## Table5-3:Lot 4 Verification of Correction Factor in Clothes Washer led I'ciii (SoakTeup.. 1'iine g 1.o 3 L I\EC (Standard) Lol4 1MC Corrected MC

# 1 Warm, 15, 50 51.4% 6.3% 

### 50.5% 496% 57.2% 

### 51.5%

____________________________ 

### 502% 57.2% 51.5%

Warm 15 200 36.4% 42.2% 37.0% 35.7% 42.6% 37.4%

____________________________ 34 9% 

### 40.5% 35.4%

Warm, 15, 350 29.1% 34.2% 

### 29.3% 29.9% 34.2% 29.3%

___________________________ 

### 29.9% 34.1% 29.2%

Warm, 4, 50 55.8% 61.5% 55.6% 55.8% 61.5% 55.6%

___________________________ 55.5% 

### 6/1% - 

### 55.3% Warm, 4, 200 4/1% /6% - 

### 41.0% 40.6% 45.6% 40.3%

_________________________ 

### 39.6% 15.5% 40.2%

Warm, 4, 350 32.1% 37.5% 32.5% 33.6% 37.8% 32.8%

___________________________ 33.5% 

### 385% 33.5%

C'old,15,50 52.2% 588% 53.0% 53,3% 58.0% 52.3%

____________________________ 

### 53.1% 59.8% 54.0%

Cold, 15, 200 38.0% 43.1% 37.9% 37.9% 42.2% 37.0%

____________________________ 

### 37.9% 43.4% 38.2%

Cold, 15, 350 30.4% 35.5% 30.6% 30.7% 35.4% 

### 30.5%

___________________________ 

### 31.1% 35.4% 30.5%

Cold, 4, 50 59.1% 64.6% 58.6% 58.9% 64.4% 58.4%

____________________________ 

### 58.9% 63.2% 57.3%

Cold, 4, 200 -43.5% 

### 47.9% 42.5% 43.0% 49.0% 43.6%

___________________________ 

### 42.8% 48.5% 43.1%

Cold, 4, 350 35.3% 41.3% 36.3% 36.0% 40.3% 35.2%

___________________________ 36 0% 

### 35 9%

5-7

## Table 5-4: Lot5Verification of Correction Factor in Clothes Washer

fl's Paiiii(Saa Temp.. Time, g La! .3 1M( 'Vmri1ard, Lar 5 R'iiC Ca,rred 1?MC



### Warm, 15, 50 51.4% 54.7% 

### 51.4% 49.6% 55.4% 

### 52.0%



### ____________________________ 50.2% 551% 49.7%

Warm, 15, 200 .36.4% 40.1% 36.8% 35.7% 39.3% 36.2%

_______________________________ 34.9% 39J% 35.8%

Warm, 15, 350 29.1% 32.8% 29.6% 29.9% 322% 

### 29.0%

___________________________ 

### 290% 32.1% 28.9%



### Warm, 4, 50 55.8% 58.1% 

### 54.7% 55.7% 504% 

### 56.0%



### ____________________________ 55.5% 567.% 

### 55.3%

Warm, 4,200 41.1% 44.6% 41.3% 40.6% 44.4% 41.1% 39.6% 432%

____________________________



### Warm, 4, 350 32.1% 36.6% __________________ 

### 33.4% 33.6% 36.4% 33.2%

_______________________________ 33. 3/ 32.0%

Cold, 15, 50 52.2% 56.4% 53.0% 53 3% 55.4% 52.0%

_______________________________ 53 1% 5..8% 

### 52.4%

Cold, 15,200 36.0% 41.7% 

### 38.4% 37.9% 40.0% 

### 36.7%

____________________________ 

### 37.9% 434% 39.1%

cold, 15, 350 30.2% 

### 35.1% 31.9% 30 7% 33.0% 

### 29.8%

____________________ 

### 311% 

## __3.Lz% 30.5%

cold, 4,50 59.1% 

### 61.4% 58.0% 58994 61.9% 

### 58.5%

_______________________________ __________________ 

### 62.4% 59.0%

Cold, 4, 200 43.5% 46.6% 43.3% 43.0% 47.6% 44.3%

_______________________________ 42.8% ..............3% 43.0%



### Cold, 4, 350 35.3% 

### 3/1.6% 35.3% 36.0% 357% 35.4%

________________________________ ( 1% 9 6% 7% 

### RMC values were determined for a horizontal axis washer and a vertical axis washer, following theJlRN/IC test procedure, with each ofTIlots 3 (the standard), 4 and5. TheRMC tests were run three times for each clothes washer/testclothlot combination. Tables5-5and5-6 summarize the RMC measured in each of the machines using test cloth fromTIlots4and5, respectively. In eachtable,these values are corrected to theTIlot3standard and compared to the RMC values measured with test cloths fromTIlot3. Withone exception, the corrected RMC is less than1%of the RMC measured with the standard(TIlot3)testcloth.

5-8

## Table5-5:Verification of Lot 4 Correction Curve in Clothes Washer Mtthint 'l'e 

# ] Lot 3 RJW Lo 4 R1C 

# j (orreekd Lot 4 R1C Vertical-Axis Machine 55.4% 62.0% 56.1% 56.0% 6 1.5% 55.7% 56.1% 61.2% 55.3% Horizontal-Axis Machine 47.1% 53.6% 48.1% 49.3% 54.3% 48.7% 48.6% 54.5% 48.8%


## Table 5-6: Verification of Lot5Correction Curve in Clothes Washer Machiiie type Lot 3 RM( Lot 5 RMC 

# J Cocrcctcil oi RNC. 

### Vertical-Axis Machine 55.4% 59.4% 56.0% 56.0% 59.6% 56.2% 56.1% 60.0% 56.6% Horizontal-Axis Machine 47.1% 50.3% 47.0% 49.3% 49.8% 46.5% 48.6% 51.9% 48.5%

5-9

## 6 Approach to obtaining and verifying consistent test cloth

An approach to minimize the effects of cloth variation on RMC is to consistently specify a single type of fabric that is produced frequently by one mill to a consistent set of specifications. Riegel Permalux50/50Momie Weave appears to be a suitable choice, because this cloth is produced in high volume, has been produced to a consistent specification for many years and is likely to continue to be produced on this basis for the foreseeable future. Riegel produces the yarns from purchased fiber and weaves and finishes the cloth material, so they have complete control over the process. With the modest inconsistencies between lots that have been observed to date, a correction factor needs to be applied to obtain consistent clothes washer RMC test results. The previous section presented a linear least squares fit method to correct actual cloth to "standard" cloth. The material below summarizes the cloth specifications, the approach to consistency verification and the translation of these into draft language that could be inserted into the test standard (Appendix Ji). 6.1 Outline of Proposed Specification Specify one standard grade of cloth from one mill: e.g.,Riegel Permalux 50/50 Momie Weave with pure bleached finish 2 Change the energy test cloth specification in 10 CFR 430 Subpart B Appendix Ji to: Duplicate the Riegel Mills specifications for the Permalux50/50 -50/50cottonlpolyester±4% -5.60oz/sq. yd.±5% -Warp and filling yarns 15/1±5%cotton count, open end spun yarn -Thread counts of 61 x54(warp x fill) ±2% Require AATCC- 118 with "D" across the board result Require AATCC-79 with drop absorbing time on the order of 1 second • Require standard extractor based RMC vs. g standardization curves and RMC correction curve for each new lot of test cloth

6-1

## 6.2 Verification

AATCC- 118 Oil Repellency Test (DuPont or 3M version) of each new lot of test cloth (when purchased from Riegel) to confirm absence of Scotchguard or other water repellent finish (required scores of"D" across the board) 2. AATCC-79 Drop Absorbency Test of each new lot of test cloth (when purchased from Riegel) for further confirmation of the absence of Scotchguard or other water repellent finish (time to absorb one drop should be on the order of 1 second) Run 4 minute and 15 minute standard RMC vs. g curves with 60°F and 100°F water temperature for each new lot of test cloth as the basis for calculating an RMC correction curve to correct RIVIC test results to "standard" test cloth (average of TI lot 3) 6.3 Standard Language DOE Draft Language for Changes to Ji Test Procedure to Specify The Energy Test Cloth and The RIVIC Correction to "Standard" Test Cloth RMC Appendix J and Ji to Subpart B of Part 430 of the clothes washer test procedure is amended to read as follows: §430.23 Test procedures for measures of energy consumption * * * * * 

## Appendix J to Subpart B of Part 430-Uniform Test Method for Measuring the Energy Consumption of Automatic and Semi-Automatic Clothes Washers * * * * * 

## 2.3 Supply water.2.3.1 Supply water reQuirements for water and energy consumption testing. For nonwaterheating clothes washers not equipped with thermostatically controlled water valves, the temperature of the hot and cold water supply shall be maintained at 1 OOE+ 1 OEF (37.8EC+5.5EC). For nonwater-heating clothes washers equipped with thermostatically controlled water valves, the temperature of the hot water supply shall be maintained at 14OEF+5EF (60.OEC+2.8EC) and the cold water supply shall be maintained at 6OEF+5FE( 15 .6EC+2.8EC). For water-heating clothes washers, the temperature of the hot water supply shall be maintained at 14OEF+5EF(60.OEC+2.8EC) and the cold water supply shall not exceed 6OEF(15.6EC). Water meters shall be installed in both the hot and cold water lines to measure water consumption.

6-2

## 2.3.2 Supply water requirements for remaining moisture content testing. For nonwater-heating

clothes washers not equipped with thermostatically controlled water valves, the temperature of the hot water supply shall be maintained at 140F + 5F and the cold water supply shall be maintained at 60F +5F. All other clothes washers shall be connected to water supply temperatures as stated in Section 2.3.1. * * * * * 

## 2.10 Wash time (period of agitation or tumble setting. If the maximum available wash time in the normal cycle is greater than9.75minutes, the wash time shall be not less than9.75minutes. If the maximum available wash time in the normal cycle is less than9.75minutes, the wash time shall be the maximum available wash time. * * * * * 

## 2.11 Agitation speed and spin speed settings. Where controls are provided for agitation speed and spin speed selections, set them as follows: 2.11.1 For energy and water consumption tests, set at the normal cycle settings. If settings at the normal cycle are not offered, set the control settings to the maximum speed permitted on the clothes washer. * * * * * 

## 3.3.1 The wash temperature shall be the same as the rinse temperature for all testing. Cold rinse is the coldest rinse temperature available on the machine. Warm rinse is the hottest rinse temperature available on the machine. * * * * * 

## Appendix Ji to Subpart B of Part 430-Uniform Test Method for Measuring the Energy Consumption of Automatic and Semi-Automatic Clothes Washers * * * * * 

## 1.22 Cold rinse means the coldest rinse temperature available on the machine (and should be the same rinse temperature selection tested in section 3.7). 1.23 Warm rinse means the hottest rinse temperature available on the machine (and should be the same rinse temperature selection tested in section 3.7). * * * * *


## 2.6 Test Cloths. 2.6.1 Energy Test Cloth. The energy test cloth shall be made from energy test cloth material, as specified in 2.6.4, that is 24 inches by 36 inches (61.0 cm by 91.4 cm) and has been hemmed to 22 inches by 34 inches(55.9cm by 86.4 cm) before washing. The energy test cloth shall be 6-3

## clean and shall not be used for more than 60 test runs (after preconditioning as specified in

section 2.6.3). Mixed lots of material shall not be used for testing the clothes washers. 2.6.2 Energy Stuffer Cloth. The energy stuffer cloth shall be made from energy test cloth material, as specified in 2.6.4, and shall consist of pieces of material that are 12 inches by 12 inches(30.5cm by 30.5 cm) and have been hemmed to 10 inches by 10 inches (25.4 cm by25.4 cm) before washing. The energy stuffer cloth shall be clean and shall not be used for more than 60 test runs (after preconditioning as specified in section 2.6.3). Mixed lots of material shall not be used for testing the clothes washers. 2.6.3 Preconditioning of Test Cloths. The new test cloths, including energy test cloths and energy stuffer cloths, shall be pre-conditioned in a clothes washer in the following manner: 2.6.3.1 Perform5complete normal wash-rinse-spin cycles, the first two with AHAM Standard detergent 2A and the last three without detergent. Place the test cloth in a clothes washer set at the maximum water level. Wash the load for ten minutes in soft water (17 ppm hardness or less) using 6.0 grams per gallon of water of AHAM Standard detergent 2A. The wash temperature is to be controlled to 135° + 5°F (57.2° + 2.8°C) and the rinse temperature is to be controlled to 60° + 5°F (15.6° + 2.8°C). Repeat the cycle with detergent and then repeat the cycle three additional times without detergent, bone drying the load between cycles (total of five wash and rinse cycles). 2.6.4 Energy test cloth material. The energy test cloths and energy stuffer cloths shall be made from fabric meeting the following specifications. The material should come from a roll of material with a width of approximately 63 inches and approximately 500 yards per roll, however, other sizes maybe used if they fall within the specifications. 2.6.4.1 Nominal fabric type. Pure finished bleached cloth, made with a momie or granite weave, which is nominally 50 percent cotton and 50 percent polyester. 2.6.4.2 The fabric weight shall be5.60ounces per square yard (190.0 g/m2),+5percent. 2.6.4.3 The thread count shall be 61 x 54 per inch (warp x fill), +2 percent. 2.6.4.4 The warp yarn and filling yarn shall each have fiber content of 50 percent +4 percent cotton, with the balance being polyester, and be open end spun, 15/1 +5percent cotton count blended yarn. 2.6.4.5 Water repellent finishes, such as fluoropolymer stain resistant finishes shall not be applied to the test cloth. The absence of such finishes shall be verified by:

6-4

## 2.6.4.5.1 AATCC- 118 Oil Repellency Test (DuPont or 3M version) of each new lot of test cloth

(when purchased from the mill) to confirm the absence of Scotchguard or other water repellent finish (required scores of"D" across the board). 2.6.4.5.2AATCC-79 Drop Absorbency Test of each new lot of test cloth (when purchased from the mill) to confirm the absence of Scotchguard© or other water repellent finish (time to absorb one drop should be on the order of 1 second). 2.6.4.6 The moisture absorption and retention shall be evaluated for each new lot of test cloth by the Standard Extractor Remaining Moisture Content (RMC) Test specified in section 2.6.5. 2.6.4.6.1 Repeat the Standard Extractor RMC Test in section2.6.5three times. 2.6.4.6.2 An RMC correction curve shall be calculated as specified in section 2.6.6. 2.6.5 Standard Extractor RMC Test Procedure. The following procedure is used to evaluate the moisture absorption and retention characteristics of a lot of test cloth by measuring the RMC in a standard extractor at a specified set of conditions. Table2.6.5is the matrix of test conditions. The 500g requirement will only be used if a clothes washer design can achieve spin speeds in the 500g range. When this matrix is repeated 3 times, a total of 48 extractor RMC test runs are required. For the purpose of the extractor RMC test, the test cloths may be used for up to 60 test runs (after preconditioning as specified in section 2.6.3). Table 2.6.5 Matrix of ExtractorRMCTest Conditions "g" Force Warm Soak Cold Soak

15 mm. spin 4 mm. spin 15 mm. spin 4 mm. spin

____________ 50

____________ _______________ ________________ 

## 200 _______________

___________ _______________ _______________ 

## 350 ______________

___________ _______________ _______________ 

## 500 ______________

_______________ ____________ _______________ ________________ 

## 2.6.5.1 The standard extractor RMC tests shall be run in a Bock Model 215 extractor (having a basket diameter of 19.5 inches, length of 12 inches, and volume of 2.1 ft3), with a variable speed drive [Bock Engineered Products, P.O. Box5127,Toledo, OH 43611] or an equivalent extractor with same basket design (i.e. diameter, length, volume, and hole configuration) and variable speed drive. 2.6.5.2 Test Load. Test cloths shall be preconditioned in accordance with 2.6.3. The load size shall be 8.4 lbs., consistent with section 3.8.1.

6-5

## 2.6.5.3 Procedure.

2.6.5.3.1 Record the "bone-dry" weight of the test load (WI). 2.6.5.3.2 Soak the test load for 20 minutes in 10 gallons of soft (< 17 ppm) water. The entire test load shall be submerged. The water temperature shall be 1 OOEF ±5EF. 2.6.5.3.3 Remove the test load and allow water to gravity drain off of the test cloths. Then manually place the test cloths in the basket of the extractor, distributing them evenly by eye. Spin the load at a fixed speed corresponding to the intended centripetal acceleration level (measured in units of the acceleration of gravity, g) ±1 g for the intended time period±5seconds. 2.6.5.3.4Record the weight of the test load immediately after the completion of the extractor spin cycle (WC). 2.6.5.3.5 Calculate the RMC as (WC-WI)/WI. 2.6.5.3.6The RMC of the test load shall be measured at three (3) g levels: 50g; 200g; and 350g, using two different spin times at each g level: 4 minutes; and 15 minutes. If a clothes washer design can achieve spin speeds in the 500g range than the RMC of the test load shall be measured at four (4) g levels: 50g; 200g; 350g; and 500g, using two different spin times at each g level: 4 minutes; and 15 minutes. 2.6.5.4Repeat2.6.5.3using soft (<17 ppm) water at 6OEF ±5EF. 2.6.6 Calculation of RMC correction curve. 2.6.6.1 Average the values of 3 test runs and fill in Table2.6.5. Perform a linear least-squares fit to relate the standard RMC(RMCstandard)

## values (shown in table 2.6.6.1) to the values measured in 2.6.5(RlIVICCIOh): RI\4Cstandard 

## A*

## P]AC +

## B Where A and B are coefficients of the linear least squares fit.

6-6

## Table 2.6.6.1 StandardRMCvalues(RMCstandard)



## G RMCpercent

_____________ 

## Warm Soak Cold Soak

_____________ 

## 15 mm. spin 4 mm. spin 15 mm. spin 4 mm. spin 50 50.4% 55.7% 52.8% 59.0% 200 35.6% 40.4% 37.9% 43.1% 350 29.6% 33.1% 30.6% 35.8% 500 24.2% 28.7% 

## 25.5% 30.0% 2.6.6.2 Check accuracy of linear least squares fit using the following method: The root mean square value of:
2 1/2 12

# ( RIVlCstandardi

-

# iRIvIc01)
i=1 

## 10 shall be less than 2 percent, where a sum is taken over all of the different tests, where RMCstandardi is the RIVIC standard value measured for the I-th test, and RMCQ is the corrected RMC value for the I-th cloth test. This equation is valid only for the use with three (3) g force values therefore when using the 500g requirement; replace the 500g value instead of the350g value. 

## 2.6.7 Application of RMC correction curve. 2.6.7.1 Using the coefficients, A and B calculated in section 2.6.6.1: RMC0=A * RMC+B 

## 2.6.7.2 SubstituteRMCIOrr

## values in calculations in section 3.8. * * * * *



## 4.1.5 * * * * * ERR, ER a' ER , are reported electrical energy consumption values, in kilowatt-hours per cycle, at maximum, average, and minimum test loads, respectively, for the warm rinse cycle per definitions in section 3.7.2.

6-7

## Appendix A: Test Data

### ADL Fabric Cycle Life Testing Wash g RMC Load WI. Bone Dry Wt. 1 100 45.7% 8.4 lb. 3788 2 200 37.3% 8.4 lb 3786 3 300 32.3% 9.4 lb. 3775 4 500 27.3% 8.4 lb. 3770 5 100 47.0% 8.4 lb. 3769 6

-- 3776 7

-- -- 3774 8

-- 3764 9 100 52.9% 3.0 3773 10 100 49.4% 5.7 3765 11 100 46.6% 8.4 3762 12 3771 13

-- 3767 14 3757 15 300 35.5% 3.0 3755 16 300 37.7% 5.7 3769 17 300 31.5% 5.4 3751 18 300 35.5% 3.0 3749 19

-- 3740 20

-- 3745 21 100 45.8% 8.4 lb. 3744 22 200 36.9% 8.4 lb. 3737 23 300 31.7% 8.4 lb. 3736 24 500 26.6% 8.4 lb. 3743 25 100 46.7% 8.4 lb. 3747 26 500 -j.-

-- 3729 27 300 33.5% 5.7 3739 28

-- 3730 29 3731 30 3731 31 3728 32 100 47.0% 8.4 lb. 3732 33 100 46.9% 8.4 lb. 3732 34

-- 3722 35

-- 3715 36

-- 3725 37

-- 3723 38 3727 39 100 46.9% 8.4 lb. 3723 40 100 48.0% 8.4 lb. 3714 41 3706 42 3713 43

-- 3709 44

-- -- 3714 45

-- 3706 46 100 47.4% 8.4 lb. 3713 47 100 46.9% 8.4 lb. 3702



### 2

# Table 1. Life Cycle Shrinkage
Lot 4 Hi H2 H3 vi V2 V3

Lot 5 Hi H2 H3 Vi V2 V3

Lot4 Hi H2 H3 Vi V2 V3

LotS Hi H2 H3 VI V2 V3 Unwashed Seti Set2 Set3

1 2 3 1 

### I 2 3 1 

### I 2 

### I 3 1 2 3 34.19 34.19 34.13 32.50 3225 32.50 32.50 3225 32.25 32.75 32.50 32.50 34.31 34.13 34.25 32.75 32.50 32.63 32.75 32.50 32.75 32.75 32.50 32.75 34.00 33.88 34.25 32.25 3225 3250 3238 32.25 32.75 32.50 32.00 32.50 2225 22.39 22.19 20.75 20.50 20.60 20.75 20.75 20.75 20.75 20.63 20.75 22.50 22.36 22.50 2i.13 20.88 21.00 21.00 20.88 21.00 2i.i3 20.88 21.00 22.31 2225 22.38 20.50 20.63 20.75 21.88 20.50 20.88 20.63 20.63 20.75

Max Shrinkage 8.1% 8.4% 7.6% 6.7% 7.9% 6.7% 7.6% 7,8% 7.3% Average Shrinkage 5.9% 6.3% 6.0% 4.9% 6.2% 5.7% 5.6% 6.2% 5.8% Unwashed Sell Set2 Set3 1 

### 1213 1 121 3 11 2 13 1 12 

### IT 33.75 34.06 33.75 31.75 31.50 3125 31.60 31.50 31.50 31.38 31.50 .31.50 33.88 33.94 34.00 31.75 31.88 31.63 31.75 31.88 31.75 31.63 31.75 31.75 34.00 33.75 34.13 31.62 31.50 31.75 31.75 31.75 31.50 31.50 31.75 31.50 21.88 22.13 2i.75 20.50 2025 20.38 20.25 20.38 20.50 2025 20.38 20,63 22.25 22.00 22.13 20.50 20.63 20.63 20.50 20.63 20.50 20.38 20.50 20.50 2i.88 22.00 22.25 20.38 20.50 20.25 20.50 20.50 20.50 20.13 20.50 20.38

Max Shrinkage 7.9% 8.5% 9.0% 7.9% 7.9% 7.9% 8.4% 7.9% 8.4% Average Shrinkage 6.7% 7.0% 7.2% 6.9% 6.8% 7.0% 7.5% 6.9% 7.0%

Unwashed Set4 SetS Set6 1 2 3 1 

### I 2 3 1 

### I 2 

### I 3 1 2 3 34.19 34.19 34.13 32.50 3225 32.50 32.50 3225 32.38 32.50 32.26 32.50 34.31 34.13 34.25 32.50 3225 32.75 32.53 32.38 32.75 32.63 32.50 32.63 34.00 33.88 34.25 32.25 32.38 32.50 32.13 3225 32.50 32.38 32.25 32.75 2225 22.38 22.19 20.75 20.78 20.75 20.63 20.50 20.63 20.75 20.50 20.63 22.50 22.38 22.50 2i.00 20.75 20.88 21.00 20.75 21.00 21.00 21.00 21.00 22.31 22.25 22.30 20.75 20.25 20,88 20.50 20.75 20.98 20.88 20.75 20.75

Max Shrinkage 7.0% 9.0% 7.2% 8.1% 8.4% 7.0% 6.7% 8.4% 7.3% Average Shrinkage 6.0% 6.5% 5.8% 6.2% 6.3% 5.8% 5.7% 6.1% 5.8% UlIwashSd Snl1 SetS SetS I 

### I 2 I 2 3 I 

### I 2 

### I 3 11 12 I 3 33.75 34.06 33.75 71 50 31.39 3125 3i.75 31.38 3i25 31.63 3i.50 3i.50 33.88 33.94 34.00 31.S0 31.70 31,83 31.50 31.75 31.63 31.50 3i.75 31.50 34.00 33.75 34.13 31.00 51.70 3'I,75 31.60 31.75 31.75 31.50 31.75 31.75 21.88 22.13 21.75 20.60 20,33 20.38 20.50 20.38 2038 20.50 20.38 20.25 2225 22.00 22.13 20.60 20.50 2063 20.50 20.50 20.63 20.38 20.50 20.50 21.88 22.00 22.25 25.50 21175 2335 20.50 20.75 20.38 20.38 20.63 20.38

Max Shrinkage 7.3'7. 7.5% 3 7.9% 7.9% 8.4% 8.4% 7.9% 

# ar Average Shrinkage ..5'' .ii3 ." ". 6.8% 6.8% 7.1% 7.0% 6.8% 7.3%

## Table 2. Horizontal Axis Preconditioning Shrinkage

_ Lot 4 UnwsIied Waih 1 

# 1 Wash 2



### 1 12 

# L3 1 12 3 )1 

### ] 21 3 Hi 34.25 34.25 34.25 33.13 33.25 33.25 32.88 32.88 32.88 H2 34.25 34.13 34.25 33.00 33.00 33.38 32.88 32.63 33.00 H3 34.25 34.00 34.13 33.00 32.88 33.38 32.75 32.63 32.88 Vi 22.25 22.25 22.25 21.75 21.88 21.38 21.63 21.50 21.38 V2 22.38 22.25 22.38 21.88 21.75 21.75 21.63 21.50 21.50 V3 22.38 22.13 22.25 21.75 21.63 21.75 21.50 21.25 21.50 Max Shrinka 3.6% 3.3% 3.9% 

# 1 4.4% 4.4% 4.0% Average Shrinkage 3.0% 2.6% 2.8% 3,7% 3.9% 

### 3.8% Lot 5 Unwashed Wash I 

### I Wash 2



### 1 1213 1 12 13 1 121 3 HI 34.00 33.88 33.75 32.38 33.13 32.25 32.50 32.75 32.88 H2 33.75 33.88 33.75 32.25 33.13 32.25 32.25 32.88 32.88 H3 33.75 34.00 33.75 32.50 33.00 32.38 32.13 32.75 32.75 VI 21.88 21.88 22.00 21.25 20.88 21.38 21.13 20.75 21.63 V2 21.75 21.63 22.00 21.25 20.75 21.25 21.00 20.50 21.63 V3 21.75 21.75 22.00 21.13 20.75 21.25 21.00 20.63 21.50 Max Shrinka 4.8% 4.6% 4.4% 4.8% 5.2% 3.0% Average Shrinkage 3.5% 3.4% 3.8% 4.0% 4.2% 2.3% Lot 4 HI H2 H3 Vi V2 V3

Lot 5 HI H2 H3 Vi V2 V3 

### Wash 3 Wash 4 Wash 5



### 1 121 3 1 

### [21 3 1 121 3 3275 32.75 32.88 32.63 32.75 3275 32.75 32.63 32.75 

### 32.75 32.63 .32.75 32.63 

### 32.50 32.75 

### 32.63 32.38 32.75 32.75 32.50 32.75 32.50 32.50 

### 32.75 32.75 32.38 32.75 21.38 21.38 21.25 21.25 2125 2100 21.13 21.13 21.13 2163 21 38 

### 2138 21.36 2125 21.25 21.25 21.25 21.25 21.25 21.13 

### 21.25 21.25 21.00 21.13 21.25 21.00 21.25 

### 5.0% 4.5% 4.5% 5.1% 5.1% 5.6% 5.1% 5.1% 

### 5.1% 4.2% 4.3% 4.3% 4.8% 4.6% 4.7% 4.8% 4.9% 4.6% 

### Wash 3 Wash 4 Wash 5 1 

### I 2 I 3 1 

### 1 2 

# 1 3 1 

### I 2 I 3 32.50 32.88 32.13 32.25 32.50 32.13 32.13 32.63 32.13 32.13 32.75 32.13 32.00 32.50 32.13 32.13 32.63 32.00 32.13 32.75 32.13 32.25 32.50 32.25 32.13 32.50 31.88 21.13 20.75 21.13 21.13 20.63 21.13 21.13 20.88 21.00 21.00 20.50 21.25 21.00 20.50 21.13 20.88 20.50 21.13 21.00 20.50 21.00 20.88 20.50 21.00 20.88 20.50 20.88 4.8% 5.7% 4.6% 5.2% 5.7% 4.8% 

# 1 5.5% 5.7% 5.6% 

### 4.1% 4.3% 4.4% 4.3% 4.9% 4.4% 4.4% 4.6% 4.9%

4

## Table 3. Vertical Axis Preconditioning Shrinkage Lot 4 Hi H2 H3 

### vi V2 V3

Lot 5 Hi H2 H3 

### vi V2 V3

Lot 4 Hi H2 H3 

### vi V2 V3

Lot 5 Hi H2 H3 

### vi V2 V3 Unwashed Wash i Wash 2



### i i 213 i i 21 3 1 121 3 34.i9 34.i9 34.i3 33.00 33.00 33.00 33.i3 33.00 33.00 34.3i 34.13 34.25 33.i3 33.00 33.25 33.13 33.00 33.i3 34.00 33.88 34.25 32.88 32.75 33.i3 32.75 32.88 33.00 22.25 22.38 22.i9 2i.50 2i.68 21.38 2i.50 2i.38 21.38 22.50 22.38 22.50 22.00 2i.75 2i.88 21.75 21.50 21.75 22.3i 22.25 22.38 2i.25 2i.38 2i.63 2i.38 21.25 21.50

Max Shrinkage 4.8% 3.9% 3.7% 4.2% 4.5% 3.9% Average Shrinkage 3.4% 3.3% 3.2% 3.5% 3.8% 3.5%
Unwashed Wash i Wash 2 

### 1 1213 1 121 3 1 121 3 33.75 34.06 33.75 32.75 32.63 33.00 32.50 32.75 32.50 33.88 33.94 34.00 32.88 32.88 32.88 32.63 32.63 32.75 34.00 33.75 34.i3 32.75 32.75 32.63 32.50 32.44 32.63 21.88 22.13 21.75 20.75 20.63 20.88 20.63 20.75 20.63 22.25 22.00 22.13 20.88 20.75 20.63 20.63 20.75 20.63 21.88 22.00 22.25 20.75 21.00 20.88 20.50 20.75 21.00

Max Shrinkage 6.2% 6.8% 6.8% 7.3% 6.2% 6.8% AverageShrinkage 4.3% 4.6% 4.5% 5.2% 4.9% 4.9%
Wash3 Wash4 Washs 

### 1 121 3 1 121 3 i 

### 121 3 32.75 32.75 32.88 32.75 32.88 32.88 32.75 32.75 32.88 33.00 32.88 33.00 32.88 33.00 33.00 33.00 33.00 33.00 32.75 32.50 32.88 32.50 32.75 33.00 32.75 32.63 33.00 21.25 21.25 21.25 21.25 21.38 21.13 21.25 21.25 21.13 21.50 21.50 21.50 21.50 21.50 21.38 21.50 21.38 21.50 21.00 21.00 21.25 21.13 21.00 21.25 21.13 21.00 21.25 5.9% 5.6% 5.0% 5.3% 5.6% 5.0% 5.3% 5.6% 5.0% 4.4% 4.4% 4.2% 4.5% 4.1% 4.3% 4.3% 4.4% 4.2%

Wash3 Wash4 Wash5 

### 1 121 3 1 121 3 1 121 3 32.00 32.13 32.50 32.00 32.13 32.13 32.00 32.50 32.13 32.38 32.50 32.50 32.38 32.50 32.25 32.25 32.38 32.38 32.50 32.38 32.25 32.38 32.50 32.i3 32.38 32.13 32.50 20.50 20.50 20.63 20.50 20.63 20.63 20.50 20.75 20.38 20.75 20.75 20.50 20.75 20.75 20.63 20.63 20.75 20.50 20.63 20.88 20.75 20.50 21.00 20.56 20.63 20.75 20.88 6.7% 7.3% 7.3% 6.7% 6.8% 7.6% 7.3% 6.2% 7.3% 5.5% 5.4% 5.5% 5.6% 5.1% 5.9% 5.7% 5.3% 5.7%

## Appendix B: Summary of Extractor Based Test Data

## Table 4. ADL Extractor Test Results (September-December, 1999) RMC TestinowIOriginal Extractor (20 minute warm soat 10 minute snin\

_ TI1A COlA TuB CG1B ASG T11920DC WashedTlDC StrippedASG TI2A CG2A TlDCsttlpped ADLScotchgard

4.71b. 4.71b. 4.71b. 4.71b. 4.71b. 4.7lb. 4.71b. 4.71b. 4.7Ib. 4.71b. 4.7lb. 4.71b. 100 52.6% 65.3% 52.9% 65.8% 44.5% 44.6% 53.9% 45.5% 53.3% 68.2% 52.2% 37.2% 300 36.5% 41.1% 34.5% 40.2% 27.9% 30.5% 34.2% 29.4% 34.7% 41.5% 34.2% 26.0% 500 29.5% 33.4% 30.1% 33.2% 23.6% 27.3% 29.2% 24.2% 30.0% 32.5% 30.1% 22.8% Sum Time Testing (20 Mm Warm soak( Time Tl1-5.7B Tt1A* A T12 TIl 

## f Til T12 115g 300g 5)t 5.7 lb. 4.7 lb. 8.4 lb. 8.4 lb. 8.4 lb. 8.4 lb. 8.4 lb. 2 55.5% 57.9% 47.9% 53.3% 53.7% 39.6% 38.5% 4 53.4% 55.7% 43.5% 49.9% 51.0% 35.8% 35.0% 6 51.3% 52.8% 41.1% 48.3% 49.3% 34.5% 33.2% 10 48.4% 52.1% 39.1% 45.8% 47.4% 33.4% 32.0% 15 47.3% 50.9% 37.2% 45.9% 45.1% 32.1% 30.9% 20 47.7% 50.2% 36.2% 44.8% 45.6% 31.5% 30.2% 25 48.0% 52.3% 36.1% 45.7% 46.3% 31.3% 30.6% Shrink Factor (Tt lot 2( Vertical Horizontal As received 33.88 22.00 Prewashed 32.75 21.00 After 45 washes 32.00 20.31 *Original Extractor oak Tini- Testino (10 minute snint RMC Taxtinn with4winuta xnin(20 winut wurw nukt time TI 1 Warm TI I Cold* TI 1 Warrn* TI 1 Cold* TI 1 Cold

115g 

### I 300g 4.7 lb. 4.7 lb. 4.7 lb. 4.7 lb. 4.7 lb. 10 51.8% 55.9% 34.7% 36.8% 37.0% 20 51.1% 57.1% 34.8% 34.5% 60 52.0% 55.2% 34.4% 36.0% 36.5% 120 56.1% 56.2% 36.2% 16 Hours 55.7% 56.2% 34.9% 36.7%

(washer) (washer) (tub) (washer) (tub) TIl T12 T13 weight 8.4 lb. 8.4 lb. 8.4 lb. 50 55.7% 54.8% 55.8% 100 50.8% 50.8% 50.7% 200 40.9% 40.4% 41.1% 300 35.7% 34.6% 35.6% 500 30.0% 29.1% 29.8%

KMt.l5U 9W/OOCK cxtractor tu minute soaK, ]5 minute spinu

__ TIl Warm T12 Warm CO Warm g 

### I Ttl Cold T12 Cold TIl Warm Tt2 Warm T13 Warm T13 Cold •ht 8.41b. 8.4lb. 8.41b. Weight 8.4lb. 8.4mb. 8.41b. 8.41b. 8.41b. 8.41b. 100 46.5% 44.4% 57.2% 50 52.8% 51.7% 50.6% 50.2% 51.4% 53.3% 100 46.1% 45.0% 100 48.3% 47.6% 46.5% 44.7% 45.9% 49.7% 200 37.4% 36.2% 44.2% 200 38.2% 37.0% 37.4% 36.1% 36.4% 38.0% 200 37.3% 35.9% 300 33.4% 32.3% 33.1% 31.3% 31.7% 33.1% 300 33.1% 31.2% 36.9% 500 27.3% 26.7% 27.1% 26.2% 26.7% 27.4% 300 31.4% 31.3% 800 24.1% 23.4% 22.6% 23.2% 23.3% 24.5% 500 27.1% 26.2% 29.3% 800 22.6% 23.2% 25.2% Lensnd, Title Cloth TI1A Eextile Innovators Lot 1920 TIl B TIl Tl1-5.7B TI2A _____________________________________ Eextile Innovators Lot 1967 T12 ASG __________________________________ IIiance (Scotch Guarded) Stripped ASG A

______________________________ TII92ODC extile Innovators Lot 1920 (Dry Cleaned) Washed TIDC TIDC Stripped CG1A _____________________________________

Cotton Goods Lot I CG1 B

____________________________ CG2A Cotton Goods Lot 2 AOL Scotchguard extile Innovators Lot 1920 (Scotch Guarded)

### Table 5.ADLWasher Testing

ADLLot 3

_

_

_

_ Warm&tk(1fl() F)J Ci. Sr)k (0F 

# c inSpiit4 Mn

## SDiflI lbMiii5,3111] 

### 4MIII Spui

_______ 

### 51.4% 55.8% 52.2% 59.1% 50 49.6% 55.8% 53.3% 

# 1 58•9Y1 50.2% 55.5% 53.1% 58.9%

____ 

### 36.4% 41.1% 38.0% 43.5% 200 35.7% 40.6% 37.9% 43.0%

34.9% 39.6% 37.9% 42.8%

______ 

### 29.1% 32.1% 30.2% 35.3% 350 29.9% 

### 33.6% 30.7% 36.0%

______ 

### 29.9% 33.5% 31.1% 36.1% 

## ADL Lot4 

## coF) 

# L 15 Mm SpIni 4 Mn Spinhl 15 Mm Spin 4 Mn Spin

_________ 

### 56.2% 61.5% 58.8% 64.6% 50 57.2% 61.5% 58.0% 

### 64.4%

572/o 61.1% 59.8% 

### 63.2%

______ 

### 42.2% 46.3% 43.1% 47.9% 200 42.6% 45.6% 42.2% 49.0%

45.5% 43.4% 40.5% 

# I 48.5%

____ 

### 342/a 37.5% 35.5% 41.5% 350 34.2% 37.8% 35.4% 

### 40.3%

______ 

### 34.1% 38.5% 35.4% 41.0%



## Vsh-B&IRvCTesng ADL Lot5 r - 

### Warm Soak (1 00 F) I Ccd Soak (60 F) 15 Mn Spin 4Miii

# scri1 15Mni Spin]4Mn Spin 

### 54.8% 

# 1 58.1% 

# 1 56.4% 61.4% 50 55.4% 

# I 59.4% 55.4% 61.9% 

### 53.1% 58.7% 55.8% 62.4%

______ 

### 40.1% 44.6% 41.7% 46.6% 200 39.5% 

### 44.4% 40.0% 47.6%

39.1% 43.2% 42.4% 

### 46.3%

______ 

### 32.8% 36.6% 35.1% 38.6% 350 32.2% 36.4% 33.0% 38.7%

____ 

### 32.1% 35.2% 33.7% 39.0% 

## ADL LotCG SonjF Qili &3k 

### G Spn 15Mir 1

### Miii Spin 15Mn Spin 4

### Mn Spin 63.4% 

# I 70.0% 

### I 65.0% I 74.6% 50 62.4% I 70.2% 

## I 67.0% 

# [ 75.6% 62.9% 70.9% 65.5% 75.7%

# J

_______ 

### 44.2% 47.9% 44.1% 48.4% 200 42.4% 46.5% 43.8% 51.3%

41.2% 46.2% 43.9% 499%

_____ 

### 33.3% 39.0% 35.2% 39.9% 350 31.8% 36.6% 34.5% 41.1%

____ 

### 31.6% 

### 36.1% 345% 39.8%



## Vemc sMSdiR)3

_____ 

### Eizxitz

### Ads MaTh

## ine Tt# _____



### PLc3jAIiLc4 A1L5]/LLctCE' 

## 1Ld ____41)L 

### 54% 5%

# I 59.4% 70.8% 47.1% 52.7% 50.2% 60.0% 

# I

_______ 

### 2 50% 2%

# I 59.6% 72.8% 44% 

### 50.9% 

# [ 50.1%

- 

### 59.3% 

## 3 56.1%

# I 61.7% 60.0% 72.1% 

## 4a6% I 54.3% 52.0% 6ü0% 

## Ae 58% 621%

# ( 59.7% ( 71.9% 48.0% 

## 52.6% I 50.8% 59.8% 

## Coneded

- 

# I 563% 562% 57.8% 

# li_- 47.1%

# 1 47.5% 481%

# Appendix C: Procedure for UsingRMCCorrection Factors in Clothes Washer Efficiency Tests This document outlines a procedure for measuring, specifying, and using a remaining moisture content (RMC) correction factor to improve accuracy and consistency in clothes washer efficiency measurements. In order to produce reasonably accurate efficiency measurements according to the J 1 test procedure for clothes washer efficiency, it is necessary to consistently measure the remaining moisture content in a test load. It has been found to be rather difficult to specify the cloth in such a manner that RMC measurements are consistent for different production runs of test clothes. Different clothes that satisfy the basic specifications on fiber content, weight, and weave may still vary in the RMC measurements by 10% absolute error in the RMC value. To resolve the inconsistent moisture-retaining properties of the clothes, a specific RMC specification has been formulated for the test cloth. This specification details the RMC values that the cloth should have under a series of water extractor tests, where the cloth is first soaked in water, and then spin-dried in a standard test extractor. The draft RMC specifications of the cloth indicate that the test cloth should attain standard RMC values in the extractor tests within 2% absolute error tolerance. In practice it is difficult to produce cloth that fits the RMC specification. This can result in test cloth supply delays and increased test cloth costs for test cloth and for testing. To resolve this practical production problem, we propose an RMC correction procedure that can be used with non-standard clothes to predict or estimate standard RMC values in clothes washer efficiency tests. The correction procedure consists of performing RIvIC measurements on batches of test cloth, and using a linear fit to relate non-standard RMC values to standard RMC values. When the linear fit is calculated, a goodness of fit measure allows an evaluation of whether the non-standard cloth can predict standard RMC values within the 2% required error tolerance.
factors.Below, we describe the procedures for the calculation and use of the RMC correction

Measurement of ClothRMCProperties The need for an RMC correction factor and its equation is determined from the measurements of the water retention properties of the test cloth. These measurements are madein a series of water extraction tests. In these tests the test cloth is soaked in water and then spindried in a standard specified extractor. At the end of the spin cycle the remaining moisture content of the cloth is measured and compared to a series of standard values.
9

## The measurement of the test cloth moisture retention properties will consist of spinning

an 8.4 pound load of cloth in an extractor after soaking the cloth in water for 20 minutes. Four tests will be performed at three different spin rates. The three tests will consist of a warm soak followed by a short spin, a warm soak followed by a long spin, and a cold soak followed by a long spin. A warm water is defined as being at 100F, cold water is 60F, a short spin is four minutes, and a long spin is 15 minutes. The three spin speeds are defined by the mean g-force they produce. Low spin speed is 100g. medium spin is 200g, and high spin speed is 300g. These spin speeds were chosen as to the minimum needed to represent the range of spin conditions that may be found in a residential clothes washers. The standard RMC values for these tests are as follows: Table 6. Remaining Moisture Content for Standard Test Cloth G

-

## Force

__________________

## Warm Soak & Short

Spin Warm Soak & Long

Spin Cold Soak & Long

Spin 100 g 50.7% 45.9% 

## 49.7% 200 g 41.1% 36.4% 38.0% 300 g 35.6% 

## 3 1.7% 33.1% (These standard values are those obtained from the third batch of test cloth that was tested in the ADL RMC tests. It is labeled ADL3 in the RMCdata.xls spreadsheet.) 

## For each new batch of cloth, three tests are performed for each set of test conditions, and the average RMC is measured for each test condition. For each batch of test cloth the deviation between the new production batch, and the standard is measured. This deviation is measured as the root mean square between the set of measured RMC values and the set of standard RMC values. If this absolute deviation is below 2%, then no correction factors are needed in MEF tests using that batch of cloth. If the absolute root-mean-square (RMS) difference between the cloth RN'IC values and standard RMC values is above 2%, then correction factors may be applied when using the cloth to test the MEF of a clothes washer.
Calculation and Use ofRMCCorrection Factors. To calculate the RMC correction factor for a batch of cloth, one takes the set of average measurements from the cloth batch tests (RMC-cloth) and performs a linear least-squares fit to relate the standard RMC (RMC-standard) using the cloth RMC:

RMCSTANDARD A * RMC CLOTH + B 

## Eq.! where A and B are coefficients of the linear least squares fit. If the root mean square value of:
10

### {STESTS[((RMCSTANDAI

-

## A *

## DMf

-

## B)2)/(N-2)]}"2<

## 2% Eq. 2 '-'CLOTH-i 

## where N is the number of distinct tests (9), where a sum is taken over all of the different tests, whereRMCSTANDAPJI is the RMC standard value for the i-th test, andR MC CLOTH is the average measured RMC value for the i-th cloth test. Under such conditions, the test cloth can be used for MEF tests as long as a correction factor is applied. The above equation is an empirical measure that the estimates using the non-standard cloth can accurately reproduce standard RMC values within 2%. 

## The equation for the RMC correction factor is as follows for all MEF tests using the production batch of cloth:
RMCCORRECTION =

## (A-i) *

### DMrI +

## B ' '-'CLOTH 

## Eq.3 This correction factor is simply added to any RMC measurement used in the MEF test procedure to correct for the non-standard behavior of that particular batch of cloth. Example Measurement and Use ofRMCCorrection Factor In this example, we show how the RMC measurements using a cloth that does not reproduce the standard RMC values can reproduce RMC results for a standard cloth by using the RMC correction factor described above. The particular case we use is the ADL4 cloth, for which we have test data from ADL's RMCdata.xlsspreadsheet. For this cloth, we have test results for warm soak and short spin, along with warm soak long spin. We do not have data for this cloth for cold soak long spin, so we won't cover that case. Table7.Test results for the ADL4 cloth G-Force Warm Soak & Short Spin Warm Soak & Long Spin 100 g 57.7% 52.7% 

## 200 g 46.3% 42.4% 300g 40.2% 36.1% Note that the ADL4 cloth produces RMC values that are consistently above the standard values by more than 2%.

11

## Using Excel, plotting RMC_standard vs. RMC_cloth and adding a trend line to the data gives the

linear fit. The results are: A=0.88 B
=

## 0.04 This means that the equation for the correction factor is
RMCCORRECTION =

## 0.04

-

## 0.12 *

### DM CLOTH 

## Eq.4 Now test this relation by seeing how well it predicts the behavior of the test cloth for a variety of spin speeds: Table 8. Test Cloth Results at Different Speeds G-Force Test RMCADL4 Correction RMCEst RMC_ADL3 50g Warm-Short 61.5 -7.6 53.9 55.8 500 g Warm-Short 34.1 -4.2 29.9 29.8 50 g Warm-Long 56.3 -6.9 49.3 51.4 500 g Warm-Long 30.4 -3.7 26.7 26.7 800g Warm-Long 26.8 -3.3 23.5 23.3 In the above example the root-mean-square deviation between the estimates and the measurements from the standard cloth are4.5%before the correction is applied and 1.3% after the correction is applied. While the correction method works very well for high g forces, for very low spin speeds (and low g-force) it works less well. The correction method decreases the deviation from the standard RMC values by over 70% in this example. In the above table "Correction" is the correction factor, and "RMC_Est" is the corrected RMC estimate, and "RMC ADL3" is the RMC estimate obtained from a cloth that fits the standard specifications. CONCLUSION There exists a procedure for testing cloth batches and computing RMC correction factors forclothes that violate the RMC specifications by more than 2%. This allows us to utilize nonstandard test clothes to predict RMC values for standard test clothes under a wide range of conditions. This procedure (utilizing an RMC correction factor) should produce repeatable MEF values even when cloth RMC differences are greater than 2% under the same test conditions. This procedure involves applying a relevant correction factor to the RMC values before calculating the MEF.
12

## Appendix D: Lot 4 & 5 Correction Curves

This appendix consists of an excel spreadsheet containing the finalized correction curves and data for Lots 4 and5. The sheets show the test data, corrected data, RMS error, and washing machine verification results for each lot. The correction curve works remarkably well with both the extractor and washing machine test data. The curve fit of the data is also excellent, with the RMS error less than 1% in both cases.

13

## Table 9. ADL Lot 4 Extractor Test Data

G 

# I Wrii Stjc IIf 

### j1 Miri3piJ 1 Mr iiiri 1: P1iri Ei''i _____________ 4 Mir Spin 56.2% -

61.5% 58.8% 64.6% 50 57.2% 61.5% 58.0% 64.4%

_____________ 57.2% 61.1% 59.8% 632%

42.2% 46.3% 43.1% 47.9% 200 42.6% 45.6% 42.2% 49.0%

______________ 405% 45.5% 43.4% 485%

34.2% 37.5% 35.5% 41.5% 350 34.2% 37.8% 35.4% 40.3%

34.1% 38.5% 35.4% 41.0% Test Point Lot 3 Lot 4

51.4% 56.2% -__________ Warm, 15, 50 49.6% 57.2%

50.2% 57.2%

______________ 36.4% 42.2% __________

- Warm, 15, 200 35.7% 42.6% 37.4%

______________ 34.9% 40.5% 35.4%

29.1% 34.2% 29.3% Warm, 15, 350 29.9% 34.2% 29.3%

29.9% 34.1% 29.2%

______________ 55.8% 61.5% 55.6% Warm, 4,50 55.8% 61.5% 55.6%

______________ 55.5% 61.1% 55.3%

41.1% 46.3% 41.0% Warm, 4, 200 40.6% 45.6% 40.3%

39.6% 45.5% 40.2%

______________ 32.1% 37.5% 32.5% Warm, 4, 350 33.6% 37.8% 32.8%

33.5% 38.5% 33.5%

______________ 52.2% 58.8% 53.0% Cold, 15, 50 53.3% 58.0% 52.3%

_______________ 53.1% 59.8% 54.0%

38.0% 43.1% 37.9% Cold, 15,200 37.9% 42.2% 37.0%

______________ 37.9% 43.4% 38.2%

30.2% 35.5% 30.6% Cold, 15, 350 30.7% 35.4% 30.5%

_____________ 31.1% 35.4% 30.5%

59.1% 64.6% 58.6% Cold, 4, 50 58.9% 64.4% 58.4%

______________ 58.9% 63.2% 57.3%

43.5% 47.9% 42.5% Cold, 4, 200 43.0% 49.0% 43.6%

42.8% 48.5% 43.1%

______________ 35.3% 41.5% 36.3% Cold, 4, 350 36.0% 40.3% 35.2%

_____________ 36.1% 41.0% 35.9% Corrected Lot 3 Average Lot 4 Aven 50.5% 50.4% 56. 51.5% 51.5% 37.0% 35.7% 41.

29.6% 34.2%
55.7% 61.4%
40.4% 45.8%
33.1% 37.9%
52.9% 58.9%
37.9% 42.9%
30.7% 35.4%
59.0% 64.1%
43.1% 48.5%
35.8% 40.9%


### Washing Machine Verification

Vertical Axis Machine Lot 3 Lot 4 Corrected

Trial 1 55.4% 62.0% 56.1% Trial 2 56.0% 61.5% 55.7% Trial3 56.1% 61.2% 55.3% Horizontal Axis Machine Lot 3 Lot 4 Corrected

Trial 1 47.1% 53.6% 48.1% Trial 2 49.3% 54.3% 48.7% Trial 3 48.6% 54.5% 48.8% 

### RMS Error 0.50% Root Mean Square Error Calculation Residual N = 12 6.24205E-06 A = 0.967 8.49531E-06 B = -0.038 1 .55367E-06 2.51011E-07 3.0544E-08 3.42744E-07 6.62548E-07 6.201 76E-07 4.10603E-07 6.62922E-06 1.07 147E-08 3. 05084E-09



### 14

## Table 10.ADL Lot 5Extractor Test Data Warm1Ul)l)

_________

____________________

## J S Sptn 4 Spin Spin 1P4nShin 54.8% 58.1% 56.4% 61.4% 50 55.4% 59.4% 55.4% 61.9%

________________ 53.1% 58.7% 55.8% 62.4% 40.1% 44.6% 41.7% 46.6% 200 39.5% 44.4% 40.0% 47.6%

________________ 39.1% 43.2% 42.4% 46.3% 32.8% 36.6% 35.1% 38.6% 350 32.2% 36.4% 33.0% 38.7%

32.1% 35.2% 33.7% 39.0%
Test Point Lot3 Lot5 Corrected Lot3 Average Lot5 Ai

51.4% 54.8% 51.4% Warm, 15,50 49.6% 55.4% 52.0%

________________ 50.2% 53.1% 49.7% 36.4% 40.1% 36.8% Warm, 15,200 35.7% 39.5% 36.2%

34.9% 39.1% 35.8%

________________ 29.1% 32.8% 29.6% Warm, 15,350 29.9% 32.2% 29.0%

29.9% 32.1% 28.9%

________________ 55.8% 58.1% 54.7% Warm,4,50 55.8% 59.4% 56.0%

___________ 55.5% 58.7% 55.3% 41.1% 44.6% 41.3% Warm, 4, 200 40.6% 44.4% 41.1%

39.6% 43.2% 39.9%

_________________ 32.1% 36.6% 33.4% Warm,4,350 33.6% 36.4% 33.2%

___________ 33.5% 35.2% 3Z0% 52.2% 56.4% 50% Cold, 15,50 53.3% 55.4% 52.0%

_________________ 53.1% 55.8% 52.4% 38.0% 41.7% 38.4% Cold, 15,200 37.9% 40.0% 36.7%

_________________ 37.9% 42.4% 39.1% 30.2% 35.1% 31.9% Cold, 15,350 30.7% 33.0% 29.8%

____________ 31.1% 33.7% 30.5% 59.1% 61.4% 58.0% Cold,4,50 58.9% 61.9% 58.5%

________________ 58.9% 62.4% 59.0% 43.5% 46.6% 43.3% Cold,4,200 43.0% 47.6% .44.3%

_________________ 42.8% 46.3% 43.0% 35.3% 38.6% 35.3% Cold,4,350 36.0% 38.7% 35.4%

__________________ 36.1% 39.0% 35.7% 50.4% 54.4%

35.7% 39.6%
29.6% 32.4%

55.7% 58.7%

40.4% 44.1%

33.1% 36.1%

52.9% 55.9%
37.9% 41.4%

30.7% 33.9%

59.0% 61.9%

43.1% 46.8%

35.8% 38.8% 

### vvasning acnune venticaflon

Vertical Axis Machine Lot3 Lot5 Corrected

Thai1 55.4% 59.4% 56.0% Trial 2 56.0% 59.6% 56.2% Trial3 56.1% 60.0% 56.6% Horizontal Axis Machine Lot3 Lot 5 Corrected

Thai 1 47.1% 50.3% 47.0% Trial 2 49.3% 49.8% 46.5% Trial 3 48.6% 51.9% 48.5% 

## RMSError= 0.44% Root Mean SquareError Calculation

7



### 15

### 65% 60% 55% 50% 45% • 40% (I) 

### 35% 30% 25% y=

### 0.967x

-

### 0.038

30% 35% 40% 45% 50% 55% 60% 65% Lot 4 RMC (%) 

## Figure 1. Correction Curve for Lot 4

16

### 65% 60%

- 

### 55% 0 50% C) 

### 45% V Co 0 -o 'if0 (0 Cl) 

### 35% 30% 25% y=

### 0.9975x

-

### 0.0319

30% 35% 40% 45% 50% 55% Lot 5 RMC (%) 

## Figure 2. Correction Curve for Lot5 bU7o bb7o



### 17

## APPENDIX D. MANUFACTURING COST ASSESSMENT

-BILL OF MATERIALS TABLE OF CONTENTS D.1 BILL OF MATERIALS (BOM)

......................................... 

## D-1

..........................................

.............................................

....................................

...........................

.......................................

........................... 

## D.2 FABRICATION PROCESSES D-3 D.2. 1 Assembly Processes D-5 LIST OF TABLES Table D. 1 Major Manufacturing Processes D-3 

## LIST OF FIGURES Figure D.1 Manufacturing Cost Assessment Approach D-1 Figure D.2 Structured Bill of Materials D-2 Figure D.3 Fabrication Process Cycle Time Estimates D-4

D-i

## APPENDIX D. MANUFACTURING COST ASSESSMENT -BILL OF MATERIALS

The manufacturing cost assessment methodology used to evaluate the cost of increasing the efficiency of clothes washers is a detailed, component-focused technique for rigorously calculating the manufacturing cost of a product (direct materials, direct labor and some overhead costs). Figure D. 1 shows the three maj or steps in generating the cost of manufacturing clothes washers.

Raw I 

# Fabrication I Finished Materials 

# Processes Bill of Parts 

# Processes Figure D.l Manufacturing Cost Assessment Approach
D.1 BILL OF MATERIALS (BOM) The first step in the manufacturing cost assessment was the creation of a complete and structured bill of materials (BOM) from the disassembly of the two baseline and six high efficiency models. The washers were dismantled and each part was characterized according to weight, dimensions, material and quantity. The BOM incorporates all materials, components, and fasteners with estimates of raw material costs and purchased part costs. Assumptions on the sourcing of parts and in-house fabrication were based on industry experience, information in trade publications and discussions with manufacturers. Interviews and plant visits were conducted at maj or manufacturing facilities to ensure accuracy on methodology and pricing. Cost estimates for raw materials and purchased components were drawn from Arthur D. Little's manufacturing databases and supplemented with information obtained from manufacturer and supplier sources. Adjustments to the cost estimates for purchased parts and raw materials were made, as appropriate, to include price discounts typically available at the purchase volumes in question. Figure D.2 is a section from the structured bill of materials of one baseline clothes washer. This section of the structured bill of materials lists the part number (defined during disassembly), description, material category, sourcing category (fabricated or vended), quantity, dimensions, weight, percent of scrap in processing, and estimated material cost.

D-11.00 Tub & Basket Assembly Weight (lbs) PartNo. (Final Assy. 1388.00/1800.00)

-Description Category 

### V(?) # Width Thkns Length Steel Other Scrap Material Cost, $ % 1.01 Tub Plastic 1 22.5 0.09 22.5 5.520 3.31 1.03 WaterLevelBox Plastic 1 2.75 0.085 1.75 0.066 0.04 1.02 Tub to Suspension Seal Rubber 1 0.6 0.03 5.2 0.036 0.02 1.07 Beach Tube Rubber 1 0.6 0.09 5.2 0.036 0.02 1.30 Basket Assembly 1.20 Basket Enameled Steel 1 20.5 0.055 18 13.500 15 4.13 1.22 Lint Collector Plastic 1 0.475 0.29 1.21 BasketBalancingRingw/Waterinit Plastic 1 20.5 0.09 2 1.400 0.84 1.49 Upper Agitator Assembly 1.50A Fabric Dispenser-Top Plastic 1 3.81 0.05 1.6 0.108 0.05 1.50B FabricDispenser-Cup Plastic 1 3 0.05 5.5 0.074 0.03 l.50C FabricDispenser-Bottom Plastic 1 4 0.06 5 0.148 0.07 1.51 Clutch Cover Plastic 1 3.25 0.05 0.9 0.030 0.02 1.52 Clutch CoverSeal Rubber 1 3.15 0.16 0.010 0.01 1.75 Lower Agitator Assembly 1.60 Bottom Agitator Bearing Plastic 1 2.95 0.26 0.016 0.01 1.59 Bottom Agitator Plastic 1 13.5 0.15 13 1.816 0.82 1.58 Upper/LowerAgitatorBearing Plastic 1 2.6 0.05 0.775 0.016 0.01 1.57 UpperAgitator Plastic 1 3.75 0.01 11.5 0.934 0.42 1.85 AgitatorClutchAssembly 1.56 ClutchBody Plastic 1 2.63 0.08 2.265 0.052 0.02 1.55 Ratchet Stops Plastic 4 0.4 0.15 0.9 0.016 0.01 1.54 ClutchBottomCover Plastic 1 1.75 0.05 0.4 0.006 0.00

Sub-Totals 22 13.50 10.79 10.12 

## Figure D.2 Structured Bill of Materials

D-2

## D.2 FABRICATION PROCESSES

After each detailed BOM was completed, the major manufacturing processes were identified. These processes are listed in Table D.1. 

## Table D.1 Major Manufacturing Processes Fabrication Finishing Assembly / Joining Fixturing Washing Adhesive Bonding Stamping / Pressing (Large, Medium,_Small) Powder Coating

___________________________ Spot Welding

___________________________ Brake Forming Enameling Seam Welding Cut & Shearing Deburring Integral Fastner (i.e. clinching) Machining Other Fasteners Injection Molding (Large, Medium, Small) Press Fitting

_____________________________ Casting _____________________________

___________________________ Inspection & Testing Information on equipment and tooling costs, typical processing cycle times, and materials used for fabrication were obtained from the ADL manufacturing databases. Equipment suppliers were contacted for further details concerning equipment capabilities and processing parameters (cycle times, scrap rates, etc.). The fabrication process cycle times were directly entered in the BOM and linked to the specific parts being fabricated. Each part had a processing time and labor cost assigned based on an overall labor rate. Figure D.3 contains an excerpt of the non-assembly processing times (seconds per process) associated with each component listed on the left. This section of the model has all the processes listed in Table D. 1, but for brevity a single page was presented in Figure D.2. Figure D.3 is from the equipment summary section, which includes total equipment and summarized labor requirements for each fabrication process. In addition to the process time and labor costs associated with fabrication, labor times for assembly associated with each part is included.

D-31.00 Tub & Basket Assembly Weight (Ibs) Part No. (Final Assy. 1388.00/1800.00)

-Description Fixturing Wash Powder Enamel Large Medium Small Brake Cut & Coating Baking Press Press Press Form Shear 1.01 Tub 1.0 1.03 WaterLevelBox 1.02 Tub to Suspension Seal 1.07 Beach Tube 1.30 Basket Assembly 1.20 Basket 40.0 4.0 10.0 30.0 2.0 1.22 Lint Collector 1.21 Basket Balancing Ring w/Water in it 5.0 1.49 Upper Agitator Assembly 1.50A Fabric Dispenser - Top 1.50B Fabric Dispenser - Cup 1.50C Fabric Dispenser - Bottom 1.51 Clutch Cover 1.52 Clutch Cover Seal 1.75 Lower Agitator Assembly 1.60 Bottom Agitator Bearing 2.000 1.59 Bottom Agitator 1.58 Upper/Lower Agitator Bearing 1.57 Upper Agitator 1.85 Agitator Clutch Assembly 1.56 Clutch Body 1.55 Ratchet Stops 1.54 Clutch Bottom Cover

Sub-Totals 62.0 4.0 10.0 30.0 3.0 

## Figure D.3 Fabrication Process Cycle Time Estimates

D-4

## D.2.1 Assembly Processes

In the final step of the cost assessment, assembly times and associated direct labor costs were estimated. Assembly cycle times were primarily derived from reversing the disassembly of the selected tear-down clothes washers. The assembly sequence was built into the structured BOM, culminating with final assembly, testing and packaging. Once the cost estimates for each machine were finalized, a detailed summary was prepared for relevant components, subassemblies and processes. The BOM and manufacturing process summaries provide detailed direct material, direct labor, indirect material, and investment costs. Indirect labor costs were estimated by subtracting the direct labor hours, determined from the bottom-up analysis, from the current average total labor hours per unit (1.8 hours). The current average labor content was derived from a top down analysis of several household laundry equipment manufacturing plants and conforms with data from the 1992 Census of Manufacturers.

D-5

## APPENDIX E. APPROACH FOR UNCERTAINTYANDVARIABILITY

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## E.1 INTRODUCTION E-1 E.2 UNCERTAINTY E-1 E.3 VARIAB1TJTY E-1 E.4 APPROACHES TO UNCERTAINTY AND VARIABILITY E-2

E-i

## APPENDIX E. APPROACH FOR UNCERTAINTY AND VARIABILITY

E.1 INTRODUCTION Analysis of an energy efficiency standard involves calculations of impacts, for example the impact of a standard on consumer life cycle cost. In order to perform the calculation, the analyst must first: 1) specify the equation or model that will be used; 2) define the quantities in the equation; and 3) provide numerical values for each quantity. In the simplest case, the equation is unambiguous (contains all relevant quantities and no others), each quantity has a single numerical value, and the calculation results in a single value. However, unambiguity and precision are rarely the case. In almost all cases the model and/or the numerical values for each quantity in the model are not completely known (i.e, there is uncertainty) or the model and/or the numerical values for each quantity in the model depend upon other conditions (i.e., there is variability). Thorough analysis involves accounting for uncertainty and variability. While the simplest analysis involves a single numerical value for each quantity in a calculation, arguments can arise about what the appropriate value is for each quantity. Explicit analysis of uncertainty and variability is intended to provide more complete information to the decision process.
E.2 UNCERTAINTY When making observations of past events or speculating about the future, imperfect knowledge is the rule rather than the exception. For example, the energy actually consumed by a particular appliance type (such as the average U.S. clothes washer) is not directly recorded, but rather estimated based upon available information. Even direct laboratory measurements have some margin of error. When estimating numerical values expected for quantities at some future date, the exact outcome is rarely known in advance.
E.3 VARIABILITY Variability means that different applications or situations produce different numerical values when calculating a quantity. Specifying an exact value for a quantity may be difficult because the value depends on something else. For example, the number of loads of laundry per week washed by a household depends upon the specific circumstances and behaviors of the occupants (e.g., number of persons, personal habits about how often clothes are washed, etc.). Variability makes specifying an appropriate population value more difficult in as much as anyone value may not be representative of the entire population. Surveys can be helpful here, and analysis of surveys can relate the variable of interest (e.g., laundry loads per week) to other variables that are better known or easier to forecast (e.g., persons per household).

E-1

## E.4 APPROACHES TO UNCERTAINTY AND VARIABILITY

Two approaches to consider uncertainty and variability are described here: scenario analysis and probability analysis. Scenario analysisuses a single numerical value for each quantity in a calculation, then changes one (or more) of the numerical values and repeats the calculation. A number of calculations are done, which provide some indication of the extent to which the result depends upon the assumptions. For example, the life cycle cost of an appliance could be calculated for energy rates of 2, 8, and 14 cents per kWh. The advantages of scenario analysis are that each calculation is simple; a range of estimates is used; and crossover points can be identified. (An example of a crossover point is the energy rate above which the life cycle cost is reduced, holding all other inputs constant. That is, the crossover point is the energy rate at which the consumer achieves savings in operating expense that more than compensate for the increased purchase expense.) The disadvantage of scenario analysis is that there is no information about the likelihood of each scenario. Probability analysisconsiders the probabilities within a range of values. For quantities with variability (e.g., electricity rates in different households), surveys can be used to generate a frequency distribution of numerical values (e.g., the number of households with electricity rates at particular levels) to estimate the probability of each value. For quantities with uncertainty, statistical or subjective measures, such as a triangular probability distribution, can be used to provide probabilities (e.g., manufacturing cost to improve energy efficiency to some level may be estimated to be $10+1- $3). The major disadvantage of the probability approach is that it requires more information, namely information about the shapes and magnitudes of the variability and uncertainty of each quantity. The advantage of the probability approach is that it provides the greatest information about the outcome of the calculations, that is, the probability that the outcome will be in any particular range is provided. Scenario and probability analysis provide some indication of the robustness of the policy given the uncertainties and variability. A policy is robust when the impacts are acceptable over a wide range of possible conditions.

E-2

## APPENDIX F. WATER AND WASTEWATER PRICES

...........................................

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## F.l SOURCE OF iNFORMATION F-i F.2 METHOD TO DETERMINE HISTORICAL WATER AND WASTEWATER PRICE TREND F-4 F.3 iMPLEMENTATION INTO LCC SPREADSHEET F-5 LIST OF TABLES Table F.1 Summary of Market Segments - Weighted RECS Households having a Washer

and a Dryer F-6 Table F.2 Marginal Prices and Escalation Rates F-lO LIST OF FIGURES Figure F.1 Location of 38 Cities Used for Determining Price Escalation F-2 Figure F.2 Annual Percent Change in Water & Wastewater Prices for 38 Cities (from 1986-

1998, in 1997$) F-3 Figure F.3 Annual Percent Change in Water-Only Prices for 38 Cities (from 1986-1998, in

1997$) F-4 Figure F.4 Flow Chart for Water Choice in LCC Spreadsheet F-8 FigureF.5 Water and Wastewater Price Trends F-9

F-i

## APPENDIX F. WATERANDWASTEWATER PRICES

F.1 SOURCE OF INFORMATION This appendix documents the methodology for estimating escalation rates of water and wastewater prices. The escalation of water and wastewater disposal costs, i.e., the rate at which water and wastewater prices are changing, was determined through an examination of trends in historical prices. The earliest historical data with both water and wastewater prices are from a survey commissioned by Ernst and Young in 1986.' A similar survey was conducted in 1998 by Raftelis2 These surveys for urban households include the fixed or minimum charge, water charge, and wastewater charge for 10 ccfa of water consumption. See Figure F. 1 for the locations of the cities used.

a ccf= hundreds of cubic feet(cu. ft. x 7.48 = U.s. gallons) F- 1

# Cities in Water Database

Seatt
oston etro Sacra ent a e ity e Moine rovidence Denve aha lana ol bus ewYork



## t. L is z -. - 

## altimore s as Wichita Ci 

### ati Los Ang s isviii

Riv rside ibuquer phis San Diego

- 

### tie Ro k

- 

### t! a DalIas ml 'Charleston Austin olie ando HonouIu Corpus Christi ami



## Figure F.1 Location of 38 Cities Used for Determining Price Escalation LBNL hadfourcriteria in composing the data set: 

## 1. The same utilities were used for each year that data was available. 2. Information on fixed charges was important to calculate a marginal price for water and wastewater. The fixed charges were subtracted from the bill for 10 ccf to get an approximate marginal price. 3. Both water and wastewater pricing for 10 ccf was needed for consistency between data sets. 4. The population served by the utility determined the weighting used. Figures F.2 and F.3 below show the distribution of price escalation rates for water and wastewater and water-only cases.

F-2

### F-3



## Figure F.2 Annual Percent Change in Water & Wastewater Prices for 38 Cities (from

1986-1998, in 1997$)