DIAGNOSTICS IN INDUSTRIAL REACTORS
This presentation is the property of its rightful owner.
Sponsored Links
1 / 35

DIAGNOSTICS IN INDUSTRIAL REACTORS PowerPoint PPT Presentation


  • 80 Views
  • Uploaded on
  • Presentation posted in: General

DIAGNOSTICS IN INDUSTRIAL REACTORS. WHY DIAGNOSTICS (sensors) ? Structure of a semiconductor production plant Financial aspect Trend and consequence for plasma diagnostics PLASMA DIAGNOSTIC IN PRODUCTION Role of a sensor in a system Different levels of warning

Download Presentation

DIAGNOSTICS IN INDUSTRIAL REACTORS

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Diagnostics in industrial reactors

DIAGNOSTICS IN INDUSTRIAL REACTORS

WHY DIAGNOSTICS (sensors) ?

Structure of a semiconductor production plant

Financial aspect

Trend and consequence for plasma diagnostics

PLASMA DIAGNOSTIC IN PRODUCTION

Role of a sensor in a system

Different levels of warning

NEEDS AND TRENDS IN THE EQUIPMENT INDUSTRY

Today, problems of scale upLonger term, total feedback control

Self bias and its meaningExamples of today’s stupidity

Loss of the viewing angleTotal automatic control

Relevance of measurement System self teaching Variations reactor to reactor

A new problem : electrostatics

SUMMARY AND CONCLUSIONS


Diagnostics in industrial reactors

oven

oven

control

control

control

oven

R

R

R

Yellow room for

PHOTOLITHOGRAPHY

Resist spinning

Soft bake

Exposure

etc…..

PVD

R

oven

R

R

PECVD

ETCH

R

R

R

R

ETCH

R

PECVD

R

WET ETCH

ETCH

R

R

R

PECVD

WET ETCH

ETCH

R

R

R

R

WET DEVELOPER

ETCH

R

R

R

PVD

R

WET CLEAN

ETCH

R

R

R

STORAGE AND TRANSFER

PVD

R

Possible architecture of a plant

plasmas


Diagnostics in industrial reactors

control

control

control

oven

R

R

R

oven

oven

AGV

Yellow room for

PHOTOLITHOGRAPHY

Resist spinning

Soft bake

Exposure

etc…..

PVD

R

oven

R

R

PECVD

ETCH

R

R

R

R

ETCH

R

PECVD

R

WET ETCH

ETCH

R

R

R

PECVD

WET ETCH

ETCH

R

R

R

R

WET DEVELOPER

ETCH

R

R

R

PVD

R

WET CLEAN

ETCH

R

R

R

STORAGE AND TRANSFER

PVD

R

Example of a fraction of process flow


Diagnostics in industrial reactors

Unit selling price

Price decay

a. u.

Return on investment

0

Factory output

100 %

reject

PRODUCTION

YIELD

Ramp up

Delivery

time

0

1 year

time

Financial aspect

Investment from 0.5 to 1 billion US $ !


Diagnostics in industrial reactors

Unit selling price

Price decay

a. u.

Return on investment

0

Factory output

100 %

reject

PRODUCTION

YIELD

Ramp up

Delivery

time

0

1 year

time

Financial aspect


Diagnostics in industrial reactors

TRENDS IN THE ELECTRONIC INDUSTRY

Investment isGIGANTIC

Process is veryCOMPLEX

Main keys to success :

DELAY(very short)

YIELD(very high)

Consequences on equipment choice :

NO RISK- proven technique preferred

- long delay for introducing innovation (probation phase)

- simple and stupid far better than sophistication

CONSISTANCY MORE IMPORTANT THAN PERFORMANCE

- production scale up based on “copy and paste”

- process and equipment should work in “robust” zones

- equipment : long MTBF and short MTTR

MTBF = Mean Time Between Failure, MTTR = Mean Time To Repair


Diagnostics in industrial reactors

PLASMA DIAGNOSTIC IN PRODUCTION

Main consequences for diagnostic & sensors attached to the plasma production tools

RELIABILITY :- the sensor must be a source of improved reliability

- the sensor should not interfere with the process

- sensor failure should not jeopardise the benefit related to the presence of the sensor.

- simple and stupid is always a winner

- smart and complex sent back to development

PRODUCTION WORTHY

- ideally the sensor should give an early warning that the process is drifting away from its optimum before the product is out of its specifications.

- however false alarms are strictly forbidden.

- the understanding of physics is irrelevant, what counts is that the sensor sensitivity and its “correlation” with process “quality”.


Diagnostics in industrial reactors

PLASMA DIAGNOSTIC IN PRODUCTION

WARNING

This paper is (on purpose) provocative to the scientific community.

Hence what is stressed is what scientist are not already familiar with.

PLEASE REMEMBER

It needs sometimes far more genius to implement something “stupid and simple” instead of a sophisticated and complex measurement.

Speaking of reliability or yield, it generally takes as much work (and creativity) to go from 50 to 98 % than to go from 98 to 99 %.

Unfortunately the business margins are in the last % points !!


Diagnostics in industrial reactors

THE 3 ROLES AND LOCATIONS OF A SENSOR

PLASMA

SENSOR

To next process

1) REMOTE POST PROCESS ANALYSIS

Not a real plasma sensor, analyses the result

Touching the substrate is usually forbidden

Optical technique (reflectometry, ellipsometry)

Still very effective if fast and reliable

Allow s an early stop of defective substrates

Can detect process drift if sensitive enough

Gives only one value (or one set of value) per run.


Diagnostics in industrial reactors

THE 3 ROLES AND LOCATIONS OF A SENSOR

PLASMA

SENSOR

2) REAL TIME CONTROL OF A PARAMETER

Measures one process parameter.

Needs not to perturb the process

(watch out for window or probe perturbation)

Possibly analyses the substrate (reflectometry)

Possibly analyses the plasma (probe, RF voltage, etc…)

Possibly analyses the gas phase (pressure, QMS, etc..)

Possibly analyses a combination (OES, self bias, etc…)

Can detect process drift if sensitive enough

Trade off needed between number of data and memory size

Gives a full time sequence of measurement per run


Diagnostics in industrial reactors

THE 3 ROLES AND LOCATIONS OF A SENSOR

Input parameter

(End point detection is part of this case)

Feed back

controller

PLASMA

SENSOR

3) FEED BACK CONTROLLING SENSOR

Similar as case 2) but also :

The sensor is used to stabilise the process

At least one process input parameter is automatically varied

to keep constant the measurement of the sensor.

Some examples :

Match box tuning (Reflected RF / 2 setting of match box capacitors)

Pressure control (pressure / throttle valve)

The offset of the sensor (departure from set point) can be recorded as process data


Diagnostics in industrial reactors

Analogic feedback

ELECTRONIC PART

SENSOR

AMPLIFIER

SIGNAL PROCESSING

COMPARISON

SAMPLING

Digital feedback

Comparison to

thresholds

PREFERABLY DATA COMPRESSION

WARNING

DATA PROCESSING

CENTRAL

DATA

STORAGE

to plant CPU

TEMPORARY STORAGE

SYSTEM PROCESSOR

WHAT TO DO WITH THE DATA ?


Diagnostics in industrial reactors

LEVELS OF WARNING FROM A SENSOR

A process controlling sensor should have several levels of warning depending of the departure from the set point

SENSOR

OUTPUT

IMMEDIATE STOP

Defective system

Stop at the

end of the run

Product in

process are

not qualified

Product still OK

Warning

message

System

check-up

to be planned

as soon as possible

OK

Central value


Diagnostics in industrial reactors

Gas flow

offset

Set point

Delay for repair

time

Everything is OK

Early warning, production is still OK, maintenance to be scheduled

Production is out of specification. Substrates to be rejected

EXAMPLE : MFC DRIFT

Mass Flow Controllers, when handling highly reactive gases and vapours, are among the most sensitive subsystems in plasma processor. Usually they do not break, they drift. An erroneous gas mixture can bring thin films out of specifications (leaky insulator, wrong taper).


Diagnostics in industrial reactors

controlled temperature

Calibrated narrow pipe

Pcal

MFC

MFC

MFC

GAS 1

Flow = Cste Pcal

2

GAS 2

GAS 3

IMPROVING PROCESS SAFETY :double checking


Diagnostics in industrial reactors

NEED AND TRENDS

IN THE EQUIPMENT INDUSTRY

Note : the point of view expressed here is mostly related to the Display industry, however some of the long term trends are also valid for the semiconductor industry.

SHORT TERM

Cost issue :- Added value per unit surface, sensor cost

Basic questions :- Interpretation of a sensor drift

Substrate size issue :- Optical measurement and viewing angle

- Self bias (meaning of the measurement)

Reactor to reactor :- difference between 2 reactors

LONG TERM

Feed back control :- Status of today

- Some possible improvements

- Long term future

Sensor research :- Relation to process results

- Multi-step processes

- Data compression


Diagnostics in industrial reactors

REQUIRED CLEANINESS

TYPICAL PROCESS TIME

(sec.)

Window

pane

(particle/m²)

1000

Solar

pannel

10000

100

AMLCD

1000

IC

10

Disk

storage

100

1

(Yen/cm²)

1

0.1

10

100

(m²)

0.01

0.1

1

10

SUBSTRATE UNIT SIZE

ADDED VALUE PER STEP

SENSORS : Cost issue


Diagnostics in industrial reactors

SENSORS : Cost issue

The Display Industry will not grow unless it learns how to produce at low cost, same goes for the solar cell industry.

The Semiconductor Industry is gradually becoming a low margin business (pressure from far east countries).

Equipment suppliers are being transmitted the cost squeezing pressure : system “cost of ownership” shall drop down

COO = COST PER UNIT PROCESS IN PRODUCTION

= ( Yearly amortisation / Yearly throughput)

+ gasses + electricity + water + other fluids

+ man power + maintenance + floor space rental

+ yield decay due to this system

The investment cost of a system is not related to the weight or the steel work, but is rather related to the complexity of the system (electronic and electric, interlocks, software, troubleshooting, etc…). Sensors can make a definitive impact on system complexity. Stupid & simple more than ever the best choice !


Diagnostics in industrial reactors

constant

sensor

maximum

variation

Marginal

Process parameter 2

OK

BAD

Process parameter 1

RELATIONS PROCESS-SENSOR

The ideal sensor gives a signal which varies with the maximum sensitivity with process quality. The relation can be experimentally established by optimised orthogonal planning (work intensive). In the attached figure, the process parameter space is only 2-d. It is usually much higher dimension. Example of process parameters :

- RF power, match box setting

- Pressure, gas flow and composition

- Temperature

Attention “quality” can be also a multiple parameter concept.

There is no need to understand the detail of the physics in the relation between sensor signal and process quality. It is more important not to neglect “hidden” parameters (purity, substrate history, etc.).

the process “quality” is shown in the colour scale


Diagnostics in industrial reactors

Substrate

diagonal

in meter

950

x

1100

1.4

FINAL?

3rd generation

1.2

700

x

850

650

x

750

1

550

x

650

2nd generation

0.8

1st generation

400

x

500

350

x

450

0.6

300

x

300

0.4

largest wafer

1980

1990

2000

Years

ISSUES RELATED TO SUBSTRATE SIZE

Trend in the Display Industry


Diagnostics in industrial reactors

ISSUES RELATED TO SUBSTRATE SIZE

self bias : sensitivity and interpretation (1)

DC Voltage

measurement

RF filter

RF PLASMA

Matching

network

Self bias: good example of “stupid & simple”

- Easy to implement

- External to the process zone

- Varies with “some” process parameters

Self bias is universally used in RF plasmas

Still used for probing display processing

What is the meaning of self bias ?

RF

GENERATOR


Diagnostics in industrial reactors

ISSUES RELATED TO SUBSTRATE SIZE

self bias : sensitivity and interpretation (2)

VRF

VRF

Vbias

SHEATH (electrode)

C  Selectrode

SHEATH (electrode)

SHEATH (g.)

Vplasma

Vplasma

SHEATH (ground)

SHEATH (ground)

C  Sground

Equivalent circuit

in blue : RF component

in cyan : DC component

SHEATH

Voltage

Vplasma

average

Ions+

Vplasma

electrons


Diagnostics in industrial reactors

VRF

Vbias

Se

e

Ve

Ve

Vplasma

Vplasma

g

Vg

Vg

Sg

Ve VeSgn

Vg VgSe

in blue : RF component

in cyan : DC component

withn = 1 / (1-)

(practically n = 1.6 - 2.2)

ISSUES RELATED TO SUBSTRATE SIZE

self bias : sensitivity and interpretation (3)

Plasma sheath = vacuum capacitance = equivalent thickness  with   V

Sheath rectification implies that :

Ve ½ Ve(peak to peak RF voltage)

Vg ½ Vg

Constant RF current  CeVe =  CgVg

henceSeVe / Ve = SgVg / Vg


Diagnostics in industrial reactors

1

1m² glass

1 m² GLASS

0.5

Vbias/(½VRF)

wafers

0

-0.5

1.5

1

0

0.5

R or (Se / Sg)

ISSUES RELATED TO SUBSTRATE SIZE

self bias : sensitivity and interpretation (4)

Vbias = Vg - Ve = ½ (Ve - Vg) = ½ VRF (1-Rn) / (1+Rn)

withR = Se/Sg (relative electrode surface ratio)

WAFER

For R 1 , Vbias is a function of both VRF and R the surface ratio.

Before is was just ½ VRF

Vbias becomes a less “simple” tool


Diagnostics in industrial reactors

ISSUES RELATED TO SUBSTRATE SIZE

self bias : sensitivity and interpretation (5)

Equivalent circuit

RF

Plasma

Dust grain below

the substrate

The series capacitance of the substrate changes the sheath capacitance of the ground, hence it modifies the equivalent surface ratio. If a dust grain is below the substrate, the substrate capacitance is modified, a change is seen in Vbias. If a Vbias drift is observed, shall we change the RF generator for calibration or open the reactor for cleaning?


Diagnostics in industrial reactors

ISSUES RELATED TO SUBSTRATE SIZE

self bias : sensitivity and interpretation (6)

Vbias as a plasma monitoring tool is so popular that people are still using it in the RIE etching of insulating substrate.

Question : what is the meaning of such a measurement when all the electrode is protected from direct exposure to the plasma to avoid sputtering of the metal?

Sacrificial

quartz liners

RIE ETCH PLASMA

to Vbias

measurement

FILTER

RF

The measured signal is due to the faint plasma which penetrates in the electrode/ground gap. One may wander about effects such as geometry, thermal expansion, surface oxidation, electronegative gases, etc.. Again it is clear that self bias gives an information with value (it is even used as an end point), but the open question is how to interpret signal level variations, drift, etc..


Diagnostics in industrial reactors

Holes in the electrode impossible or very difficult

< 2°

1 cm

1 m

Line filter

Sensor

ISSUES RELATED TO SUBSTRATE SIZE

Viewing angle

The plasma gap cannot be varied : the process which was qualified with smaller substrate must be preserved

2 severe problems :- incidence angle is very small, reflectometry or ellipsometry are not at their best. Technology to be revisited.

-the optical aperture is very small, non coherent sources are difficult to use. This optical etendue problem is also an issue for local analysis of the plasma spontaneous emission.

During process, part of the analysed light emission is reflected on walls. The reflection coefficient is modulated by the film thickness variations. The signal is found to vary while the plasma is stable. This oscillation would have some value if the reflection angle was well defined, but the solid angle would need to be very small and the signal would be very weak.


Diagnostics in industrial reactors

REACTOR TO REACTOR VARIATIONS

KAI : Parallel processing PECVD production system (20 identical reactors in parallel).

Ideally they should provide identical results. In reality they give an excellent +/- 3% reactor to reactor thickness variation for SiN deposition.

Note that this level of variation is of the order of the the uncertainty of the sensors attached to each reactor.

However after very careful analysis and cross-correlation we have identified, for this specific SiN process, what is responsible of the 3% box to box average thickness variation :

- about 1% is due to gas flow variation (well related to the accuracy of our gas flow divider)

- about 1% is related to the RF generator calibration accuracy (made on a 50 resistive load)

-about 1% is related to the reactor capacitance fluctuation (match box losses)


Diagnostics in industrial reactors

RF

Match Box

Large resonance

RF current

REACTOR TO REACTOR VARIATIONS

RF power distribution

OHMIC LOSSES IN

MATCH BOX

& FEED THROUGH

PLASMA

50 


Diagnostics in industrial reactors

Match Box

in : RF reflected power

out : capacitor setting

RF generator

in : RF power

out : gain setting

M B

MFC

in : thermal differential

out : valve setting

Generator

Temperature

in : thermocouple

out : heater current

Pressure

in : capacitance gauge

out : valve setting

FEED BACK CONTROL IN PROCESS SYSTEMS

Classical feed-back sub-system units found today in most standard process equipment


Diagnostics in industrial reactors

FEED BACK : present status

These independent feedback loops are actually interacting via the plasma. In some cases, this interaction can result into long relaxation time , even instability

Example : Pressure regulation versus match box

Reflected RF

Process exhaust flow

(for one given

match box setting)

0

0

Effective RF power

Pressure

Effective

RF power

Exhaust

gas flow

Process

pressure

Plasma

impedance

Reflected

RF power

Match box

adjustment

Both pressure control and match box setting are coupled via the plasma response. If the gain of the feedback loops is too large and for some parameter coupling configuration, the ensemble can ring and offer very poor control. All this can be stabilised by proper setting of the PID.


Diagnostics in industrial reactors

Vacuum

Gas in

Plasma “on”

Hot plate

heat loss

gas cond.

plasma

power

PLASMA

radiative

0

Target temperature

Temperature

Standard

feedback

Heater

power

FEEDBACK

SYSTEM

Improved method

FEED BACK : present status


Diagnostics in industrial reactors

SENSORS

computer

DRIVERS

LONG TERM : Multiple feedback

Modern fighter planes,

Most advanced robots

are driven by multiple feedback from a simple central unit

The central unit computer must be a fast real time unit. Such units are today available on the market (originating mostly from the military market)


Diagnostics in industrial reactors

Input

parameters

Sensors &

diagnostics

PROCESS

Controlled

parameters

Real time

computer

Process quality rating

LONG TERM : Multiple feedback

The computer establishes the process result as a combination of sensor measurement, then detect the differential from optimum, finally it calculates the variations of all control parameter settings in order to bring the process as close as possible to its optimum process point.


Diagnostics in industrial reactors

PROCESS

LONG TERM : Multiple feedback

Necessary conditions for multiple feedback implementation

- Drop the individual sensor + feedback concept.

- Relation process quality / sensor response must be known

- Sensors must be absolutely reliable

One finds here again the main issues related to sensor/diagnostics in industrial environment

Such a system can define its best response by self-learning : The response of all process component is analysed for a step like perturbation of all input parameters, including the controlled parameters. The system response is locally linearized and the response calculation is similar to a matrix inversion logic.


  • Login