Volumetric Verification as a first step to MT uncertainty evaluation · 2014-11-06 · Department...

Department of Design and Manufacturing Engineering

Dr. José A. Albajez

Traceable In-process dimensional Measurement for machine tools (TIM) Workshop at NPL – 05/11/2014

VOLUMETRIC VERIFICATION AS A FIRST STEP TO MACHINE TOOL

UNCERTAINTY EVALUATION

JJ. Aguilar, J. Santolaria, S. Aguado, D. Samper

1.- INTRODUCTION


Machine Tool

Manufacturing capabilities

Metrological capabilities

Workpiece

Manufacturing Tolerances

Measuring uncertainties Improvement:

- Prediction - Correction

Geometric/ Kinematic Errors

Thermal Effects Dynamic Errors

1.- INTRODUCTION


Machine Tool

Manufacturing capabilities


Source:.Virtual Machine Tool. Y. Altintas, C. Brecher, M. Weck, S. Witt. Annals of the CIRP. v54, pp 115-138. 2005.

Virtual Machine Tool

1.- INTRODUCTION


Machine Tool


Workpiece

Measuring uncertainties

Virtual Coordinate Measuring Machine

Source: The “Virtual CMM” a software tool for uncertainty evaluation – practical application in an accredited calibration lab. M.Trenk, M. Franke, H. Schwenke. ASPE. 2004.

Traditional verification techniques used in small and medium machines are limited by their range of

measurement and measurement time employed.

long range machines: new techniques based on the use of laser measurement systems by tracking technique.

Laser Tracer / Laser Tracker

1.- INTRODUCTION


Volumetric verification consists of minimising the difference between real points measured with Laser Tracker, and nominal points introduced in the numerical

control (NC) through the Machine Tool kinematic model. Nonlinear optimization:

2. Volumetric Verification: Operating Principle


3. Solution Developed: Principle of work

Development of new solution in long range machine tool allowing a qualitative and quantitative progress in the accuracy achievable on current machine tool. Through the use of a commercial laser tracker, as a long range measurement system, using

techniques of volumetric resolution.

Volumetric verification is based on the minimization of the volumetric error of the machine tool by an intensive process of identification parameters based on the

kinematic model of the machine tool.


LASER TRACKER

• One of the advantages of the laser tracker as measurement system is the equipment flexibility. This is not a dedicated, but, versatile equipment used in many

applications.



• Another advantage of the laser tracker in the verification of machine tool is the reduction of needed time.



SOFTWARE DEVELOPED

Machine Tool Kinematic Model Generator

CNC Generator Module Identification Strategy

Generation Module

Identification Module Results’ Representation

Module Compensation Module

3. Solution Developed: Scheme of the software


Algorithms that discretize the workspace of the machine

depending on errors to characterize creating different types of mesh.

The algorithm creates a NC program file depending on the control version. As well as downtime between points to measure.

3. Solution Developed: NC Code Generator Module


3. Solution Developed: Measurement and extraction

Automatically capture points Number of points to measure

Samples per point Stabilization time

….

Capture software Measurement Technique used

Measurement data analysis Extraction of measurement points *.txt


3. Solution Developed: Kinematic model generator

Generated the kinematic model of any machine tool with N axis, both linear and rotary. It takes into account the position of the axis relative to the machine base and

the incorporation of the LT in the kinematic model.

Kinematic Scheme

Machine Configuration

Equation of Movement


General information of the verification test

Optimization information Errors to characterize Approximation functions to use: - Simple Polynomials - Legendre Polynomials - Chebyshev Polynomials - Fourier Series

Offsets to optimize

3. Solution Developed: Identification Strategy


3. Solution Developed: Compensation Module

Original CNC program

Program CNC affected by

approximation functions

Algorithms developed to generate the new corrected NC code using the optimized error fuctions from the verification process.


3. Solution Developed: Representation of results

Average maximum and minimum volumetric error in each iteration

Histogram errors previous to volumetric verification

Histogram errors after volumetric verification compensation


3. Solution Developed: Representation of results

Error map before compensation Error map after compensation


3. Solution Developed: Identification Process

Identification strategy is defined by:

• Machine tool

Structural configuration of the machine tool, number and type of axis.

Available space to measure (visibility, objects around …)

Discretization of the workspace of the machine tool (mesh of points, cloud of points, diagonals...)

Non-geometrical errors (temperature, heating time, backlash error,…)

• Measurement system used

Characteristic of the measurement system.

Number of laser tracker used.

Laser tracker positioning around the machine.

Laser tracker measurement configuration (strategy, samples per point, frequency, etc).



• Improvement of data capture

Auto-calibration of laser tracker positions.

Multilateration (mathematical modelling).

• Identification process

Objective function.

Polynomial functions to used as regression functions.

Optimization in phases (type of axis, type of error, phases of measurement, etc)

Feedback of optimization.

Convergence criteria.

• Additional parameters to optimize

Laser tracker position.

Offsets


NOMINAL POINTS

OPTIMIZATION

OPTIMIZATION PARAMETERS

OPTIMIZATION

POINTS

MEASURED POINTS

KINEMATIC MODEL

CONVERGENCE CRITERIA

CHARACTERIZATION FUNCTIONS

+ -


All these parameters has been considered and studied in order to determine the best identification strategy for each machine tool and verification test.


{EXX (a0..am) ,EYX (b0..bm),EZX (c0..cm),EAX (d0..dm),EBX (e0..em), ECX (f0..fm),EAO,EBO,ECO}n n=1…i,

Apromation Function;

Time of data capture

Tem

per

atu

ra º

C

4. Additional works carry out

• Protocol as the preliminary phase of the volumetric verification of geometric errors:

Errors from the measurement system used.

No geometrical errors from the machine tool.

•Bachklash errors

•Tracking error

• Repeatability at a point

Errors due to thermal variations.

Point



• Studies about multilateration and position auto-calibration of laser trackers:

Mathematic algorithms developed based on non-lineal optimization procedures (trilateration and tetralateration).

Geometrical and analytical resolution of multilateration.

Influence of spatial angle between laser trackers

Influence of ratio between radial and angular laser tracker noise.

Best laser tracker distribution.

Spatial angle between LT2 and LT3 (from 10º to 340º)

Incr

ease

in h

eigh

t f

rom

2

00

0 t

o 0

(m

m)

of

LT1



• Coefficients to predict multilateration scope previous to measurement:

Multilateration technique to be used in relation with laser tracker measurement characteristic MCLT and laser tracker positioning β.

3

909090 323121 LTLTLTLTLTLT

6

var

1)())((2

)(_)(_

emdradanngularsen

mmderrorradialmerrorradialMC

error

cteLT


• Laser tracker positioning and characteristic in multilateration scope :

Relationship between laser tracker measurement characteristic MCLT and laser tracker positioning β.

5. Results of machine tool verifications

The application developed has been validated:

Re-measurement of verification points.

Measuring a series of control points, not used in verification, before and after compensation.

Comparing accuracy of the control points before and after verification using a traditional interferometer.



The application developed has been validated:

Re-measurement of verification points.

Measuring a series of control points, not used in verification, before and after compensation.

Comparing accuracy of control points before and after verification using a traditional interferometer.

Optimization Process

Laser

Tracker

Max. Initial

E.M (µm)

A. Initial E.M

(µm)

Min. Initial E.M

(µm)

Leica LT 600 76 31.5 7

Laser

Tracker

Max. Final E.M

(µm)

A. Final E.M

(µm)

Min. Final E.M

(µm)

Residual Error

(%)

Leica LT 600 33.1 14.7 2.5 46,60%

Control Points

Laser

Tracker

Max. Final E.M

(µm)

A. Final E.M

(µm)

Min. Final E.M

(µm)

Residual Error

(%)

Leica LT 600 27,5 13,7 2,3 43.5%



Soraluce FX 14000

Working volume: 4,5 m x 1,6 m x 1 m

Positioning, straightness, squareness,

pitch, yaw and roll errors.

(21 error parameters)

Zayer Tebas 5000

Working volume: 5.0 m x 2.0 m x 0.45 m

Positioning, straightness, squareness,

pitch, yaw and roll errors.

(21 error parameters)




Example with Active Target


Soraluce SV 6000

Working volume:

2.4m x 1.0m x 0.6m

Positioning, straightness, squareness, pitch, yaw and roll errors. (21 error parameters)



First verification tests using multilateration have been already realized.

Due to machine tool configuration, the LTs positioning create an angle β≈ 60º.


6. Final Considerations

- Monte Carlo simulations to predict geometrical uncertainty.

- Axis redundancy: uncertainty is path dependent.

- Only use of linear axes?

- Metrology modules in CAM software: STEP-NC?

- ISO 14253-2

- The Best Measuring Capability (BMC) is the least possible uncertainty of measurement achievable.

- PUMA method: Procedure for Uncertainty MAnagement)



Acknowledgments: - PSE ALEXANDRIA- Development of techniques and methodologies for damage inspection and dimensional metrology (Pss-020000-2009-27-hiparco) - TRACE. Long range dimensional metrology: development of new procedures for measuring and calibration. 2010. - DICON: Development of new advanced systems of Dimensional Control in manufacturing processes for high impact sectors (INNPACTO BOE-A-2011-5824).

Department of Design and Manufacturing Engineering

Dr. José A. Albajez


THANK YOU FOR YOUR ATTENTION

JJ. Aguilar, J. Santolaria, S. Aguado, D. Samper

Volumetric Verification as a first step to MT uncertainty evaluation · 2014-11-06 · Department...

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