Table 5-3: Lot 4 Verification of Correction Factor in Clothes Washer

led I'ciii (Soak Teup.. 1'iine g 1 .o 3 L I\EC (Standard) Lol 4 1 MC 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

EE-RM-PET-100 COMMENT 88
Table 5-4: Lot 5 Verification 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 the Jl RN/IC test procedure, with each of TI lots 3 (the standard), 4 and 5. The RMC

tests were run three times for each clothes washer/test cloth lot combination. Tables 5-5 and 5-6

summarize the RMC measured in each of the machines using test cloth from TI lots 4 and 5,

respectively. In each table, these values are corrected to the TI lot 3 standard and compared to

the RMC values measured with test cloths from TI lot 3. With one exception, the corrected

RMC is less than 1% of the RMC measured with the standard (TI lot 3) test cloth.

5-8

EE-RM-PET-100 COMMENT 88
Table 5-5: 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 Lot 5 Correction 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

EE-RM-PET-100 COMMENT 88
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 Permalux 50/50 Momie 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 Permalux 5 0/50

-50/50 cottonlpolyester ± 4%

-5.60 oz/sq. yd. ± 5%

-Warp and filling yarns 15/1 ± 5% cotton count, open end spun yarn

-Thread counts of 61 x 54 (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

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
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 than 9.75 minutes, the wash time shall be not less than 9.75 minutes.

If the maximum available wash time in the normal cycle is less than 9.75 minutes, 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 (55.9 cm by 86.4 cm) before washing. The energy test cloth shall be

6-3

EE-RM-PET-100 COMMENT 88
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 (30.5 cm by 30.5 cm) and have been hemmed to 10 inches by 10 inches (25.4 cm by 25.4

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 Perform 5 complete 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 be 5.60 ounces per square yard (190.0 g/m2), +5 percent.

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 +5 percent 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

EE-RM-PET-100 COMMENT 88
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).

2.6.4.5.2 AATCC-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 section 2.6.5 three 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. Table 2.6.5 is 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 Extractor RMC Test 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. Box 5127, 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

EE-RM-PET-100 COMMENT 88
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 ±5 seconds.

2.6.5.3.4 Record 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.

2.6.5.3.6 The 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.

2.6.5.4 Repeat 2.6.5.3 using 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 Table 2.6.5. 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

EE-RM-PET-100 COMMENT 88
Table 2.6.6.1 Standard RMC values (RMCstandard)

G

RMC percent

_____________ 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 the 350g

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 Substitute RMCIOrr 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

EE-RM-PET-100 COMMENT 88
Appendix A: Test Data

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
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%

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
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%

EE-RM-PET-100 COMMENT 88
Appendix B: Summary of Extractor Based Test Data

EE-RM-PET-100 COMMENT 88
Table 4. ADL Extractor Test Results (September-December, 1999)

RMC Testino wI Original 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 with 4 winuta 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 9 W/ OOCK cxtractor tu minute soaK, ]5 m inute 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)

EE-RM-PET-100 COMMENT 88
Table 5. ADL Washer Testing

ADL Lot 3

_

_

_

_

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

c inSpiit 4 Mn SDiflI lb Miii 5,3111] 4 MIII 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 Lot 4

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%

40.5% I 45.5% 43.4% 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&I RvCTesng

ADL Lot 5

r

- Warm Soak (1 00 F) I Ccd Soak (60 F)

15 Mn Spin 4 Miii scri1 15 Mni Spin] 4 Mn 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 Lot CG

SonjF Qili & 3k G 15 Mir Spn 1 Miii Spin 15 Mn 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 s MSdiR)3 _____

Eizxitz Ads MaThine

Tt#

_____

PLc3j AIiLc4 A1L5] /LLctCE' 1Ld

____4

1)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%

EE-RM-PET-100 COMMENT 88
Appendix C:

Procedure for Using RMC Correction 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 Cloth RMC Properties

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 made

in 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

EE-RM-PET-100 COMMENT 88
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 of RMC Correction 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

EE-RM-PET-100 COMMENT 88
{STESTS[((RMCSTANDAI - A * DMf'-'CLOTH-i - B)2)/(N-2)]}"2 < 2% Eq. 2

where N is the number of distinct tests (9), where a sum is taken over all of the different tests,

where RMCSTANDAPJI is the RMC standard value for the i-th test, and R 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 + '-'CLOTH B 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 of RMC Correction 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.xls spreadsheet. 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.

Table 7. 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

EE-RM-PET-100 COMMENT 88
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

50 g 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 are 4.5% 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 for

clothes 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

EE-RM-PET-100 COMMENT 88
Appendix D: Lot 4 & 5 Correction Curves

This appendix consists of an excel spreadsheet containing the finalized correction curves and

data for Lots 4 and 5. 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

EE-RM-PET-100 COMMENT 88
Table 9. ADL Lot 4 Extractor Test Data

G I Wrii Stjc IIf

j

1 Miri 3piJ 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

EE-RM-PET-100 COMMENT 88
Table 10. ADL Lot 5 Extractor Test Data

Warm1Ul)l) _________

____________________ J

S Sptn 4 Spin Spin 1 P4n Shin

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 Lot 3 Lot 5 Corrected Lot 3 Average Lot 5 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 Lot 3 Lot 5 Corrected

Thai 1 55.4% 59.4% 56.0%

Trial 2 56.0% 59.6% 56.2%

Trial3 56.1% 60.0% 56.6%

Horizontal Axis Machine Lot 3 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 Square Error Calculation

7

15

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
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 Lot 5

bU7o bb7o

17

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
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-1

EE-RM-PET-100 COMMENT 88
1.00 Tub & Basket Assembly Weight (lbs)

Part No. (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 Agitator Clutch Assembly

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

EE-RM-PET-100 COMMENT 88
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-3

EE-RM-PET-100 COMMENT 88
1.00 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

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
APPENDIX E. APPROACH FOR UNCERTAINTY AND VARIABILITY

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

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

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

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

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

EE-RM-PET-100 COMMENT 88
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

EE-RM-PET-100 COMMENT 88
E.4 APPROACHES TO UNCERTAINTY AND VARIABILITY

Two approaches to consider uncertainty and variability are described here:

scenario analysis and

probability analysis.

Scenario analysis uses 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 analysis considers 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

EE-RM-PET-100 COMMENT 88
APPENDIX F. WATER AND WASTEWATER PRICES

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

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

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

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

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

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

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

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

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

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

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

Figure F.5 Water and Wastewater Price Trends F-9

F-i

EE-RM-PET-100 COMMENT 88
APPENDIX F. WATER AND WASTEWATER 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

EE-RM-PET-100 COMMENT 88
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 had four criteria 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

EE-RM-PET-100 COMMENT 88
F-3

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

1986-1998, in 1997$)

EE-RM-PET-100 COMMENT 88