectral based.• Only 75% accurate.
• 1986-1995, Smith, Delio, Winfough, et. al. MTRC University of Florida.– Automatic Chatter Avoidance: Spectral Based. Machine Integrated
• 1999- 2008 Morgan, Turner, et. al.– Enhanced and intelligent vibration detection methods.– Tighter integration into machine tool control.– Constrained layer damping.
First Academic Implementations
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• Cutting Performance Analyzer (CPA), MLI 1990’s• Precision High-Speed Machining with
vibration control, Ingersoll Milling, McDonnell Douglas (1994)
– Speed control and active damping– J. Halley: Produce-ability Engineering Group,
McDonnell Douglas• Chatter Recognition and Control, “CRAC”
– Interactive system installed on a Makino A55 in 1996 for the government of Malaysia, (McDonnell Douglas sponsored, delivered by MLI).
– Interfaced through analog connection to speed and feed overrides.• Harmonizer (1996)
– First released by MLI and later marketed by Ingersoll Cutting Tools, later by MLI as an App for iOS and Android operating systems.
First Commercial Installations
CRAC, Malaysia
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• AMRC (2006)– Directed damping
• Constrained layer, pneumatics, particle dampers, tuned mass, MR fluid
– Adaptive system integrated with lobe predictions on machine.• Combined predictive, stability diagrams with corrective strategies.
• Machine Tool Companies (2008)– SSV Okuma and Haas– Navi™ by Okuma– Makino (Autonomic Spindle Technology)
• iOS and Android Apps (2010)
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Stability Lobe Diagrams (Dynamics gaining wider acceptance)
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Stability Lobe Diagram
Courtesy: BlueSwarf LLC
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• Process Planning– Job cost estimation.– Manufacturability assessment.– Assist in process design, e.g. selection of best holder, tool, machine.
• Tool Crib– Tool tuning.– Tool customization and matching to machines.– Setup reduction, standardization.
• NC Programming– Enhance tool data parameters, comprehensiveness and accuracy.– Program verification.
• Maintenance– Predictive or Preventive maintenance– Detect shifts in dynamic characteristics, improve quality.
• Production– Adverse vibration detection, diagnosis.– Process adaptation.
Applications of Dynamic Technology.
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• Predictive– Identify dynamic characteristics
• From machine and part design• Measurement or modeling. • Intelligent Process Development
– Predict cutting behavior.– Optimize with virtual tools.
• Adaptive– Process monitoring of machining vibration.– Detect when allowable vibration levels are exceeded.– Manual or integrated with machine tool.– Design cutting tests.
Two Fundamental Approaches
Stability Diagram
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• Complete machining analysis, full speed and load range.
– All can be done a-priori and stored.– Generally done statically– Possible load or speed dependence
on dynamic parameters.– Extra effort to include both work piece
and cutting tool.
• Optimizable, repeatable.• No machining time, tooling or scrapped parts.
– Some time needed to perform measurement.
• Repeatability and baseline.– Right First Time– Cost Avoidance
Predictive Advantages and Disadvantages
Tool Dashboard
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• Automatable and low skill set required.– Still requires either interruption of cutting process or pre-test.– No guarantee of optimization.
• With correct sensor selection can automatically include complete cutting components including work piece dynamics.
• Reactive, not predictive and can destroy parts and tools.
• Performance limited by machine capabilities.
• Time consuming to produce reference or baseline measurements.
Adaptive Advantages and Disadvantages
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• Predict Frequency shifts– FRFs can change
• under load or speed• Due to wear or “events”, or position.
– Spindle models can simulate changes in bearing and contact conditions, SPA Model
0 Hz 2500 Hz 5000 Hz 7500 Hz
0.00e+00
5.00e-07
-5.00e-07
-1.00e-06
2019181716151413121110987654321
Real Flexibility (m/N) versus Frequency (Hz)
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• Products– ChatterMaster (Vibraction)– Cut-Pro (MAL)– Harmonie (TOOL)– MetalMAX (MLI)
• Capabilities– Rotating spindle FRF measurements– Tool dynamic data management- CAD/CAM integration– Tool-path and parameter optimisation– Process Damping– Machine Tool structural dynamics– Special tool or machine designs to inhibit chatter development.
Non-uniform Design
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• In process monitoring.– MTConnect– On machine tool optimisation
• Adaptive– Controller response time means that chatter will be incurred
briefly and can cause damage– Such a system can be used as a backup
• OEMs– MAPS (DMG-Mori)– Navi (Okuma)– Fisher
• Trouble shooting/ process development/ teach mode• Diagnostic
– Preventive Maintenance– With knowledge of baseline dynamics.
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• Tools available to compute forces and dynamic behaviour for CAM programme– MLI Metalmax– Blueswarf dashboards– MAL Virtual Machining (Cut-Pro)
• Verification Tools – Third Wave - Production Module (indirectly includes
dynamic behaviour)– VERICUT – OptiPath (can load process limits)– Many CAM packages incorporate process parameter look
up tables, detailed tool assembly definitions.– Tool management systems can track process parameter
data.
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• Spindle health monitoring systems
• Detect and alarm for overloads in vibration
• Detect a change in dynamic behaviour over time
• Could use vibration,FRF and model datato perform advanceand specific diagnosis
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• Automatic prove out, AMRC 2003.• Proven parameters can be written to tool data
management system • Prior knowledge of tool FRF will quicken cycle but is
not essential
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• Receptance coupling- measure once , optimise whole suite.
• Tool dynamic data management-CAD/CAM integration
• Surface Location Error (SLE)– Forced vibration dependent.– Problematic across entire speed range
and dependent on dynamic characteristics as well as cut profile.
• Dynamic Data Machining Handbook (DDMH)– Interactive, queried machining handbook
that includes effects of dynamics.
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• With intelligent application dynamics can yield benefits on difficult materials
• Titanium drag brace optimisation• Cycle time reduced by 50%
• Large stable roughing cuts• Pocketing with process damped tooling assemblies• Special tools to remove fork ends• Tool paths to maintain radial depth of cut and load
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• Large stable roughing cuts: 1” x 5”• Low tooth passing frequency due to Vs constraint• Large cuts where tool modes are stabilised
– Tune machine tool structure and determine stability lobes for low rpm high productivity roughing
Tuning of ram position for optimum productivity
Stability lobe from cross transfer function for Machine structural modes
0.0 32.0 64.0 96.0 128.0 160.0 192.0 224.0 256.0 288.0 320.0-20282
584
886
1188
1490
1792
20942395
Frequency, Hz
Mag
nitu
de
Fixture/Machine structure accels.
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• Pocketing with process damped tooling assemblies– Tune tool and tool holder to raise
frequency of first dominant mode– Increase the maximum surface
speed before chatter is induced
0 Hz 2500 Hz 5000 Hz 7500 Hz
0.0
5.00e-7
-5.00e-07
-1.00e-06
-1.50e-06
13128765
2Real FRF for 12mm end mill 1 Real FRF for 32mm end mill
0 Hz 2500 Hz 5000 Hz 7500 Hz
0.00e+00
5.00e-07
-5.00e-07
-1.00e-06
-1.50e-06
Increasing first dominant mode Increases max Vs
FRF of toolholder and tool
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• Special tools to remove fork ends
– Variable Pitch
– Variable Helix
– Reduced flute number
• Tool paths to maintain radial depth of cut and load
Maintaining low ae (left) enables increased apUse toolpaths to maintain a constant ae
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-Multi spindle machine only as good as weakest spindle-Dynamics used to monitor condition and diagnose faults
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High Strength Steel Forging ‐ Dynamics
• Use dynamics to select initial strategy– Process damping is poor, cutting force is high– High feed milling andplunge milling
• Use dynamics to select tooling – Plunge mills and special form finishers
• Use dynamics to tune parameters– Eliminate chatter and optimise productivity
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• Repeatability• Cost Avoidance!• Productivity• Capability• Equipment maintenance
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• Machining is dynamic by nature. Interrupted and/or non-uniform loading due to raw material features.
• Limits are always imposed by design of the “Machining System”, including work piece geometry.
• Adaptive systems have limitations due to their inability to predict and the unavoidable damage to tool or work piece that is left behind.
• Understanding and acceptance of the influence of dynamics in machining process is now at a point that customers recognize value.
• The ideal implementation would be a combination of both predictive techniques combined with smart machining technology, including self-diagnostics.
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Assess
Identify Process Requirements
Document Component Capabilities
Manufacturability
Modal AnalysisFRF TestingArtifacts
ReceptancesTool and Holder
Geometry
Design
Process ParametersWork piece and fixture
GeometryDynamic Behavior
Prediction
Stability AnalysisSLERCSAFEA
Damping techniques
Verify
NC Verification and Optimization
Machine BenchmarkingMachine and Spindle
Modeling.
Tool Path Optimization and Verificationl
Smart Machine SensingPreventive Maint.
FRF DataProcess Monitoring
Machine
Dynamics Future: Impacts all stages of machining process.
Function
Technology
MonitorAdapt
DiagnosePreventive
MaintenanceAutomatic
Characterization.
Adaptive ControlAdaptive BehaviorSmart machine
Sensing.MTConnect
.Available
Now
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• Not just a niche technology.– Directed Dynamics benefit across all types of machine and
throughout the machining process.– Predictive techniques combined with process monitoring will deliver
the most robust and effective solutions.• Proven
– Refinement still needed (predictive models).– Solutions must be more targeted and
accurately implemented.• Dynamic Future
– Off-line predictive capabilities.– Well defined process development.– Use of smart machining monitoring.
• Questions– Sam Turner, [email protected]– Tom Delio, [email protected]
