Performance-based Optimization for Titanium Milling · cutting tools. This technology has been recently applied in milling operations on titanium alloys. The optimization method has

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Performance-based Optimization for Titanium Milling

Xiqun Wang

March 31, 2008

Abstract In the manufacturing industry, especially defense and aerospace, many component designs and characteristics of titanium materials make them expensive to machine. A considerable amount of stock must be removed from the initial form such as forgings, plates, bars, etc. In some instance, as much as 50 to 90% of the primary form’s weight ends up as chips. Maximum machining efficiency for titanium alloys is required to minimize the costs of stock removal and maximize productivity. A performance-based methodology of machining optimization has been developed by TechSolve to optimize machining parameters in order to achieve optimum machining performance of machines and cutting tools. This technology has been recently applied in milling operations on titanium alloys. The optimization method has been validated for a dozen of tool-material combinations in face-milling and end-milling operations. Optimum cutting parameters, speeds and feeds, are derived based on the user requirements of the overall machining performance including surface roughness, cutting forces, material removal rate and tool-life. Applications of the machining optimization system can improve process planning, increase productivity and reduce machining cost. A case study will illustrate the optimization of end milling operations on Ti-6Al-4V parts. The comparison of machining performance between pre-technology and post-technology shows that understanding the machining process leads to productivity improvement by optimizing machining parameters without any capital expenditure. It is also a challenge for machining process planners to select appropriate machining parameters for new titanium alloys. Generally, the selection of machining parameters for tooling material combinations is based on experience, handbooks or static databases. However, since there is little experience and little knowledge about the machinability of the new material, process planners will have great difficulties in the selection of machining parameters and cutting tools. Inappropriate machining parameters may cause high scrap rate, short tool life or even tool failure. It will be helpful for process planners if the vendor of the new material could provide a range of safe machining parameters with which they can start process planning. A standard methodology has been developed by TechSolve to evaluate the machinability of new titanium alloys and recommend starting machining parameters for process planners. A case study will illustrate the evaluation of machinability for the new titanium alloy Ti-5-5-5-3 and process planning of end milling operations to produce a part using the obtained machinability information.


ITA Tit i C f 2008

for Titanium Milling

ITA Titanium Conference 2008

September 24th, 2008

Xiqun Wang, Ph.D.

E-mail: [email protected]

OutlineIntroduction to TechSolveIntroduction to TechSolve

Introduction to Smart Machine Initiative Platform (SMPI)

Technical Difficulties in Titanium Milling

Machining PerformanceMachining Performance


Case Studies

© TechSolve www.techsolve.org

TechSolve’s Mission and Vision

Mission StatementMission StatementTo enable our customers to provide outstanding products and servicesoutstanding products and services.

Vision StatementTo be a vital contributor to the success of the customers and communities To be a vital contributor to the success of the customers and communities we serve and merit continuing commitment from our stakeholders.


Smart Machine Platform InitiativeMissionMission

– Be the framework for the identification, development, and transition of technologies that recognize the goal of “First Part Correct” g g gmanufacturing.

Goal– Bring about the realization of “First Part Correct” manufacturing

capabilities and technologies.

Objective– The development and dissemination of “First Part Correct” technology

for manufacturing systems. This technology will address the specific needs for the pre-process, in-process planning, and execution of discrete part production.


p p

SMPI Technology Thrust Areas

I t lli t

M hi T l M hi T l

Intelligent ProcessPlanning

OnOn--MachineMachineProbingProbing

Machine Tool Machine Tool MetrologyMetrology

Intelligent Intelligent MachiningMachining

Tool Condition Tool Condition MonitoringMonitoring

NetworkNetworkHealth & Health &

MaintenanceMaintenance

gg


Intelligent Process PlanningDefinition: Module in smart machine to optimize machining parameters; virtually simulate machining Definition: Module in smart machine to optimize machining parameters; virtually simulate machining

processes; and generate, verify, and optimize tool paths in order to achieve optimum machining performance in machining operations

Machining Performance Experimental Database

HPM Optimization

Tool Path Generation

12

14

16

18

20

r, kW

6

7

8

9

10

OC

,mm 0. 25

0 0

0.4

0

0.55

Objective Function 0.3

ConstraintRa (μm)ConstraintMR (in3/min) Tool Path Verification & Optimization

0

2

4

6

8

10

0 5000 10000 15000 20000Spindle Speed, rpm

Pow

er

0

1

2

3

4

5

Axi

alD

O

0.15

0.15

0.15

0.2

0.20.25

0.25

0.3

0.3

0.3

0.35

0.35

0.35

0.4

0.4

0.45

0.45

0.45

0.5

0.5

0.5

0.55

Axi

al D

epth

of C

ut (i

n)

0.1

0.15

0.2

0.25

ConstraintFc (lbs)ConstraintTL (min)ObjectiveFunction

Optimum

Handbook

FeasibleRegion

Weighting Factors: CRa = 0.7 CFc = 0.1 CMR = 0.1 CTL = 0.1

Tool Path Verification & Optimization


Machining Performance Constraints

0.2

Cutting Speed (rpm)

1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000

0.05 Recommended

Titanium Metallurgy

α (alpha) and near αLow to medium strength

Specific Cutting Forces

hard

– Low to medium strength– Example: Ti-6-2-4-2

β ( l h b t )α-β (alpha-beta)– Medium to high strength

Example: Ti 6 4 Ti‐6‐2‐4‐2 Ti‐6‐4 Ti‐17 Ti‐5‐5‐5‐3– Example: Ti-6-4

β (beta) and near βHi h t th t i t di t

Ti‐6‐2‐4‐2 Ti‐6‐4 Ti‐17 Ti‐5‐5‐5‐3easy

– High strength up to intermediate temperature levels

– Example: Ti-17, Ti-5-5-5-3


a p e , 5 5 5 3

Difficulties in Titanium Milling

Titanium is a poor conductor of heat

Titanium has a high tendency for chemical reactions

The modulus of elasticity of titanium is low compared to steel The modulus of elasticity of titanium is low compared to steel and aluminum

Work hardening characteristics


Titanium Milling


Overall Machining Performance

The overall machining performance is a function of multiple interrelated criteria

Cutting Forces / Surface

M hi i

Cutting Power Roughness

Machining Performance

Tool Wear / Tool Life

Material Removal Rate


Recommended Machining Parameters

MaterialEnd Milling (Slotting) End Milling (Peripheral)

Axial Depth of Cut

Cutting Speed Feed

(inch/tooth)

Radial Depth of Cut

Cutting Speed Feed

(inch/tooth)(inches) (fpm) (inch/tooth) (inches) (fpm) (inch/tooth)

Ti-6-4Ti 6 2 4 2

0.250 75 0.003 0.250 125 0.0030.125 100 0.004 0.125 150 0.004

Ti-6-2-4-2 0.050 125 0.005 0.050 190 0.0050.015 165 0.006 0.015 225 0.0060.250 60 0.001 0.250 100 0.0020 125 75 0 002 0 125 125 0 003

Ti-170.125 75 0.002 0.125 125 0.0030.050 90 0.003 0.050 165 0.0040.015 115 0.004 0.015 200 0.0050 250 50 0 001 0 250 75 0 001

Ti-5553

0.250 50 0.001 0.250 75 0.0010.125 60 0.002 0.125 100 0.0020.050 90 0.003 0.050 140 0.0030 015 115 0 004 0 015 190 0 004


0.015 115 0.004 0.015 190 0.004

(Reference: Titanium Milling Guide, TechSolve)

Optimization of Ti MillingUnderstanding the process leads to 3X productivity improvement without Understanding the process leads to 3X productivity improvement without any capital expenditure

0 3Process Parameters

0.25

0.3Handbook Optimized

Spindle Speed (rpm): 2,000 1,600Axial Depth of Cut (mm): 1.0 3.8

ConstraintRa (μm)ConstraintFc (lbs)ConstraintTL ( i )

0.2

OC

(in)

Optimum

Radial Depth of Cut (mm): 12.7 12.7Feed Rate (mm/tooth): 0.20 0.20Metal Removal Rate(cm3/minute): 20 3 61 8

TL (min)ConstraintMR (in3/min)ObjectiveFunction

0.15Axi

al D

O

Tooling Conditions:12.7 mm, 4-Flute Solid Carbide Endmill

FeasibleRegion

(cm3/minute): 20.3 61.8

0.05

0.1 Shrink Fit Tool HolderMakino V55

Max Spindle Speed: 20,000 rpmMax Power: 20 kWatt

HandbookRecommended


1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000Cutting Speed (rpm)

Case Study


Material: Ti-6Al-4V

Third Wave Systems AdvantEdgeTM Production Module 3D

Tool Path OptimizationThird Wave Systems AdvantEdgeTM Production Module 3D


Tool Path Optimization

Baseline Optimized Saving104 min 38 min 66 min 63 5%


104 min 38 min 66 min 63.5%

Thank YouThank You


Reference: “Titanium Milling Guide” by TechSolve, Inc., 2007

Performance-based Optimization for Titanium Milling · cutting tools. This technology has been recently applied in milling operations on titanium alloys. The optimization method has

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