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CHAPTER 4: ENGINEERING ANALYSIS

4.1 INTRODUCTION
The EngineeringAnalysis determinesthe maximumtechnologicallyfeasible energyefficiency levelanddevelopscost-efficiencyrelationshipsto showthe manufacturercostsof achievingincreased efficiency. As described later in this section, manufacturers were asked to provide clothes washer performance and manufacturing cost information for conducting the engineering analysis. Datawas collectedutilizingtheefficiency-levelapproach. Theclotheswashermanufacturersremarkedthatthis approachwas the most suitable approachfor showing the manufacturing cost ofachieving increased efficiency and also provided a high degree ofconfidentiality ofdesign. This approach consists of letting the manufacturers supply cost and corresponding efficiency data using any design options or design optioncombinations they choose. The collected informationdescribes manufacturer specific costs ofachieving predetermined efficiency levels. This format has the benefit ofbeing entirely compatible with data requirements for manufacturer impact analysis.



### 4.2 PRODUCT CLASSES
For this rulemaking the Department is proposing the following classes: Compact (less than 2.0 ft. 3 

### capacity) and Standard (2.0 ft. 3 

### or greater capacity). Based on current information, the Department believes that there is no basis for separate product classes for H- and V-axis clothes washers. Recent and near-termproduct offerings, and working prototypes ofH- and V-axis clothes washers demonstrate large energy savings while maintaining important product features. The Department is proposing to eliminate certain previously defined classifications (Semi-Automatic Top-Loading, Front-Loading and Suds Saving) because they do not offer any added utility which is inherently less energy efficient and therefore would require protectionfrom the energy conservation standards. In the May 1991 Final Rule, these classes were not subject to minimum energy conservation standards because they represented a small portion ofthe market, and there was insufficient information to analyze them. However, the 1988 standard requiring an unheated rinse optionis still applicable to these classes. The Departmenthas furtherreviewedthistopic and believes that these products should be subject to the minimum energy conservation standards applicable to either compact or standard clothes washers.



### 4.3 BASELINE UNIT
A baseline unit is the starting point for analyzing design options for improving energy efficiency. In this engineering analysis, the baseline unit represents a typical model with an energy efficiency no lower than the minimum required by the amended National Appliance Energy Conservation Act (NAECA). New minimum standard for clothes washers (top loading, 1.6 cu.ft.

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### orgreater capacity) was set at EnergyFactor (EF) = 1.18 cu.ft./kWhper cycle and became effective on May 14, 1994.
The Department issued two new test procedures during the course ofthis rulemaking: Appendices 

### "J"and 

### "JI"62 FR45484 [1]. 

### (See Sectionl.B.2. onTestProcedure). The Engineering Analysis presented in this document is based onthe Appendix

### JI testprocedure. This test procedure calculates a MEF (Modified Energy Factor) descriptor. Unlike its EF predecessor, the MEF uses remaining moisture content (RMC) to account for energy saved due to lower drying times and temperature use factors (TUFs). Using cloth loads and different water temperatures are among the manyothersubstantivedifferencesbetweenthe

### Jand

### JI testprocedures. Giventhese differenttesting methods and variables, there is no computationalrelationship betweenthe EF and MEF descriptors.
Inorderto determinethe MEFvalue for thebaseline unit, clotheswashermanufacturers were asked to take a representative clothes washer with an EF as close as possible to 1.18 (current minimum EF) and perform the new 

### JI procedure. If

### no clothes washer was available with an EF value close to 1.18, they were asked to adjust the water volume, machine energy, and/or hot water volume to obtain an EF of 1.18. Five manufacturers (Amana, 

### Frigidaire, GEA, Maytag and Whirlpool) submitted datato the Association ofHome Appliance Manufacturers (AHAM). AHAM mathematically averaged these values to derive an industry average MEF value of0.817 for the baseline unit (based on an EF=1.18) [2].



### 4.4 COST-EFFICIENCY DATA COLLECTION Manufacturing cost and efficiency data was collected utilizing the efficiency level approach, in cooperation with AHAM. The manufacturers provided cost and corresponding efficiency data using any design options or design option combinations they choose. The collected information describes manufacturer specific costs ofachieving predetermined efficiency levels in addition to the energy-use characteristics. AHAMmembersprovidedcostsandenergydatafor the following levels: Baseline, 5%, 10%, 15%, 20% and 25% improvement applied in an existing Y-axis clothes washer and improvements of35%, 40%, 45%, and 50% applied in a H-axis clothes washer. Manufacturers believe that the disclosure oftheir individual costs is not practical giventhe proprietary nature ofthe information. Hence they agreed to provide detailed cost information to AHAM which would then aggregate this data and provide "industry" costs to DOE. 

### 4.4.1 Characterizing Uncertainty
Inthe manufacturing cost information previously supplied by manufacturers (Comment#38, AHAM), a confidence level was provided to characterize the probability of achieving the costs reported. Building onthisframework, DOEproposedmodificationto themostrecentdatacollection so that the cost estimates reported would be bound by a range. DOE requested manufacturers to provide a range of costs associated with achieving each efficiency level. Separate ranges were requested for variable and fixed costs.

4-2For example, for characterizing variable costs, each manufacturer was asked to provide its best point estimates ("most likely" values) for incremental material, labor and overhead costs for achieving a particular efficiency level. These disaggregated costs were then added to arrive at the "most likely" total variable cost for that manufacturer. In addition manufacturers were asked to indicate their maximum and minimum total variable costs to meet the efficiency level. Triangular distributions created using minimum, maximum, and "most likely" values were used to characterize theuncertaintyassociatedwiththemanufacturing costestimates. Similarprocedurewasadoptedfor fixed costs. Figure 4.1 shows illustrative input distributions for incremental manufacturing costs. This figure assumes that data is provided by three manufacturers.

Efficiency Level1

Efficiency Level2 0

0 2

2 3 4 5

Incremental Cost($)

3 4 5 Incremental Cost($) Manuf- Mkt. 6 7 8 acturer Share A 50% B 30% 

### c 20%

6 7 8 

### Figure 4.1 Illustrative input distributions for incremental manufacturing costs

4.4.2 Variability in Costs between Manufacturers Legend

-
-·-·



## --

The clothes washer manufacturing costs previously submitted to DOE (Comment#38, AHAM) demonstrated large variability in some cases. This variability was expressed using the standard deviation in previous data submittals. DOE will not be using standard deviation figures to conductits subgroupanalysis sincethesemaymask seriouscostimpacts,particularlyto smallerfirms. The Departmentrequested disaggregated cost data from all manufacturers. Cost distributions, both variable and fixed, for the industry for achieving a particular efficiency level were obtained by applying shipment-based weights to each manufacturer's cost distribution. This approach captures the richness ofthe data provided by manufacturers and ensures that the final cost distributions incorporate eachindividualmanufacturer'scostdistributionstherebyaccountingfor variabilityinthe data submittals.

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### 4.4.3 Manufacturer Assumptions for Supplying Data
AHAM in conjunction with Arthur D. Little proposed the following items to be used as guidelines to the manufacturers for data collection:

0 Each incremental MEF above the baseline will be viewed as the prospective future standard level. Thusthe dataentriesfor energy and costs shouldbethosethat are necessaryto convert 100% ofthe company's production to that minimum standard level. Each incremental step will be viewed as a separate entity. Thus, for example, ifa company has some washing machines which already meet a new level above the baseline, thenthe costs shownwould be to convert the remainder ofall machines. In addition, no assumption will be made about multiple standardslevels orphase-inperiods. Forexample, 

### if a companywere developing the costs for the 20% Y-axis level ofMEF=l.021, then it should be assumed that DOE would announce (accordingly to previously announced schedule) on October 1999, that the new standard level would be MEF=l.021 at some date at least three years hence. • All MEF levels are to be obtained by using the Appendix J1 test procedure. Whereas, the baseline calculations assumed a warm-rinse to be included, this is not the case with the projected levels. Manufacturers may use whatever means to achieve the individual levels. • The MEF levels given represent incremental percentage efficiency improvement levels over the baseline. Companies have been asked to include cost and efficiency datafor datapoints that may occur between the levels on the next lowest increment level. For example, ifa company were to have technology that would allow them to obtain a 22% increase in efficiency (or an MEF of 1.05), that data would be entered on the line for a 20% improvement. 

### ° Cost and efficiency datamay have some incremental "step"-type function. Thus, companies may know oftechnology that would enable thento reach a 20% improvement in efficiency, but may not have the technology available to reach a 15% efficiency level. Inthis case, the costs and efficiency improvements for the 20% level would be entered into the line for both the 15% and 20% improvements. ° Companies may use information on product costs, capital and tooling, or factory improvements which have already been incurred. 

### If a company has made product improvementsto energyefficiency as aresult of theMay 14, 1991, FinalRule and anticipated future energy standards in excess ofthose implemented on May 14, 1994, then these costs may be usedto develop the efficiency and costs for this datacollectionexercise. Inthis case, companieshave beenaskedto use informationoncosts incurredthatdirectlyrelate to energy efficiency improvementsinexcess of the 1994 standard. Companiesmayusethis information as a basis with which to calculate conversion of 100% oftheir production to that minimum standard level, according to the levels shown in the accompanying chart.
DOE worked with AHAM in developing a survey instrument which was then sent out by AHAMto manufacturers requesting detailed cost and energy-use datafor eachefficiency level. The energy and water-use data for the industry was obtained by applying shipment-weights to each manufacturer's data. This data is presented in Table 4.1.

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### "

Table 4.1 Energy-use Data Product Characterisics FnernvUse Water Use Percent MEF Total EnerW- Clothes Hot Machine

__ Diyer

___ Water Water Irr1provement w/ dryer Container Water Fners.>.: Fnerl!V Use Use
cu.ft.!kWhlcycle kWh/cycle cu.ft. kWh/cycle kWh/cycle kWh/cycle gal.I eye gal./ cu.ft. [I] [2] [3] [4] [5] [6] [7] [8] [9] Baseline 0.817 3227 2.847 1.587 0.209 1.43 39.181 13.779 5 0.860 3.165 2.817 1.543 0.209 1.413 38.613 13.732 IO 0.908 3.017 2.822 1.408 0.209 1.4 38.613 13.71 15 0.961 2.833 2.832 1216 0209 1.407 38.621 13.67 20 1.021 2.739 2.893 1.113 0218 1.408 38.446 13.342 25 1.089 2.292 2.866 0.715 0.304 1273 26.6 9.22
35 1257 1.866 2.749 0.462 0.133 1.27 21.03 7.661 40 1.362 1.859 2.749 0.462 0.133 1263 21.03 7.661 45 1.485 1.651 2.736 0.429 0.114 1.107 23.405 8.57 50 1.634 1.574 2.736 0.413 0.114 1.047 23.405 8.57

For datain columns [3), [4], [5], [6],[7],[8], and [9], companies were asked to approximate the energy component that they would use to develop the MEF shown in column [2]. Where this <la.ta includes multiple products with varying clothes container capacities, for instance, a shipment**w1~ighted** average within the product 

### mix could 

### be used.



### 4.:5 DATA AGGREGATION
Arthur D. Little prepared a spreadsheet to aggregate cost data obtained from various mmufacturers. AHAM used this spreadsheet to aggregate the cost data obtained from the mmufacturers. This aggregated data was then presented to DOE. This procedure helped address concerns ofmanufacturers concerning the proprietary nature ofthe manufacturing costs and their disclosure.
The aggregation spreadsheet takes each manufacturer's total variable (labor, material and overhead) and total fixed (tooling, investment, R&D, and marketing) costs characterized using triangular distributions and aggregates them applying shipment-based weights to arrive at the total**va~iable** and fixed cost distributions respectively for the industry for achieving each efficiency level. The aggregation spreadsheet was developed using Microsoft Excel and Crystal BallTM [3] software and has the ability oftreating custom distributions also.
The following procedure is used for arriving at the industry incremental total variable cost distribution for a particular efficiency level from individual manufacturers' cost submittals:

4-5• Eachmanufacturer's incremental material, labor and tooling costs are added to arrive at the manufacturer's "most likely" incremental total variable cost. • The "most likely" incremental total variable cost along with the minimum and maximum values ofincremental total variable costs, as reported by manufacturers, are used to create triangular distribution for the incremental total variable cost. • Samples are drawnfrom eachmanufacturer's incremental total variable cost distributions to create an industry incremental total variable cost distribution. The number of times a particular manufacturer's cost distribution is sampled relative to others is dependent on its relative market share (when compared to other manufacturers). Figure 4.2 graphically illustrates individual manufacturers' incremental total variable cost distributions and the industry total incremental variable cost distribution thus obtained (here it is assumed that the industry is made up oftwo manufacturers with eachhaving a 50% market share).
The final cost distribution can also be presented using percentile values- 0, 10, 25, 50, 75, 90 and 100percentiles. CrystalBallTM software was used for specifying individual distributions and for samplingthemto arrive at the final distribution. CryStalBallTMprovidestheflexibility ofreporting the final distribution graphically or by specifying percentile values. AHAM provided aggregated industry cost data using percentile values.
Thisprocedurewasusedfor arriving attheindustryincrementaltotalvariablecostdistribution for each efficiency level. Industry incremental total fixed cost distributions are also obtained using the same steps as for the variable cost. In addition, shipment weighted averages ofthe most likely costs, both fixed and variable, were also calculated for each efficiency level as point values for incremental costs.

4-6Efficiency LevelX

0

1.00 Manufacturer A . Manufacturer B

### ~ 4 

## s & 

## I t 1 Incremental Cost($) 1 1 -1 _1 _1**~I ~I** **~I** 01 in1 01 !!?.1 !::.1 e1

I

2.75 4.50 6.24 Incremental Cost($) 8.00 Total Rel. Probability
= 1.0



### lFigure 4.2 Industry cost distribution obtained by sampling each manufacturer's cost distributions

The results after aggregation are presented in Tables 4.2 through 4.4. Table 4.2 gives the industry cost data using "most likely" values. Tables 4.3 and 4.4 present detailed cost distributions for total variable, total fixed, and incremental total manufacturing costs using percentile values.



### Table 4.2 Aggregated Cost Data using "MostLikely" Values
Product Characterisics Variable Costs Total Total lncremen. No. of Percent MEF Cost Per Unit Variable Fixed Mfg. Cost Respondents Improvement Materials Labor Overhead Costs Costs
cu.ji./kWhlcyc/e ($per Unit) ($perUnit) ($per Unit) ($per Unit) [I] [2] (12] (13] (14] (15] (22] (23] Baseline 0.817 5 0.860 $0.01 $0.01 $0.00 $0.02 $0.07 $0.09 5 IO 0.908 $0.25 $0.04 $0.01 $0.30 $0.61 $0.91 5 15 0.961 $3.18 $0.10 $0.04 $3.32 $1.01 $4.33 5 20 1.021 $10.71 ($0.02) ($1.80) $8.89 $6.21 $15.10 5 25 1.089 $36.14 $8.61 $0.09 $44.84 $19.29 $64.13 5
35 1.257 $86.73 $10.94 $7.78 $105.45 $22.72 $128.17 5 40 1.362 $87.15 $10.94 $7.78 $105.87 $22.72 $128.59 5 45 1.485 $125.58 $15.52 $14.51 $155.61 $24.67 $180.28 4 50 1.634 $132.40 $15.68 $14.51 $162.59 $24.67 $187.26 4



### 4-7----- ---------

For column [12], companies were asked to indicate incremental costs associated with materials that would be needed to achieve the particular standards levels in $ per washer unit.
For column [13], companies were asked to indicate the incremental cost oflabor associated with the newtechnology to reach the particular standard levels in$ per washer unit.
Forcolumn [14], companies were asked to indicate the incremental overheadcost associated with this standard level. On column [14], for example, additional electricity to produce new components may be considered as overhead.
For each of these columns, entries on the baseline line are not necessary. However, companiesthatmayhave variable cost increasesnecessaryto bring allproductionupto the

### minimum ofMEF=0.817 were asked to include this cost in the 5% improvement line.

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### Table 4.3 Industry Cost Distributions for 5%, 10%, 15% 20% and 25% Improvements applied to an existing V-axis Clothes Washer
Product Characterisics Total Total Incremental Percent Percentile MEF Variable Fixed Manufacturing Improvement Costs (j) Costs (q) Costs (b) cu..ft./kWhlcycle ($per Unit) ($per Unit) ($per Unit)
Baseline 0.817 5 100 (Max.) 0.860 $0.24 $0.87 $1.11 90 $0.01 $0.18 $0.18 75 $0.01 $0.01 $0.02 50 $0.01 $0.01 $0.02 25 $0.01 $0.01 $0.02 10 $0.01 $0.01 $0.02 0 $0.00 $0.00 $0.00 10 100 (Max.) 0.908 $6.75 $10.84 $12.84 90 $1.26 $1.09 $2.71 75 $0.49 $0.30 $0.96 50 $0.01 $0.06 $0.07 25 $0.01 $0.05 $0.06 10 $0.01 $0.01 $0.02 0 $0.00 $0.00 $0.00 15 100 (Max.) 0.961 $40.00 $10.84 $46.19 90 $3.96 $4.36 $14.08 75 $0.76 $0.30 $0.97 50 $0.65 $0.15 $0.80 25 $0.58 $0.12 $0.72 10 $0.01 $0.01 $0.02 0 $0.00 $0.00 $0.00 20 100 (Max.) 1.021 $70.00 $20.60 $79.45 90 $27.78 $15.63 $38.48 75 $14.13 $11.75 $27.74 50 $0.72 $0.33 $1.06 25 $0.65 $0.26 $0.95 10 ($0.53) $0.24 $0.90 0 ($12.20) $0.21 $0.80 25 100 (Max.) 1.089 $83.28 $27.63 $102.63 90 $70.40 $25.36 $93.97 75 $67.24 $24.04 $90.85 50 $63.46 $22.14 $86.26 25 $15.11 $14.39 $29.37 10 ($0.30) $14.07 $16.13 0 ($12.20) $4.85 $1.28



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### Table 4.4 Industry Cost Distributions for 35%, 40%, 45% and 50% Improvements applied to a H-axis Clothes Washer

Product Characterisics Total Total Incremental Percent Percentile MEF Variable Fixed Manufacturing Improvement Costs (j) Costs(q) Costs (b) cu.fl.lkWhlcycle ($per Unit) ($per Unit) ($per Unit)
Baseline 0.817 35 100 (Max.) 1.257 $280.00 $101.60 $381.60 90 $228.80 $25.28 $254.01 75 $118.63 $23.29 $143.34 50 $69.06 $21.41 $90.56 25 $63.59 $19.44 $85.30 10 $60.38 $17.20 $81.74 0 $52.03 $15.06 $67.43 40 IOO <Max.) 1.362 $290.00 $101.60 $391.60 90 $229.28 $25.28 $254.44 75 $117.17 $23.30 $143.57 50 $69.05 $21.41 $90.54 25 $63.73 $19.44 $85.28 IO $60.44 $17.15 $81.74 0 $52.03 $15.06 $67.43 45 100 (Max.) 1.485 $300.00 $101.60 $401.60 90 $239.76 $28.23 $266.26 75 $227.29 $23.70 $251.73 50 $128.38 $19.89 $153.71 25 $79.38 $18.02 $97.37 IO $69.25 $16.95 $87.36 0 $52.30 $15.06 $68.26 50 100 (Max.) 1.634 $300.00 $I01.60 $401.60 90 $239.46 $28.29 $266.11 75 $227.31 $23.76 $251.70 50 $132.89 $19.89 $157.87 25 $95.45 $18.00 $113.81 IO $84.95 $16.94 $102.98 0 $66.16 $15.06 $82.12

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### The AHAM data submittal was used to develop a cost-efficiency graph. This graph is presented in Figure 4

### .3
AHAM Clothes Washer Data 450
400



# -**·~** 350 en en**~300**



## .... Cl) 

# • 0 250 

# • • )( 

## u 

## I! 200 c Cl) E 150 )( )( )/.. Cl)


# ... - CJ 

# I . .E 100 

# ***~** 4**~ ~**  

# • 

# • 

# • 50 4 

## !c**~**

0 

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# •

,.._ CX>
..... ..... 0) ,.._ N LO

## ~ .....**~** 0**~ ~** **~** LO**~ ~**  CX> 0) "'! c:i c:i c:i c:i
..... ..... ..... ..... ..... (Baseline) (5%) (10%) (15%) (20%) (25%) (35%) (40%) (45%) (50%) Modified Energy Factor 

### Figure 4.3 Cost-Efficiency graph for clothes washers



### 4.15 RETAIL PRICE 4100% •90% )(753 X50% {'125% •10% +0%



### The results ofthe Engineering Analysis are summarized in the Cost-Efficiency graph using pe:rcentile values, aspresented inFigure 4.3. Manufacturer andretailmarkups, discussed

### inChapter 6 ofthis document, 

### will be applied to these total incremental cost distributions to determine the purchase price (i.e. price to the consumer) ofclothes washers. These consumer prices 

### will thenbe used along with energy-use data to perform LCC analysis.



### 4.7 PROPRIETARY DESIGN
At the November 1996 workshop, it was acknowledged that Whirlpool had four patented proprietaryprototype designs which include bothV- and H-axisplatforms. Whirlpool indicated that these were working prototypes. In a letter dated November 29, 1996, DOE communicated the pa.tents numbers ofWhirlpool's designs to the workshop participants. (DOE, No. 57). During the 4-11workshop, Whirlpool asked that the designs be included in the rulemaking analysis. Whirlpool also indicatedthatitwouldbeappropriateto conductanindependent study to estimatethemanufacturing costs ofthenewdesigns. (Whirlpool, No. 

### SSL at 169). Whirlpooldid not seethepracticality ofeach manufacturer estimating the cost ofthe Whirlpool designs, since estimates by other manufacturers would only be based on patent information and could not be expected to produce consistency in approach or a high degree ofaccuracy. (Whirlpool, No. 69 at 4). Maytag commentedthat the Whirlpooldesigns needed to be subjectedto a full and complete engineering and cost analysis by DOE. Maytag requested that all manufacturers 

### be given the opportunitytoparticipate inthisprocess sincethe cost ofapplying these designs to a manufacturer's ownbasic washer design varies greatly from manufacturerto manufacturer. (Maytag, No. 64 at 1). GEAalso statedthatthe analysis neededtobe expandedto coverthe designs disclosed byWhirlpool. 

### It further stated that only a revised method focusing on the technical know-how, manufacturing capabilities and economic strengths ofindividual manufacturers would permit the proper evaluation ofthe impacts on "atypical manufacturers." (GEA, No. 63 at 7).
Inresponse the Department conducted a ''tear-down" manufacturing cost assessment ofone ofthe V-axis Whirlpool prototype. The main objective ofthe manufacturing cost assessment, is to quantify the differential manufacturing costs ofproducing high efficiency clothes washers based on (1) the Whirlpool proprietary V-axis design, and (2) commercially available V- and H-axis designs. See Chapter 

### S for further details.

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### :REFERENCES
L U.S. Department ofEnergy (DOE) 1997. Energy Conservation Programfor Consumer Products: Test Procedurefor Clothes Washers and Reporting Requirementsfor Clothes Washers, Clothes Dryers, andDishwashers. 

### 2.. Association ofHome Appliance Manufacturers (AHAM). December 2, 1997. Letter from Wayne Morris (Technical Director--Regulatory Affairs, AHAM) to Bryan Berringer (Program Manager, Clothes Washer Rulemaking, U.S. DOE). 3. Crystal BallTM.

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