Motivation and approach for predictable high - ISETC · Motivation and approach for predictable high ... described in the company’s Annual Report on Form 10-K for the year ended

Copyright © 2010 SunPower Corporation. All rights reserved.

Motivation and approach for predictable high performance of PV systems

International Solar Energy Technology Conference

Doug Rose, SunPower Corporation

October 20, 2010

© 2010 SunPower Corp.

Acknowledgments

Many people at SunPower, with particular recognition of Dave DeGraaff and Ben Bourne.

This material is based in part upon work supported by the Department of Energy under Award Number DE-FC36-07GO17043

2

For additional related information see:

Doug Rose, Oliver Koehler, Ben Bourne, David Kavulak, Lauren Nelson, High-confidence prediction of energy production FROM High-efficiency photovoltaic systems, 25th European Photovoltaic Solar Energy Conference, Valencia, Spain, Sept. 7, 2010

D. DeGraaff, S. Caldwell, R. Lacerda, G. Bunea, A. Terao, D. Rose, “Qualification, Manufacturing, and Reliability Testing Methodologies for Deploying High-Reliability Solar Modules,” 25th European Photovoltaic Solar Energy Conference, Valencia, Spain, Sept. 7, 2010


Safe Harbor Statement

3

This presentation contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995.

Forward-looking statements are statements that do not represent historical facts and may be based on underlying assumptions.

SunPower uses words and phrases such as “may,” “will,” “should,” “could,” “would,” “expect,” “plan,” “anticipate,” “believe,” “estimate,”

“predict,” “potential,” “continue” and similar words and phrases to identify forward-looking statements in this presentation, including

forward-looking statements regarding: (a) plans and expectations regarding future financial results, operating results, liquidity, capital

expenditure and business strategies, (b) management’s plans and objectives for future operations, (c) the company’s projected costs

and cost reduction roadmap, (d) forecasted demand growth, and projected bookings and pipelines, (e) construction, completion,

ability to obtain financing and revenue recognition timing, (f) growth in dealer partners, (g) product development and competitive

position, (h) manufacturing ramp plan and scalability, (i) future government award funding, (j) future solar and traditional electricity

rates and cost savings of our systems, (k) trends and growth in the solar industry, and (l) the success and benefits of our joint ventures

and partnerships. Such forward-looking statements are based on information available to the company as of the date of this

presentation and involve a number of risks and uncertainties, some beyond the company’s control, that could cause actual results to

differ materially from those anticipated by these forward-looking statements, including risks and uncertainties such as: (i) potential

difficulties associated with operating the joint venture with AUO and integrating the SunRay business, and the company’s ability to

achieve the anticipated synergies and benefits from these transactions; (ii) the company’s ability to obtain and maintain an adequate

supply of raw materials, components, and solar panels, as well as the price it pays for such items; (iii) general business and economic

conditions, including seasonality of the industry; (iv) growth trends in the solar power industry; (v) the continuation of governmental

and related economic incentives promoting the use of solar power; (vi) the significant investment required to construct power plants

and the company’s ability to sell or otherwise monetize power plants; (vii) the improved availability of financing arrangements for the

company’s customers; (viii) construction difficulties or potential delays, including permitting and transmission access and upgrades;

(ix) Increasing competition in the industry and lower ASPs; (x) the joint venture’s ability to ramp new production lines in Fab 3 and the

company’s ability to realize expected manufacturing efficiencies; (xi) manufacturing difficulties that could arise; (xii) the success of the

company’s ongoing R&D efforts and the acceptance of the company’s new products and services; (xiii) the company’s international

operations; (xiv) the company’s liquidity, substantial indebtedness, and its ability to obtain additional financing; (xv) the company’s

ability to protect its intellectual property; (xvi) evolving regional permitting, financing, grid interconnection, technical, and other customer

or regulatory requirements; (xvii) possible impairment of goodwill; (xviii) possible consolidation of AUO SunPower; and (xix) other risks

described in the company’s Annual Report on Form 10-K for the year ended January 3, 2010 and Quarterly Report on Form 10-Q for

the quarter ended July 4, 2010, and other filings with the Securities and Exchange Commission. These forward-looking statements

should not be relied upon as representing the company's views as of any subsequent date, and the company is under no obligation to,

and expressly disclaims any responsibility to, update or alter its forward-looking statements, whether as a result of new information,

future events or otherwise.

SunPower

>1 GW solar PV deployed 2009 revenue of $1.5B

4

Commercial Power PlantsResidential

5,000+ Employees; 100% solar

Current production capacity > 600MW

> 1000 dealers and growing rapidly

4+ GW power plant pipeline


5

Trackers

SunPower Products (examples)

Roof top and roof integrated solutions

225 W 318 W

Panels

> 22% Efficiency

SunPower Solar Cell


Highest efficiency

mass-produced

modules in the world

Power Plants

Monitoring

6

Solar PV Power Plants Are Cost Competitive

0 50 75 100 150 200 250 300 350 400

Levelized Cost ($/MWh)

Renewables

Conventional

$86 - 192

$119 - 194

$65 - 110

$231- 254

$67-96

Gas Peaking

Gas Combined

Cycle

Wind

Solar Thermal

Solar PV

LCOE by Resource $/MWh: 2010 - 2013

Prices include federal incentives

Source: Lazard Capital Markets 6/2010


Learning Curves

Silicon is keeping up (Trina, a leading Chinese Si company, selected due to readily-available cost data)

– c-Si market share in 2010 is ~84%

Note: Value of typical c-Si module is > value of typical thin film module and value of high efficiency cSi value > value of standard efficiency c-Si modules

7

0.70

7.00

70.00

10 100 1000 10000 100000

$/W

Cumulative Volume (MW)

Industry PRICE

Trina c-Si Price

Trina c-Si Cost

First Solar Price

First Solar cost

1.00

Poly-silicon

shortage


Higher Efficiency → Lower System Costs

8

ConventionalSunPower

PanelPanel

BOSBOS

InstallationInstallation

Fixed Costs

Fixed Costs

Co

sts

/Wa

tt

Value of efficiency

9


- Lowers area-related costs

Reduced materials costs– Less module and system area

Reduced installation costs

- Lowers $/W projects costs

For area-constrained projects, it allows more Watts for the project

– Reduces $/W fixed costs (e.g., sales, design, permitting, connection, etc.)

across more watts

For non-area-constrained, it can still give lower fixed costs by allowing optimum selection of mounting location and reduced site preparation

- Gives more W (and additional kWh with tracking), so higher project NPV

- Provides higher return with simple tracking

Reduced shipping costs (module and BOS)

10

Tracking

Mid-to-high-efficiency modules

enable cost-effective 1-axis tracking

Captures up to 30% more sunlight

than fixed tilt systems with only one

low-power actuator per ~200kW

Reduces the $/kwh costs of the

modules, mechanical and electrical

BOS, and O&M costs

Better match of energy production

with summer load (time of day & seasonal)

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Fixed Tilt CF - Mojave

T0 Tracker - Mojave

Cal ISO Load 7/15/08

Peak CA Summer

Load

PV Power Plant Output vs.

Summer Utility Demand

Curve

Load

T0 tracker

Fixed tilt


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Fixed Tilt CF - Mojave

T0 Tracker - Mojave

Cal ISO Load 7/15/08

Peak CA Summer

Load

20.0%

22.0%

24.0%

26.0%

28.0%

30.0%

32.0%

34.0%

36.0%

38.0%

40.0%

Fixed Tilt T20 Tracker T0 Tracker

Annual CF

Summer CF

Summertime capacity factor with SunPower

modules and T0 tracker in Las Vegas is 38%


Performance

11

LCOE = Energy produced

Total System Installed Costs + O&M CostsNPV [ ]

LCOE ≡ Levelized Cost of Energy

NPV ≡ Net Present Value

Total system costs includes cash flow impact of financing

O&M ≡ Operation and Maintenance

Energy / rated W Environmental conditions

Mounting (tracking, tilt,…)

System design

Module type

System availability(uptime)

System Quality and Reliability System Lifetime

Degradation rates

Failure rates

Confidence in the energy production and O&M estimates very strongly affects selling price and financing rates

High Efficiency

]NPV [

The importance of performance (and accurate, confident prediction of that performance)

© 2010 SunPower Corp.12

Degradation rate, system life, O&M, and discount rate can have a

tremendous impact on LCOE:

Case 1 Case 2 Case 3

System Price 100% 100% 100%

kWh/kWp 100% 100% 100%

Annual Degradation 1.0% 0.5% 0.3%

System Life 15 25 40

Annual O&M $/kWh 0.030$ 0.010$ 0.005$

Discount Rate 9% 7% 5%

LCOE $/kWh 0.23$ 0.13$ 0.09$

31% decrease

in LCOE

77% increase

in LCOE

Assume same installed

price and first year

energy performance

Varied as shown


Performance and performance prediction

Analysis of technology attributes (physics of energy production)

13

Goals:

• High performance

• Accurate prediction of

that performance

Analysis of field data

SunPower simulation tool:

– Description

– Validation

– Performance

Understanding of 3rd-party simulation tools


Physics of energy production

#1 factor: Nominal Efficiency = 12% 67% (i.e., 4-20% efficiency modules)

#2 factor: Climate and mounting (e.g. trackers give up to 35% increase vs. fixed tilt)

kWh/kWp for a given location/mounting is normally within 5%, but still valuable to customer and is a tool for understanding and optimization

– < 1 sun irradiance

– Temperature coefficient

– Temperature of operation

– Spectral effects

– Light-induced degradation

– Yearly degradation

14


Irradiance level

Standard Test Condition: 1000 W/m2 irradiance. Average irradiance outdoors is <1000 W/m2

All else being equal:

– High series resistance (Rs) reduces energy produced but increases kWh/kWp

– Low shunt resistance (Rsh) reduces energy produced and kWh/kWp

SunPower modules have low Rs and high Rsh

Note: If a manufacturer with high Rs raises module efficiency by reducing Rs, their kWh/kWp will go down, so previous field data of kWh/kWp should not be used without adjustment

15

Low series resistance

High series

resistance

SunPower 318W module


Temperature coefficient

Main influence on Tcoef is Voc relative to band gap (higher Voc/Eg is good)

Traditional c-Si ‡ and mc-Si ‡ Voc=0.625 Tcoef, power = -0.47%/C

SunPower back-contact Voc=0.691 Tcoef, power = -0.38%/C

For a warm location with an energy-weighted average T of 45⁰C:

– Loss of energy from temperature for traditional Si: 9.4%

– Loss of energy from temperature for SunPower: 7.6% (1.8% lower than std)

– Loss of energy from a thin film with Tcoef = -0.25%/C: 5.0% (4.4% lower than std)

16

‡Data for 10 largest producers of traditional silicon modules as reported by Photon International


Operating temperature

Operating temperature differences comes from:

Mounting (e.g., air-gap to roof) - is the largest factor

Differences in temperature at open-circuit from module type

– NOCT = Normal Operating Cell Temperature, but NOCT measured at open circuit

– Module packaging (especially module transparency) can affect NOCT

– SunPower NOCT measured to be ~1⁰C lower than standard c-Si

Measurements show one factor is higher reflection and transmission of far infrared wavelengths, which is only partially offset by higher absorbance of visible wavelengths

Reduced temperature from higher efficiency

– Cells are cooler in operation than at open circuit because some energy is sent out as electricity instead of dissipated as heat.

– A SunPower 19.4% module vs. a standard c-Si 14.4% module means ~5% less heat to dissipate, and ~1.4⁰C lower operating temperature (beyond NOCT differences)

17


Spectral effects

Single junction with c-Si bandgap gives high tolerance to spectral variation:

– Gives higher efficiency at air-mass > STC condition of AM1.5. Average AM is

> 1.5, so this increases kWh/kWp of SunPower and other c-Si relative to most thin films

18

c-Si

CdTe

2j a-Si

3j a-Si

Response curves of selected modules in Sandia module database; other modules within a technology type can have a different response.


Degradation

Light-induced degradation (LID)

– SunPower uses n-type Si, so no LID

– “Average” c-Si LID is ~1.5% (previously, some low-quality modules had LID > 10%)

Yearly degradation

– 0.3% vs. 0.7% gives 4.5% difference in energy production over 25 years

– Field testing from NREL and other locations is showing a lower-than-average degradation of SunPower modules

19


Attribute impact on kWh/kWp

Rough estimations of kWh/kWp of SunPower compared to:

20

Lower-than-average yearly degradation and failure probability for SunPower

modules is expected to increase this kWh/kWp advantage

vs. “average c-Si” vs. CdTe vs. “avg” a-Si

Climate: hot cool “average” “average”

Irradiance level - 0.4% - 0.7% -2% -4%

Temp. coefficient 2.4% 1.2% -1.9% -4%

Operating Temp. 1.3% 1.0% 2% 1.5%

LID 1.5% 1.5% 0 3%

Spectrum 0 0 2% 8%

Angle of incidence 0.1% 0.3% 1% 1%

Total ~5% ~3% ~0.5% ~5%

Due to the large range of “average c-Si”, and the large range of mounting types and climates, the estimates are only offered as a benchmark for

analysis of field test results. The values for the “average” CdTe and a-Si have even greater uncertainty, due to both the variation within each of

those technologies and the amount of technical data we have available


Meta-analysis of field tests with SunPower modules

10 independent field tests including SunPower PV were reviewed to evaluate the relative performance among PV Technologies.

The 10 field test represent all the independent tests known to SunPower where data was available for analysis

Institute/ Test Site Location Start End Years Technologies

HE c-Si c-Si TF

SunTechnics Study Landshut, DE Apr '05 Apr '06 1.0 1 1

CREST Leicestershire, UK Apr '07 Apr '08 1.0 1 2

ISAAC-TISO Lugano, CH Mar '06 Jul '07 1.3 2 9 3

IPE, Uni Stuttgart Stutgartt, DE June '06 on-going 4.1 2 7 4

IPE, Uni Cyprus Nicosia, Cyprus June '06 on-going 4.1 2 7 4

IPE, Egypt Alexandria, Egypt Aug '08 Jun '09 0.9 2 7 4

Hokaido Electric (NEDO) Wakanai, Japan Apr'07 Sep'07 0.5 2 4 2

Landwirtschafliche

Lerhanstalten, Bayreuth Bayreuth, DE Jan '09 Dec '09 1.0 2 1 3

Gelsenkirchen FHS Bocholt, DE Jun '09 Oct '09 0.4 3 1

Desert Knowledge Alice Springs, AU Oct '08 on-going 1.8 1 4 1

21


Field Test Issues

Test with side-by-side 2.6kW arrays‡ showed mc-Si had 63% higher kWh/kWp compared to CdTe! Is that real?

22

‡ R. Eke, S. Oktik, “Comparison of 18 Month kWh/kWp Energy Output of Four Photovoltaic Systems with Four Different Module

Technologies, Proceedings of the 22nd European Photovoltaic Solar Energy Conference, 3-7 September 2007, Milan, Italy.

– No! The CdTe array was shaded part of the day and had inverter issues.

Degradation– Initial degradation / stabilization

– Different yearly degradation rates

Defining kWh/kWp baseline– Mfg flash or independent measurements better for c-Si, but would be unfair to thin films

which degrade then stabilize (best is to use stabilized value as the “kWp” baseline)

Non-Representative Results

– Results vary for PV technologies within single tests and between different tests (i.e., a single test should not be assumed to be representative)

– Non-representative results can skew kWh/kWp estimates if included in averages. Non-representative modules in tests and test set-up problems occur often.

Year 1 Year 2 Year 5

a-Si Single junction +23% +3% -7%

a-Si Triple junction +7% -3% -10%

Example: Energy per rated W vs. mc-Si module

Source: Rodziewicz, et. al, “Long-Term Analysis of Energy

Gained by Different PV Modules in 2001-2006”,


Field Test Results

Analysis results show higher kWh/kWp performance of SunPower vs. other technologies, similar to the results from attribute analysis

23

-3.0%

-2.0%

-1.0%

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

HIT c-Si CdTe a-Si CIS

kWh/kWp of SunPower vs. other types

Approach 1

Approach 2

Approach 1:(Broad # of Sites)

Approach 2:(Minimize Test Issues)

# Tests 9 3

Duration 14.3 yrs 9.4 yrs

Field Test issues

Degradation - Use all data - Tests > 1 yr data

- Weight results by

duration of tests

kWh/kWp

Baseline

- Rated power - Mfg flash for c-Si

- Rated power for

thin films

Sample Size - 9 tests;

2-13 per tests

3 tests; 10 or more

per test; min 2 per PV

Technology

Non-

representati

ve Data

- Omit irregular

data (DKA test

omitted)

Omit irregular data

(DKA test omitted)

Two analysis approaches


Performance Prediction - PVSim

PVSim Engine

Balance of

System Losses

External Loss

FactorsPVSim

Web UI

PV Model:Cell Temperature

Energy Conversion

Inverter

Site

Location

Weather

Data

System

Design

Geometry:Solar Position

Module Orientation

Incidence Angle

Shading

Irradiance:Beam/DNI

Diffuse

Plane-of-Array

System Power &

Energy Yield

24

PVSim is SunPower’s web-based software tool used to predict PV system energy production

Loss factor assumptions based on 12 years of experience

Component specs updated by industry experts and validated by in-house and 3rd-party testing

Validation includes both model behavior and total performance


Performance Prediction – Model Validation

25


SunPower simulation tool

PVSim provides accurate prediction across a range of applications.

– Standard deviation of error is 1.3%

– Actual energy delivery is 1.2% higher than predicted

26

Powerguard = flat fixed mount

T0 = horizontal 1-axis tracked

T10 = 10° fixed tilt

T20 = 20° tilt 1-axis tracked


3rd-party energy prediction tools

Some tools do not have advanced models for accurately predicting irradiance, tracking effects, shading effects, operating temperature, and/or module-response to irradiance and spectrum

Models which use manufacturers data-sheet values without validating against test data can incorrectly predict modules’ response to irradiance and spectral variations, leading to large prediction error (absolute, and one module vs. another)

27


Performance analysis conclusions

28

• High kWh/kWp performance of SunPower modules and systems

• High-confidence prediction of energy production using advanced

simulation tool, aided by consistency and understanding of products

Attribute analysis: Predicts ~3-5% kWh/kWp advantage of SunPower vs. standard c-Si, and ~1-5% vs. thin films

Meta-analysis of 10 independent field tests:

– Average kWh/kWp: +5% vs. standard c-Si and +3% vs. thin films

SunPower advanced energy simulation tool:

– Standard deviation of error in actual vs. predicted for 17 large systems across broad range of locations and mounting approaches = 1.3%.

Lower-than-average yearly degradation and failures rates would increase this kWh/kW advantage

QUALITY AND RELIABILITY

SunPower’s unique perspective

30

>1 GW solar PV deployed

550 MW 2010 production

Diversified portfolio: roofs to power plants

1. Broad view from deployments

built with a wide variety of PV

modules from more than a

dozen different manufacturers

over more than 10 years.

2. Fully-vertical enables closed-

loop learning from the roofs and

power plants back to whatever

the root cause, from wafering to

cell and module mfg, to systems.

3. Manufacturing heritage from IC

chips

SunPower brings a unique perspective to

the challenge of deploying high-reliability

PV modules …

… we are sharing this information in the

belief that the entire industry benefits from

a high prevalence of robust PV modules.


Deploying high-reliability PV Modules: Overall Process

31

CustomerStatistical Process Control

Cert.testing

Qualification Testing

• Testing-to-failure

• Long-term testing

• Field testing Cont. Mfg. Testing

• ORT

• HASA

FMEA

• Field Experience

• HALT

• Theoretical under-standing

Supplier Quality Control

• PSC Audit

• STARS score

• Inc. Mat’l Audit

Out-of-box Audit

• Reliability Req’ts,

• Design Concepts

Manufacturing QualityDesign for Reliability

Closed-loop learning



32


Cert.testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts




Failure Modes and Effects Analysis (FMEA)

FMEA is the foundation of Design for Reliability – it’s list of all known failure modes, and their relative importance

The FMEA is typically built from 3 primary areas:

– Field Experience

– Tests-to-failure, e.g. HALT, long-term-testing

– Theoretical understanding / modeling

Examples of FMEAs given by SunPower in papers presented at EUPVSEC 2010 (D. DeGraaff et al., and G. Bunea et al.)

33

The FMEA lists all the possible failure modes, and therefore it drives the

Qualification Testing, as well as the Continuous Manufacturing Testing.


Highly Accelerated Life Testing (HALT)

HALT is a method of discovering product weaknesses by applying stress combinations which are relevant, but considerably exaggerated.

Goal is to rapidly activate the same failure modes that would take years in the field. (It is not a pass/fail test.)

SunPower’s module HALT includes:

– Solar Simulator

– Oven test

– Damp Heat with voltage bias

– Dynamic load

34

It is difficult or impossible to obtain information about how things fail in the

absence of actual failures: TEST TO FAILURE!


Solar simulator HALT

35

The Solar Simulator explores melting of certain encapsulants, breakdown of

adhesives, corrosion, discoloration, out-gassing, local hot spots, and behavior

of extremely hot cells (sometimes exceeding 170C)

1%

0

-1%

-2%

-3%

-4%

-5%

Before After

Bubbled backsheet

likely from layup-tape

out-gassing

Delamination

along

interconnect-

ribbon likely from

flux residue

SunPower back-contact-cell modules

Power Output Change


(short-circuit, 1sun plus 150W/m2 UV,

55%RH, 60⁰C ambient)

Damp heat with bias HALT

36

Power Output Change

SunPower back-contact-cell modules

0%

-2%

-4%

-6%

-8%

-10%0 600

Time (hrs)

Damp Heat with bias (1000V) significantly accelerates failure modes relative to

Damp Heat without bias.


Front-contact

metal corrosion

(1000V, 85%RH, 85⁰C ambient)

Damp heat with bias HALT

37

Power loss

Sample 1: -3.2%

Sample 2: -4.4%

Power loss

Sample 1: -12%

Sample 2: -23%

Electroluminescence

images show damaged

cells around the

perimeter, where

leakage current to the

frame is highest.


Dynamic Load HALT

1,000 alternating cycles of +/-2400 Pa (standard wind load), then 4 temp. cycles -40 to 60C

< 1% loss in power for SunPower modules with all-back-contact cells:

38


Reason for better performance of modules with back-contact cells

Back contact design includes thick and wide metal “fingers” that cover the entire back of the cell.

– For cracks, the power loss is from recombination within the crack itself – the high coverage of the back-contact metal keeps cell intact

– For corrosion (damp-heat with bias), the large area of metal provides a buffer –the series resistance stays low even with some corrosion.

39

Metal (+) and (-) “fingers” cover

the entire back of the wafer

Stamped, strain-relieved copper

bar connects adjacent cells with

redundancy



40


Cert. testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts


Closed-loop learningThe Qualification Test Plan should address all moderate and high RPN

failure modes in the FMEA.


SunPower back-contact-cell modules: long-term testing example

41



42


Cert.testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts




Certified ≠ High-Reliability

… but it is not sufficient to assure high reliability.

43

Certification is needed to sell PV modules …

– IEC 61215, 61730 and UL 1703 module certifications

– ISO 9001 certification



44


Cert.testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts




Supplier Quality Control: 4 stages

1. Early engagement

• Understand internal requirements, determine sourcing strategy

2. Planning and Preparation

• Set expectations with supplier, develop a roadmap

3. Qualification

• Align expectations, data collection and analysis, conformance

• Change Notification process

• PSC audit (Prevention / Standardize / Customer Satisfaction

• STARS (Supplier Total Achievement Rating System) score

4. Ongoing oversight

Improvement plan, periodic review

Self-assessment with validation (incoming materials inspection)

45



46


Cert.testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts




Statistical Process Control (SPC)

From semiconductor fab heritage

Mindset: know the effects of every change for each process step (including interactions).

– Response Surface Mapping defines the Process Windows, limits determined by “running the corners”

SunPower uses a 6-level approach, starting with “What to Control,” and ending with “Continuous Improvement”

47



48


Cert.testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts




Continuous Manufacturing Reliability Testing

Tests are a final insurance against defects.

Highly Accelerated Stress Audit (HASA) – detect any material defects or manufacturing problems that escaped the supplier quality and manufacturing SPC hurdles.

– Address the key degradation mechanisms from the FMEA

Ongoing Reliability Testing (ORT) - to continue to validate the baseline reliability of the product.

– These are longer-duration tests with milder stress levels.

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Cert.testing





• ORT

• HASA

FMEA


• HALT



• PSC Audit

• STARS score


Out-of-box Audit


• Design Concepts





Reliability essential for non-module components too

Just the waterproof validation testing included:

TAS-100 Wind Driven Rain Test

– Tests for ability to resist rain infiltration in hurricane conditions.

– Wind Speed 35 to 120 mph in segments, with time between segments to allow water to infiltrate, 8.8 in/hr rainfall

Aging & Flood Test

– Accelerated aging, followed by 96 hour immersion test (up to screw heads), adhesion testing.

On-roof flood test by Aquatech consulting

– 4-8 gallons/ft2/hour, performed for one hour.

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SunPower Smart Mount®

- Reduces materials and installation costs

- No rails, so low profile but cool operation

SUNPOWER CONFIDENTIAL


Thank You

Documents

Motivation and approach for predictable high - ISETC · Motivation and approach for predictable high ... described in the company’s Annual Report on Form 10-K for the year ended