illustrative input distributions for incremental manufacturing costs. This figure assumes that data

is provided by three manufacturers.

Efficiency -

LeveIl

0 ----- 34

Incremental Cost ($)

Efficiency

Level 2 23456; 8

Incremental Cost ($)

Manuf- Mkt

acturer

.

Share Legend

A 50% -

B 30%

C 20% --

Figure 4.1 Illustrative Input Distributions for Incremental Manufacturing Costs

4.4.2 Variability in Costs between Manufacturers

The Department requested 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 of the data provided by manufacturers and ensures that the final cost

distributions incorporate each individual manufacturer's cost distributions thereby accounting for

variability in the data submittals.

4.4.3 Manufacturer Assumptions for Supplying Data

AHAM in conjunction with DOE proposed the following items to be used as data collection

guidelines for manufacturers:

Each incremental MEF above the baseline is viewed as the prospective future standard level.

Thus the data entries for energy and costs are those necessary to convert 100% of the

company's production to that minimum standard level. Each incremental step is viewed as

a separate entity. For example, if a company has some washing machines which already

meet a new level above the baseline, then the costs shown represent the cost of converting

the remainder of all machines.

• All MEF levels are obtained by using the Appendix Ji test procedure. Whereas, the baseline

calculations assumed a warm-rinse, this is not the case with the projected levels.

Manufacturers may use whatever means they wish to achieve the individual levels.

Cost and efficiency data may have some incremental "step"-type function. Thus, companies

4-3

EE-RM-PET-100 COMMENT 88
may know of technology that would enable then to reach a 20% improvement in efficiency,

but may not have the technology available to reach a 15% efficiency level. In this 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

improvements to energy efficiency as a result of the May 14, 1991, Final Rule and

anticipated future energy standards in excess of those implemented on May 14, 1994, then

these costs may be used to develop the efficiency and costs for this data collection exercise.

In this case, companies have been asked to use information on costs incurred that directly

relate to energy efficiency improvements in excess of the 1994 standard. Companies may

use this information as a basis with which to calculate conversion of 100% of their

production to that minimum standard level, according to the levels shown in the

accompanying chart.

DOE worked with AHAM in developing a survey instniment which was then sent out by

AHAM to manufacturers requesting detailed cost and energy-use data for each efficiency 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.

4-4

EE-RM-PET-100 COMMENT 88
Table 4.1 Energy-use Data

Product Characteristics Energy Use Water Use

Total

Percent MEF Energy Clothes Hot Machine Dryer

Improve- cu.ft/kW wldryer Container Water Energy Energy Water Use Water Use

ment h/cycle kWh/cycle Cu. ft. kWh/cycle kWh/cycle kWh/cycle gal/cyci gal/cu. Ft.

[1] [2] [3] [4] [5] [6] [7] [8] [9]

Baseline 0.817 3.227 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

10 0.908 3.017 2.822 1.408 0.209 1.4 38.613 13.71

15 0.961 2.833 2.832 1.216 0.209 1.407 38.621 13.67

20 1.021 2.739 2.893 1.113 0.218 1.408 38.446 13.342

25 1.089 2.292 2.866 0.715 0.304 1.273 26.6 9.22

35 1.257 1.866 2.749 0.462 0.133 1.27 21.03 7.601

40 1.362 1.859 2.749 0.462 0.133 1.263 21.03 7.61

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 data in 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

data includes multiple products with varying clothes container capacities, for instance, a shipment

weighted average within the product mix could be used.

4.5 DATA AGGREGATION

The Department prepared a spreadsheet to aggregate cost data obtained from the

manufacturers. AHAM used this spreadsheet and transmitted the results to DOE. This procedure

helped address manufacturer concerns on the possible disclosure of proprietary manufacturing costs.

The aggregation spreadsheet was developed using Microsoft Excel and Crystal Ba11TM software.

The following procedure is used to arrive at the industry incremental total variable cost

distribution for a particular efficiency level from individual manufacturers' cost submittals:

Each manufacturer's incremental material, labor and tooling costs are added to arrive at the

4-5

EE-RM-PET-100 COMMENT 88
manufacturer's "most likely" incremental total variable cost.

The "most likely" incremental total variable cost along with the minimum and maximum

values of incremental total variable costs, as reported by manufacturers, are used to create

a triangular distribution for the incremental total variable cost.

Samples are drawn from each manufacturer'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.

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 of two manufacturers each having a 50% market share).

The final cost distribution can also be presented using percentile values- 0, 10, 25, 50, 75,

90 and 100 percentiles. Crystal Ba11TM software was used to specify individual distributions and to

sample them to arrive at the final distribution. Crystal Ba11TM provides the flexibility of reporting

the final distribution graphically or by specifying percentile values. AHAM provided aggregated

industry cost data using percentile values.

This procedure was used to arrive at the industry incremental total variable cost distribution

for each efficiency level. Industry incremental total fixed cost distributions are obtained using the

same steps as for the variable cost distribution. In addition, shipment weighted averages of the most

likely costs, both fixed and variable, were calculated for each efficiency level as point values for

incremental costs.

4-6

EE-RM-PET-100 COMMENT 88
Manufacturer A

Efficiency Manufacturer B

Level X

Mkt.share

___________

kt. share ________

0 1 4 5 6

I I 1Incremental Cost ($) ---I

I

a

o O u o oi

>'

2

0

w

>

IS

a,

Total Rel.

Probability

= 1.0

Figure 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.

4-7

1.00 2.75 4.50 6.24 8.00

Incremental Cost ($)

EE-RM-PET-100 COMMENT 88
Table 4.2 Aggregated Cost Data using "Most Likely" Values

Product Characteristics Variable Costs per Unit Total Variable Total

Fixed

Increm.

Mfg. Cost

No. of

Respondents

Percent MEF Materials Labor Overhead

Improvement cu.fi./ ($) ($) ($) Costs ($ per Costs (S ($ per

kWh/cycle Unit) per Unit) Unit)

($)

[1] [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

10 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

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 of labor associated

with the new technology to reach the particular standard levels in $ per washer unit.

For colunm [14], companies were asked to indicate the incremental overhead cost associated

with this standard level. On colunm [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,

companies that may have variable cost increases necessary to bring all production up to the minimum

of MEFO. 817 were asked to include this cost in the 5% improvement line.

4-8

EE-RM-PET-100 COMMENT 88
Table 4.3 Industry Cost Distributions for 5%, 10%, 15% 20% and 25% Improvements

Applied to an Existing V-axis Clothes Washer

Product Characteristics Total Total Incremental

Percent Percentile MEF Variable Costs Fixed Costs (q) Manufacturing

Improvement cu.ft/kWh!cycle (j) ($ per Unit) ($ per Unit) Costs ($ 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

6 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

0.00

0.01

0.00

0.02

______________ 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 27.630 102.63

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

4-9

EE-RM-PET-100 COMMENT 88
Table 4.4 Industry Cost Distributions for 35%, 40%, 45% and 50% Improvements

Applied to a H-axis Clothes Washer

Product Characteristics Total Total Incremental

Percent Percentile MEF Variable Costs Fixed Costs (q) Manufacturing

Improvement (b) cu.ft/kWh/cycle (j) ($ per Unit) ($ per Unit) Costs ($ per Unit)

Baseline

________________

0.8 17

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

6 52.03 15.06 67.43

40 100 (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

10 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

10 69.25 16.95 87.36

0 52.30 15.06 68.26

50 100 (Max.) 1.634 300.00 101.60 401.60

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

10 84.95 16.94 102.98

0 66.16 15.06 82.12

The AHAM data submittal was used to develop a cost-efficiency graph. This graph is

presented in Figure 4.3.

4-10

EE-RM-PET-100 COMMENT 88
AHAM Clothes Washer Data

450

400

350

0i

0)

250

C.,

. 200

150

.E 100

50

0

4

4 -

)

-

+ .

4

.

I I I

N- 0) N- C\1 LC)

d d

(0 0) (0 00 (0

0) 0 cN c•) (0

CO co

(Baseline) (5%) (10%) (15%) (20%) (25%) (35%) (40%) (45%) (50%)

Modified Energy Factor

Figure 4.3 Cost-efficiency Graph for Clothes Washers

100%

c 90%

Y50%

25%

10%

- SWA

4-11

EE-RM-PET-100 COMMENT 88
REFERENCES

1. Title 10, Code ofFederalRegulations, Appendix JandJl to Subpart B or Part 430-- Un?form

Test Method for Measuring the Energy Consumption of Automatic and Semi-automatic

Clothes Washers, January 1, 1999.

2. Morris, W., Technical Director for Regulatory Affairs, AHAM, personal communication.

Letter to Bryan Berringer, Program Manager, Clothes Washer Rulemaking, U.S. DOE.

December 2, 1997.

4-12

EE-RM-PET-100 COMMENT 88
CHAPTER 5. MANUFACTURING COST ASSESSMENT

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TABLE OF CONTENTS

5.1 PROJECT OBJECTiVES 5-1

5.2 MANUFACTURING COST ESTIMATES AND ASSUMPTIONS 5-1

5.3 COST STRUCTURE OF THE SPREADSHEET MODEL 5-4

5.4 RESULTS FROM THE ANALYSIS 5-7

5.4.1 Results for High-Volume Manufacturers 5-8

5.4.2 Results for Low-Volume Manufacturers 5-12

LIST OF TABLES

Table 5.1 Summary of Clothes Washers Analyzed 5-1

Table 5.2 Key Manufacturing Assumptions 5-3

Table 5.3 Assumptions for High / Low-Volume Manufacturer 5-4

Table 5.4 Major Manufacturing Processes 5-5

Table 5.5 Greenfield Investment for and Depreciation Life of Plant, Equipment 5-9

Table 5.6 Summary of Sensitivity Analyses 5-12

Table 5.7 Greenfield Investment for an Annual Production Volume of 1.5

and 0.3 Million Units 5-14

LIST OF FIGURES

Figure 5.1 Full Product Cost 5-2

Figure 5.2 Manufacturing Cost Assessment Stages 5-4

Figure 5.3 Range of Cost Premiums for H-axis, high efficiency V-axis over

V-axis Baseline 5-7

Figure 5.4 Cost Composition by Washer Type 5-8

Figure 5.5 Full Production Cost Breakdown by Sub-Assembly Level 5-8

Figure 5.6 Investment Cost Breakdown by Major Manufacturing Process 5-9

Figure 5.7 Monte Carlo Simulation of Aggregated Baseline Cost 5-10

Figure 5.8 Monte Carlo Analysis: Relative Importance of Each Input Factor 5-11

Figure 5.9 Range of Cost Premiums for Low Volume Manufacturers 5-13

Figure 5.10 Averaged Cost Differentials by Category and Washer Type

from the Means 5-14

Figure 5.11 Investment Requirements by Category 5-15

5-i

EE-RM-PET-100 COMMENT 88
CHAPTER 5. MANUFACTURING COST ASSESSMENT

A manufacturing assessment was conducted to estimate the manufacturing costs associated

with an increase in energy efficiency for clothes washers. This approach involved the disassembly

of eight clothes washers, analysis of the materials and manufacturing processes, and the development

of a spreadsheet model. The model was run using a Monte Carlo simulation to approximate industry

manufacturing costs and to determine sensitivities to key inputs.

The model contains separate manufacturing assumptions for both high-volume manufacturers

(producing 1.5 million units per year) and low-volume manufacturers (producing 0.3 million units

per year). The analysis of low-volume manufacturers was done to capture the differentiated cost

structure of this market group. Table 5.1 summarizes the type of clothes washer analyzed and

whether or not it was analyzed for a high or low volume manufacturer.

Table 5.1 Summary of Clothes Washers Analyzed

Clothes Washers High Volume

Manufacturer

Low Volume

Manufacturer

Analyze two vertical-axis (V-axis) washers (baseline) X X

Analyze four high-efficiency V-axis washer designs X

Analyze two horizontal axis (H-axis) washer designs X X

5.1 PROJECT OBJECTIVES

The project had five core objectives which were followed throughout the assessment:

• Develop a clear and consistent manufacturing cost assessment methodology.

• Build a detailed manufacturing cost assessment model that accurately predicts the cost

differential of selected models.

• Develop a model that estimates the cost premium of low-volume versus high-volume

manufacturers of V-axis and H-axis washers.

• Report the differential manufacturing costs in aggregated form or as a range to maintain

confidentiality of the data.

• Obtain input from stakeholders on the manufacturing cost estimates and assumptions to

confirm accuracy.

5.2 MANUFACTURING COST ESTIMATES AND ASSUMPTIONS

The categories used to summarize the manufacturing costs developed closely parallel the cost

categories used by the Association of Home Appliance Manufacturers (AHAM). Full production cost

is defined as the sum of direct material, direct labor and overhead (including investment

5-1

EE-RM-PET-100 COMMENT 88
depreciation).a Other cost elements (SG&A, R&D, and interest) are grouped under the nonproduction cost category. Together these costs make up the full factory cost of the product as shown

in Figure 5.1.

Full Cost of Product

Full Production Cost * Non-Production Cost

________ ________

Iovertieaci Selling

I'idirect Latmr - raiKi. ieurcji - Ca o -

IPcliCI MteriaI - Afvertisirig

&

reff 1.111 Wih erts

Mrtriuri: - laos to ITild new

or ftflçvr]

Depreialcori - . . . Sales person ror' I prCJdias.Dc

produciori roinp. ± Towel

TaxeS wp. etc. processes

L1ranc related - Lpeitirw

Warehousinq

-

compliance

'0 essoto

- Dehvery

-

- cold I

keepirg

- Order anlryl

pr000sslrlq.

* Tax Reform Act of 1986, requires companies to measure cost of goods sold as the full production cost of the goods sold.

Figure 5.1 Full Product Cost

It is understood that the cost of specific models - or costs to individual manufacturers - will

vary, depending on elements such as the product's precise characteristics, actual manufacturing

processes, and the product mix in the factory (multiple clothes washer and dryer products). Also

there are considerable differences in the levels of vertical integration as some manufacturers prefer

purchasing partially complete sub-assemblies to manufacturing themselves. However, as this set of

assumptions remain constant, the differential cost estimation methodology reduces the impact of

plant-specific characteristics.

In developing the cost model for the manufacturing cost assessment, several assumptions

were made. These assumptions are based on general industry practice, determined from manufacturer

a Overhead costs in the AHAM data collection do not include investment depreciation

5-2

EE-RM-PET-100 COMMENT 88
interviews, 1992 U.S. census data, and internal Arthur D. Little sources. Table 5.2 summarizes the

key manufacturing assumptions used in the analysis.

_

__

Table 5.2 Key Manufacturing Assumptions

Category Assumption

Work Days per Year (days) 250

Average Shifts per day (shifts) * 2.0

Runtime per Shift (hours) 8

Lot Size (work days)

Assembly Worker Downtime

_____________________

20%

E i U i % kd F Monte Carlo mean 85% qu pment pt me ( wor ays) I 75% to 95%

B d d W h

r Monte Carlo mean $23

ur ene ages @er our) 1 Range $17 to $28

Building Depreciation Life (years) 25

Conveyor Depreciation Life (years) _____________________________________ 15

(Small Stamp 0-60 ton, (years) j 5

I Medium Stamp 60-600 ton, (years) t 5

T li D i ti Lif Large Stamp 600-1500 ton, (years) 10oo ng eprec a on

e 1 Small IJM 0-15 0 ton, (years) t 5

I Medium IJM 150-500 ton, (years) t 5

_______________________________L Large IJM 500-1250 ton, (years) t 10

Average Depreciation Life

'

Monte Carlo mean 100%

(adjusts equipment, tooling dep. lives5 1 Range 75% to 125%

Maintenance Cost j Monte Carlo mean 4%

(% of Equipment Cost) Range 2.5 to 5.5%

Utilities Cost J Monte Carlo mean 2.1%

(% of Materials Cost) Range ito 3.5%

C i U ili i

JMonte Carlo mean 85%

apac ty t zat on

Range 60 to 95%

I R ui Monte Carlo mean J -

100% nvestment eq rements

Range 50 to 150%

Taxes (% of Factory Cost) 0.9%

Insurance (% of Factory Cost) 0.8%

* Fabrication, 2.5 Shfls, Assembly 1.0 Shfls

t Tooling depreciation l?fe is the maximum number of years that a stamping or molding die is expected to be used

before a design iteration makes it obsolete. However, dies may wear out from use before their maximum design life.

For metal stamping dies, we assumed two million hits, for injection molding (IJM) dies we assumed one million hits.

For the purpose of depreciation, we select whichever leads to a shorter life. The design life of a die is factored by the

average depreciation life variable which thus may increase or decrease its design (but not hit) life.

5-3

EE-RM-PET-100 COMMENT 88
Manufacturing plants are assumed to require investment for a "green field" site, including

all new equipment, tooling, installation, and building. It is also assumed that manual final assembly

is necessary to reflect the need for flexibility in production of multiple models.

Table 5.3 characterizes the two scenarios used in this analysis - high volume and low

volume manufacturers. Low volume manufacturers suffered from several disadvantages, such as

purchased parts costing 10% more than for their larger counterparts and higher overhead cost

structures. Raw materials, on the other hand, were assumed to be price equivalent. The

manufacturing volume for the low volume manufacturer was set at the lower limit of what industry

sources consider to be a viable production capacity to compete in the overall mass market.

Table 5.3 Assumptions for High / Low-Volume Manufacturer

Manufacturer High Volume Low Volume

Plant Size (total square feet) 1000000 250000

Conveyor Length (feet) 57600 9400

Production capacity (maximum units / year) 1500000 300000

Indirect Labor Penalty (on top of already increased assembly

time)

n.a. 10%

Low Volume Part Cost Penalty

__________________

n.a.

_________________

10%

5.3 COST STRUCTURE OF THE SPREADSHEET MODEL

The manufacturing cost assessment methodology used is a detailed, component-focused

technique for rigorously calculating the manufacturing cost of a product (direct materials, direct labor

and some overhead costs). Figure 5.2 shows the three major steps in generating the clothes washer

manufacturing cost.

Raw Fabrication Finished Materials Materials

Bill of

Materials Purchased Parts

Processes Assembly

Processes

Figure 5.2 Manufacturing Cost Assessment Stages

5-4

EE-RM-PET-100 COMMENT 88
First, a baseline was established to compare against the high efficiency models. Two clothes

washers were chosen due to their high popularity in the 1997/8 market and the fact that they came

from two different manufacturers. Following is a list of the key characteristics describing the

baseline clothes washers:

• 27" overall width

• 3 wash/rinse temperature settings

• Unheated rinse

• 3 Settings for Load Size

• 2 wash/spin speeds

• 8 or more wash cycles

• Super capacity wash basket

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 major manufacturing

facilities to ensure accuracy on methodology and pricing. For more information on the BOM, see

Appendix D.

Following the development of a detailed BOM, the major manufacturing processes were

identified and developed for the spreadsheet model. These processes are listed in Table 5.4.

Table 5.4 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

5-5

EE-RM-PET-100 COMMENT 88
Information on equipment and tooling costs, typical processing cycle times, and materials

used for fabrication were obtained from Arthur D. Little 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 entered in the

BOM and linked to the specific parts being fabricated. Each part / process had a time and labor cost

assigned.

For this analysis $23.00 per hour was used as the average fully burdened labor rate based on

typical yearly wages and benefits for union employees. This parameter was investigated using

sensitivity analysis because labor rates can vary considerably, depending on geographic location,

availability of skilled labor, and level of union representation.

In the final step of the cost assessment, assembly times and associated direct labor costs were

estimated. Assembly cycle times were primarily derived from the disassembly of the selected 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.

The 1992 Census indicates an average labor content in the household laundry equipment

segment to be 2.1 labor-hrs per unit. However, experts estimate 1.8 hours is more accurate for 1999,

as a savings of 0.3 hrs per unit, or approximately 14% for the industry over the past 7 years, could

be expected. The indirect labor-hour per unit was multiplied by the average labor rate ($23) in order

to estimate the indirect labor cost. The average direct labor hour per unit was 1.32 hours; therefore

the indirect labor content was calculated to be on average 0.48 labor hours per unit. The indirect

labor is included in the overhead estimate, along with indirect materials, utilities, depreciation,

maintenance, taxes, and insurance. The direct labor cost total is approximately $25 per unit, while

the indirect labor costs are estimated to be $13.50 per unit at the fully burdened $23 per hour labor

rate.

5-6

EE-RM-PET-100 COMMENT 88
5.4 RESULTS FROM THE ANALYSIS

5.4.1 Results for High-Volume Manufacturers

In total, eight washing machines were disassembled and analyzed - two V-axis baseline

models, four high-efficiency V-axis washers and two H-axis models. Compared with the baseline,

Figure 5.3 shows the total incremental cost range that the H-axis and the high efficiency V-axis

exhibited from the Monte Carlo analysis.

$250.00

$200.00

0

Cl)

D

$150.00

- $100.00

$50.00

$0.00

-$50.00

I ____________________

_________________

_______ -J

1 ______________________________________

H-axis

Washer Machine Type

HE V-axis

Figure 5.3 Range of Cost Premiums for H-axis, high efficiency V-axis over V-axis

Baseline

The breakdown of costs by category also varies by washer type. Of the total costs, the

proportion attributable to material increases for the high efficiency model, while the other

components decreased. In Figure 5.4 the breakdown is reported using average values by washer

type.

5-7

EE-RM-PET-100 COMMENT 88
100%

90%

0

80%

70%

60%

C55) cD

50%

40%

0 30% a)

20%

10%

0%

V-axis H-axis HE V-axis

Washer Type

Figure 5.4 Cost Composition by Washer Type

Figure 5.5 illustrates the cost breakdown of sub-assembly by washer type.

100%

90%

80%

70%

U,

0

e 60%

50%

8 40%

5, 0

30%

20%

10%

0%

Figure 5.5

C a b in e

IPum ps, Valves, &

_ sc.&FInalAssy

C on tro Is

-

I

Dsuspension

_______ _______________

_

LTranny & Motor

Tub & Basket

_

V-axis Baseline H-axis HE V-axis

H H

Washer Type

Full Production Cost Breakdown by Sub-Assembly Level

5-8

EE-RM-PET-100 COMMENT 88
100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Figure 5.6 Investment Cost Breakdown by Major Manufacturing Process

Figure 5.6 provides a breakdown of investment costs by major manufacturing process.

Depreciation costs from fixed investments in equipment and tooling, a major overhead cost

element, were estimated based on the requirements derived from the component cycle times and

production volumes. Production volumes, in conjunction with equipment process times, determine

the number of pieces of equipment necessary and the plant investment costs. Table 5.5 compares

investments required to build manufacturing facilities and the depreciation lives of those

investments.

Table 5.5 Greenfield Investment for and Depreciation Life of Plant, Equipment

Hiqh Volume Manufacturer Investment Requirements (USD MM)

Equipment Tooling Bldg Total

V-Axis

H-axis

HE V-axis

$114.40

$96.02

$97.22

$34.17

$38.85

$35.20

$100.00

$100.00

$100.00

$248.58

$234.87

$232.42

___________ Average_Dep reciation_Lives_(Years) ___________

Equipment fooiing Bldg Total

V-Axis

H-axis

HE V-axis

10.1

11.0

10.7

2.7

2.8

3.5

25.0

25.0

25.0

15.1

15.6

15.9

5-9

Baseline V-axis H-axis HE V-axis

EE-RM-PET-100 COMMENT 88
To evaluate the key parameters simultaneously and to understand the cumulative effects of

variability and uncertainty we conducted a Monte Carlo simulation. This process generates random

inputs within a prescribed distribution that then completes numerous iterations (10,000) to quantify

the range of possible outcomes and the probability of each occurrence. Figure 5.7 shows the output

from this simulation for the baseline V-axis washers.

10,000 Trials

Forecast: High Vol: V-axis Baseline

Frequency Chart 19 Outliers

.024 - 239

.018 179.2

-Il

-'

rD

.012 1195 -

=

=

.006 59.75

.000 0

$200.00 $210.00 $220.00 $230.00 $240.00

USD

Figure 5.7 Monte Carlo Simulation of Aggregated Baseline Cost

Figure 5.8 illustrates the relative importance of all input factors on the final product cost of

the V-axis baseline. Investment requirements and wages are the most important variables in

determining the per unit washer cost. However, the importance of the investment factor is also due

to its wide range (±50%).

5-10

EE-RM-PET-100 COMMENT 88
Sensitivity Chart

Target Forecast: High Vol: V-axis Baseline

-1 -0.5 0 0.5 1

Measured by Rank Correlation

Investment Relativity Factor .67 -

Burdened Wages ($/hr) .67 Jf I

Average Depreciation Life (%) -.21

Maintenance (% of Equipment Costs) .12

Actual Output (units/year) -.09 1

Utility Cost (% of mat) .08

Uptime (%) -.08 [1

Figure 5.8 Monte Carlo Analysis: Relative Importance of Each Input Factor

In addition to the Monte Carlo simulation, which allows all parameters to vary

simultaneously within the ranges given in Table 5.2, a sensitivity analysis was also conducted while

holding other variables constant. The results of this analysis are presented in Table 5.6. Although

Monte Carlo found wages to be the most important variable, this analysis identified Plant Investment

factor as the critical variable. For the Plant Investment factor, we assume that 100% represents the

baseline equipment cost. Actual higher or lower investment levels (on a percentage basis) can then

be investigated.

5-11

EE-RM-PET-100 COMMENT 88
Table 5.6 Summary of Sensitivity Analyses

Variation Found in

MC Variable Studied Input Manufacturing Cost

Rank Parameter

Variation V-axis H-axis HE

___________

(baseline) V_axis*

_______

1

_______________________________

Labor Rate (vary hourly labor $17-28 $17 $19 $16

rate)

____________

2 Plant Investment (vary as % ±50% $24 $23 $20

investment)

3 Equipment and Tooling (vary 7-12 yrs. $5 $5 $4

________

depreciation)

____________ ____________ ___________ ___________

4 Actual Plant Output (vary output) 60-100% $5 $5 $4

5 Machine Availability (% work 70-95% $4 $3 $3

_______

days)

___________ ___________ __________ __________

6 Utility Costs - electricity, gas, 1-3.5% $3 $6 $5

steam (% of washer material

costs)

7 Equipment Maintenance Costs 2.5-5.5% $3 $2 $2

(vary as % of installed

______

equipment)

__________ __________ _________ _________

* HE V-axis stands for the High Efficiency V-axis models studied

In summary, the estimate of the mean production cost of the high volume baseline vertical

axis washer is $219. The cost premium for horizontal-axis technology ranges from $78 to $203 over

the vertical-axis baseline (based on two samples) while the cost premium for high efficiency vertical

axis technology ranges from $-34 to $187 (based on four samples). It should be noted that some of

the high-efficiency V-axis models analyzed represent large departures from current V-axis baselines

and would require complete retooling of most manufacturing facilities. Furthermore, patent

protections could restrict adoption of these designs by other manufacturers. Finally, as a group, the

high efficiency V-axis clothes washers considered are less efficient than the H-axis designs analyzed.

5.4.2 Results for Low-Volume Manufacturers

The results from the analysis of low volume manufacturers (0.3 million units per year) are

presented in Figure 5.9. The figures present costs for low volume manufacturers relative to the mean

value for the high volume manufacturer. Figure 5.9 compares Monte Carlo simulation ranges from

the low volume manufacturer to the high volume baseline V-axis cost.

5-12

EE-RM-PET-100 COMMENT 88
$300.00

0

Ci)

2. $250.00

(I)

0

0

a $200.00

>

$150.00 0(1)

ax

sioo.oo

>E

$5000

$0.00 a

a

-$50.00

Rrngeore boed on 2,000 Monto V-axis H-axis

Washer Machine Type

Figure 5.9 Range of Cost Premiums for Low Volume Manufacturers

Figure 5.10 presents the cost differential, by cost category, of low volume manufacturers

compared to high volume manufacturers for both baseline V-axis and H-axis washers. Comparing

low-volume to high volume manufacturing costs at the means of all input variables, it is to be

expected that low-volume manufacturers' depreciation, and material costs are higher. Low volume

manufacturers' labor costs increase mainly due to lower allocation efficiency and the additional 10%

indirect labor cost penalty. Other costs (insurance, taxes, utilities, maintenance) also have a positive,

but lesser impact.

5-13

EE-RM-PET-100 COMMENT 88
$40.00

$30.00

$20.00

o

$10.00

$0.00

Washer Type

Figure 5.10 Averaged Cost Differentials by Category and Washer

Type

Depreciation costs from fixed investments in equipment and tooling, a major overhead cost

element,were estimated based on the requirements derived from the component cycle times and

production volumes. Production volumes, in conjunction with equipment process times, determine

the number of pieces of equipment and the plant investment. To size of the plant and the number of

pieces of equipment, we assumed an up-time of 90%. Table 5.7 compares the investments required

to build high and low volume V-axis and the H-axis plants and the depreciation lifetime of those

investments.

Table 5.7 Greenfield Investment for an Annual Production Volume of 1.5 and 0.3 Million

Units

Hard tooling for stamping and injection molding operations is not included in indirect

material costs for either small or large manufacturers. A per-hit or simple straight-line depreciation

5-14

V-axis H-axis

EE-RM-PET-100 COMMENT 88
assumption is used to calculate the yearly amortized per unit cost, whichever leads to a shorter life.

These assumptions can vary greatly, and have a significant effect on the total investment and the

depreciation element of the overhead costs.

Low volume manufacturers face a proportionally higher investment hurdle than their high

volume counterparts. A key driver is tooling costs which are more than 60% of the investments

required for high volume manufacturers while the volume is just 20%. While large manufactures can

wear out tooling in less than a year, small manufacturers may have to scrap tooling due to design

changes after several years of use. On average, tooling expenses are 50% higher for small

manufacturers and the average tool life is twice as long. Thus, large manufacturers have an inherent

advantage in how quickly they can cycle through tooling changes since the penalty is lower.

100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

L

I P

_

_______ ______

[I Quality

- - _______

DJoining ± IMetaIWork

0 Tooling

OIJM

9 Stamping

9 Coating

High Vol V-axis Low Vol V-axis High Vol H-axis Low Vol H-axis

Figure 5.11 Investment Requirements by Category

In summary, the estimate of the full production cost of the baseline vertical axis washer was

$219 for large manufacturers. The cost premium for low manufacturers over the mean high volume

baseline V-axis ranges from -$1 to $60 over for the V-axis design and $103 to $253 for the H-axis

designs, depending primarily on design and variations in key input parameters (Figure 5.9). At the

mean of all input variables small manufacturers producing V-axis washers have a cost disadvantage

of $26. For H-axis washers this disadvantage increases to $35. The greenfield assumption possibly

overstates the V-axis penalty as depreciation costs as observed in 10K reports are lower than

calculated in this analysis. This indicates that at least a portion of current V-axis facilities are able

to use fully depreciated equipment. This equipment may not be reusable to produce H-axis washers

however.

The cost disadvantages presented in Figure 5.10 is for production cost only and does not

include any additional scale disadvantages that exist in non-production costs such as selling, general

5-15

EE-RM-PET-100 COMMENT 88
and administrative and R&D. Also the designs investigated may be patented, making them

impossible for small manufacturers to replicate, and increasing the cost disadvantage even more.

5-16

EE-RM-PET-100 COMMENT 88
CHAPTER 6. MARK-UPS FOR PRICE DETERMINATION

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6.1 OVERVIEW 6-1

6.2 RETAIL MARK-UPS 6-2

6.2.1 Background 6-2

6.2.2 Retail Price Information 6-3

6.2.2.1 Consumer Expenditure Surveys (CES) 6-3

6.2.2.2 Dealerscope Merchandising Statistical and Marketing Reports 6-4

6.2.2.3 ELCAP Clothes Washer Sales Information 6-5

6.2.3 Manufacturer Price Information 6-5

6.2.3.1 Current Industrial Reports (CIR) 6-5

6.2.3.2 AHAM Fact Book 6-6

6.2.4 Retail Mark-ups from Manufacturer and Retail Price Information 6-6

6.2.5 Retail Mark-ups Estimated from Sec's Financial Statements 6-8

6.3 SALES TAX 6-10

6.4 MANUFACTURER MARK-UPS 6-10

6.4.1 Background 6-10

6.4.2 Manufacturer Price and Mark-up for the Baseline Standard Clothes Washer

6-11

6.4.3 Manufacturer Price and Mark-ups for Different Efficiency Levels 6-12

6.4.3.1 Pre-ANOPR Analysis 6-12

6.4.3.2NOPRAnalysis 6-12

LIST OF TABLES

Table 6.1 Retail Prices of Clothes Washers from 1986 through 1994 obtained from the

Consumer Expenditure Surveys 6-4

Table 6.2 Retail Prices of Clothes Washers from 1986 through 1995 estimated from

Dealerscope Merchandising's Annual Statistical Reviews 6-4

Table 6.3 Shipment Weighted Retail Prices of Clothes Washers from 1994 through

1997 Based on ELCAP Retail Sales Data 6-5

Table 6.4 Manufacturer Prices of Clothes Washers from 1986 through 1996 Estimated

from Current Industrial Reports 6-6

Table 6.5 Manufacturer Prices of Clothes Washers from 1986 Through 1996 Estimated

Using Data from the Aham Fact Book 6-6

Table 6.6 Retail Mark-ups for Clothes Washers from 1986 Through 1994 Using Retail

Prices from the Consumer Expenditure Surveys, and Manufacturer Prices

from the Current Industrial Reports 6-7

Table 6.7 Retail Mark-ups Estimated from Different Data Sources 6-8

6-i

EE-RM-PET-100 COMMENT 88
Table 6.8 Gross Margins for Retailers of Electronics, Home Office Equipment and

Major Appliances ................................................ 6-9

Table 6.9 Manufacturing Cost of a Baseline Clothes Waher Estimated from the

Industry Cost Structure .......................................... 6-11

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

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

LIST OF FIGURES

Figure 6.1 Average Costs and Mark-ups for the Baseline Clothes Washer 6-1

Figure 6.2 Retail Mark-ups Estimated from Different Data Sources 6-8

6-u

EE-RM-PET-100 COMMENT 88
CHAPTER 6. MARK-UPS FOR PRICE DETERMINATION

6.1 OVERVIEW

The following figure illustrates the representative prices and mark-ups for a typicala V-axis

clothes washer being sold in the U.S. marketplace:

Figure 6.1 Average Costs and Mark-ups for the Baseline Clothes Washer

To perform LCC analysis, the Department used a 2-step mark-up approach where: (a) the

manufacturing costs (i.e., full production costs) are marked up to the manufacturer price using a

manufacturer mark-up; and (b) the manufacturer price is marked up by a retail mark-up to arrive at

the retail price. The price paid by the consumer includes the sales tax ill addition to the retail price.

This sales tax is accounted for by using a sales tax mark-up over the retail price of the clothes

washer.

The Department used a fixed retail mark-up of 1.40, and a fixed mark-up of 1.052 to cover

the sales tax. The manufacturer mark-up over full production costs was found to be 1.35 for the

baseline unit.

am this description a typical unit refers to a high production volume model with high market share (industry

average); not necessarily a minimally complying unit under NAECA, or a unit with an MEF value of 0.817 (AHAM

baseline). Currently no data exists that would allow the Department to associate sales information on the basis of

the MEF descriptor to be used in the present rulemaking. In the absence of specific price information for a baseline

(0.817 MEF) clothes washer, typical values are used as default values for the baseline model. Since the life-cyclecost (LCC) analysis uses differential costs only, the absolute value of the baseline unit cost has no impact on LCC

and payback analysis. The absolute value of the baseline unit cost is important, however, if price survey

information is used to compare prices derived from a mark-up over cost with prices observed in the market.

6-1

EE-RM-PET-100 COMMENT 88
Based on the information above, the total mark-up from full production costs to consumer

price is 1.990.

Section 6.2 of this document presents a discussion on retail mark-ups, presenting current and

historical retail mark-ups for clothes washers. Section 6.3 presents a brief discussion on sales tax

and its effect on consumer price. Section 6.4 outlines the Department's methodology for estimating

manufacturer mark-ups.

6.2 RETAIL MARK-UPS

The objective of this section is to estimate the manufacturer price-to-retail price mark-up for

clothes washers from the available sources of price information.

6.2.1 Background

One measure of the effect of appliance efficiency standards on consumers is the change

(increase) in the purchase price of the appliance. A more stringent standard usually results in

increased manufacturing costs to the manufacturers. These increased costs (and associated margins)

are passed-through from the manufacturers to the retailers and eventually to the consumer in the form

of higher purchase prices.

It is important to identify what proportion of the standards-induced costs will be reflected in

retail prices, as this mechanism is important for the rulemaking in two ways: a lower margin over

incremental manufacturing costs passed-through justifies a less stringent standard from a

manufacturer impact standpoint; and has the opposite effect of lowering consumer LCC which

justifies a more stringent standard from a consumer perspective.

Retailers buy appliances (clothes washers in this case) from manufacturers and sell them to

consumers at higher prices to cover their operation costs and profit margins. The amount by which

the manufacturer price (price paid by the retailer to the manufacturer) is marked up by the retailer

to arrive at the retail price is referred to as the retail mark-up.

In this section we estimate the manufacturer price-to-retail price mark-up for clothes washers

(i.e., the retail mark-up) based on available historical market information. Sources of information

for the retail price of clothes washers include:

(1) Consumer Expenditure Surveys, conducted by the Bureau of Labor Statistics in conjunction

with the Bureau of Census'

(2) Dealerscope Merchandising's Annual Statistical Surveys2

(3) ELCAP price database3

6-2

EE-RM-PET-100 COMMENT 88
Sources of information for the manufacturer price of clothes washers include:

(1) Current Industrial Reports, U.S. Department of Commerce4

(2) Association of Home Appliance Manufacturers's Fact Book, 1997

Sections 6.2.2 and 6.2.3 present the retail and manufacturer price data, respectively, along

with short descriptions of the data collection procedures and the characteristics of each of these data

sets. These data sets are then used to arrive at the retail mark-ups which are reported and compared

in Section 6.2.4. Retail prices from each data source are divided by manufacturer prices from each

of two sources for manufacturer price, thereby resulting in six different sets of estimates for retail

mark-ups. Section 6.2.5 presents an analysis of financial statements (SEC 10-K reports) of a few

appliance retailers to get an understanding of gross margins in the appliance retail business.

6.2.2 Retail Price Information

6.2.2.1 Consumer Expenditure Surveys (CES)

Consumer Expenditure Surveys (CES) provide information on the buying habits of American

consumers, including data on their expenditures, income, and consumer unit (families and single

consumers) characteristics. The survey consists of two components: a quarterly Interview Survey

and a weekly Diary Survey, each with its own questionnaire and sample. Data collection is carried

out by the Bureau of Census under contract with the Bureau of Labor Statistics (BLS).

The data are collected in independent Quarterly Interview and Weekly Diary surveys of

approximately 5,000 sample households. Each survey has its own independent sample, and each

collects data on household income and socioeconomic characteristics. The Interview survey includes

monthly out-of-pocket expenditures, such as housing, apparel, transportation, major home

appliances, health care, insurance, and entertainment. The Diary survey includes weekly

expenditures of frequently purchased items, such as food and beverages, tobacco, personal care

products, and non-prescription drugs and supplies.

Table 6.1 shows the unweighted average purchase price of clothes washers as reported in the

consumer expenditure surveys. These values represent the price to consumers net of a trade-in and

represent purchases by individuals. These values are reported for the period of time 1986 through

1994. Table 6.1 also shows the retail price of these washers. The retail prices were estimated by

subtracting the sales tax from the purchase price paid by consumers (based on sales tax rates and

shipments of clothes washers in all the 50 states, a shipment weighted average sales tax of 5.2% was

calculated).

6-3

EE-RM-PET-100 COMMENT 88
Table 6.1 Retail Prices of Clothes Washers from 1986 through 1994 obtained from the

Consumer Expenditure Surveys

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994

Purchase Price ($) 431.98 432.29 437.60 442.23 444.21 444.05 435.21 419.43 435.06

RetailPrice($) 410.63 410.92 415.97 420.37 422.25 422.10 413.70 398.70 413.56

6.2.2.2 Dealerscope Merchandising Statistical and Marketing Reports

Dealerscope is the monthly trade publication for retailers of consumer electronics, major

appliances, and computers. The magazine covers product news, industry trends, and new

technologies, along with reports on the marketing, branding, merchandising, and retail strategies

of vendors and dealers.

Dealerscope reports contain one-year and five-year unit shipments industry-wide and the

retail value of these shipments. In these reports the data is based on information provided by

leading manufacturers. Companies are asked to indicate how much the overall total shipments

and average retail prices have changed for the industry, and for the product category.

Manufacturers are not asked for the annual changes in their own companies's shipments or in

retail prices of their own brand of merchandise.

Table 6.2 provides the retail price of clothes washers estimated from the statistical

reviews. The estimated retail value of clothes washers shipped from factories is divided by the

clothes washer units shipped industry wide to arrive at the per unit retail price.

Table 6.2 Retail Prices of Clothes Washers from 1986 through 1995 estimated from

Dealerscope Merchandising's Annual Statistical Reviews

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995

Retail Price ($) 439.3 440.4 440.4 406.1 410.2 415.0 382.8 382.7 394.2 394.2

6-4

EE-RM-PET-100 COMMENT 88
6.2.2.3 ELCAP Clothes Washer Sales Information

The ELCAP service collects sales data (retail prices) on clothes washers from a number

of retailers-consumer electronics superstores, appliance stores, and mass merchants. Table 6.3

presents shipment weighted retail price for the years 1994 through 1997. (The 1997 retail price

is based on sales data through August 1997.)

Table 6.3 Shipment Weighted Retail Prices of Clothes Washers from 1994 through 1997

Based on ELCAP Retail Sales Data

Year 1994 1995 1996 1997

Retail Price ($) 393.00 371.92 390.07 388.21

6.2.3 Manufacturer Price Information

6.2.3.1 Current Industrial Reports (CIR)

The CIR program has been providing monthly, quarterly, and annual measures of

industrial activity for many years. The primary objective of the CIR program is to produce

timely, accurate data on production and shipments of selected products. The data are used to

satisfy economic policy needs and for market analysis, forecasting, and decision making in the

private sector. The CIRs include statistics for the United States on the quantity and value of

shipments along with comparative data on exports, imports, and domestic output.

The CIR program uses a unified data collection, processing, and publication system. The

census bureau updates the survey panels for most reports annually and reconciles the estimates to

the broader-based annual survey of manufactures and the census of manufactures. The census of

manufactures provides a complete list of all producers of the products covered by the CIR

program and serves as the primary source for CIR sampling. The CIR program includes a group

of mandatory and voluntary surveys. Typically, the monthly and quarterly surveys are conducted

on a voluntary basis. Those companies that choose not to respond to the voluntary surveys are

required to submit a mandatory annual counterpart corresponding to the more frequent survey.

The figures on quantity and value of shipments represent physical shipments of all

products sold, transferred to other establishments of the same company or shipped on

consignment, whether for domestic or export sale. The value represents the net sales price, f.o.b.

plant, to the customer or branch to which the products are shipped, net of discounts, allowances,

freight charges, and returns. Shipments to a company's own branches are assigned the same

value as comparable appropriate allocation of company overhead and profit. Products bought

and resold without further manufacture are excluded.

a ELCAP service was discontinued at the end of 1997. Clothes washer retail sales are currently being

tracked by INTELLECT ASW.

6-5

EE-RM-PET-100 COMMENT 88
Table 6.4 provides the estimated manufacturer price of clothes washers. The value of the

clothes washers shipped from factories is divided by the quantity of shipments to arrive at the per

unit manufacturer price.

Table 6.4 Manufacturer Prices of Clothes Washers from 1986 through 1996 Estimated

from Current Industrial Reports

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

Mfgr. Price

($)

272.6 269.9 262.0

_______

277.3

_______

278.1

_______

275.9

________

277.6

_______

283.8

________

279.0

________

273.2

_______

275.2

________

6.2.3.2 AHAM Fact Book

The AHAM Fact Book is a comprehensive collection of facts defining the U.S. major

home appliance industry, its market and its products. The Association lists both:

the total manufacturers' sales of clothes washers (excludes freight charges or extended

warranty costs), and

the industry unit shipments (domestic and exports) of clothes washers.

The above stated information can be used to arrive at an average per-unit manufacturer

price for clothes washers, presented in Table 6.5.

Table 6.5 Manufacturer Prices of Clothes Washers from 1986 Through 1996 Estimated

Using Data from the Aham Fact Book

Year 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996

Manuf.

Price(S) 265.7 263.9 269.1 277.7 286.7 287.8 291.3 292.4 299.4 302.9 287.4

6.2.4 Retail Mark-ups from Manufacturer and Retail Price Information

Table 6.6 shows average retail mark-ups over the 9-year period, 1986 through 1994, for

clothes washers sold in the U.S. The retail mark-ups in this table are obtained using

manufacturer and retail price information obtained from governmental sources-retail price

information from the Consumer Expenditure Surveys conducted by the Bureau of Labor

Statistics, and manufacturer price information from the Current Industrial Reports prepared by

the Bureau of Census.

6-6

EE-RM-PET-100 COMMENT 88
Table 6.6 Retail Mark-ups for Clothes Washers from 1986 Through 1994 Using Retail

Prices from the Consumer Expenditure Surveys, and Manufacturer Prices from

the Current Industrial Reports

Year Retail Price (CES) Manuf. Price (CIR) Retail Markup

1986 410.6 272.6 1.51

1987 410.9 266.9 1.54

1988 416.0 262.0 1.59

1989 420.4 277.3 1.52

1990 422.3 278.1 1.52

1991 422.1 275.9 1.53

1992 413.7 277.6 1.49

1993 398.7 283.8 1.40

1994 413.6 279.0 1.48

Table 6.7 gives the retail mark-ups estimated using price information from different data

sources explained earlier in the text, and the same information is presented graphically in Figure

6.2. For the period 1986 through 1996, the average retail mark-up varies from a minimum of

1.33 (in 1995) to a maximum of 1.62 (in 1988).

6-7

EE-RM-PET-100 COMMENT 88
Table 6.7 Retail Mark-uns Estimated from Different Data Sources

Year Retail Mark-up

(Dealerscope)

AHAM)

Retail

Mark-up

(Dealerscope)

(CIR)

Retail

Mark-up

(CES)

(AHAM)

Retail

Mark-up

(CES)

(CIS)

Retail

Mark-up

(ELCAP)

(AHAM)

Retail

Mark-Up

(ELCAP

(CIR)

Average

Retail

Mark-up

1986 1.65 1.61 1.55 1.51

_______

1.58

1987 1.67 1.65 1.56 1.54 1.61

1988 1.64 1.68 1.55 1.59 1.62

1989 1.46 1.46 1.51 1.52 1.49

1990 1.43 1.47 1.47 1.52 1.47

1991 1.44 1.50 1.47 1.53 1.49

1992 1.31 1.38 1.42 1.49 1.40

1993 1.31 1.35 1.36 1.40 1.36

1994 1.32 1.41 1.38 1.48 1.31 1.41 1.39

1995 1.30 1.44 1.23 1.36 1.33

1996 1.36 1.41 1.39

l.8

_______

_______ - =

-e-ELcAPAHAM

1986 1988 1990 1992 1994 1996

Year

Figure 6.2 Retail Mark-ups Estimated from Different Data Sources

6.2.5 Retail Mark-ups Estimated from Sec's Financial Statements

Information relating to the gross margins (or gross profit) of appliance retailers can be

obtained from their SEC 10-K financial statements. Table 6.8 presents gross margins for some

6-8

EE-RM-PET-100 COMMENT 88
appliance retail companies (Best Buy, Circuit City Stores, Lowe's, and Sun T.V. and Appliances).

Most of these retailers sell electronics and home office equipment along with household appliances.

The margins in Table 6.8 represent the average of the margins that retailers obtained from sales in

all the above mentioned categories. On average, appliance sales are more profitable (i.e., obtain

higher margins) than sales of personal computers, T.V. 's and other electronics due to the intensely

competitive and highly promotional pricing environment in the electronics retail environment.a As

a consequence, some retailers are trying to further increase their margins by expanding the appliance

part of their business and by putting greater emphasis on the sale of extended service contracts.b

Table 6.8 Gross Margins for Retailers of Electronics, Home Office Equipment and Major

Appliances

Company

_________________________

Gross margin

(Avg.: 1990-1996)

% Revenue from

Appliances

Retail

mark_up*

Retailer A 25.2% 12.0 1.34

RetailerB 26.3% 15.0 1.36

Retailer C 16.2% 9.0 1.19

RetailerD 25.7% 17.5 1.35

Typically in the retail industry, gross profits, as reported in SEC 10-K statements, are

obtained by subtracting the "cost of sales" from the "net sales." Dividing gross profit by the net sales

gives the gross margin. Gross margin represents the mark-up that retailers receive over the total of

the:

price that the retailers pay to the manufacturers for buying the goods,

costs involved in the process of buying the goods from manufacturers (these might include some

transportation costs, administration and labor costs), and

costs of maintaining and operating warehouses where the goods are stocked after they are bought

from manufacturers.

From the above description of gross margins, it can be seen that the retail mark-ups (defined

earlier in this write-up as the ratio of retail price to manufacturer price) will be, in general, higher

than what the gross margins indicate. This is because in addition to profits and SG&A, the retail

mark-ups will also have to cover the costs incurred by retailers for buying and warehousing

activities. The buying and warehousing costs as a percentage of the net sales or revenues are not

available.

a Source: Standard and Poor's Stock Reports on Circuit City Stores and Best Buy.

b Source: Standard and Poor's Stock Reports on Best Buy.

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6.3 SALES TAX

Consumers pay sales tax in addition to the retail price at the time of purchasing an appliance.

This additional margin for sales tax needs to be reflected in the mark-up from manufacturer price

to consumer price.

For the year 1995, the shipment weighted sales tax on clothes washers was calculated to be

5.2%. This information is based on individual sales tax rates for 50 states and weighted by the

clothes washer shipments (source: AHAM) in each of these states. Hence, a mark-up of 1.052 is

used to cover the sales tax.

In the year 1994, for which retail price is available from all the three sources, namely, CES,'

Dealerscope2 and ELCAP,3 the average clothes washer retail price is $400.25. Looking at Tables

6.2 and 6.3, there seems to be no discernible change in clothes washer retail prices since 1994.

Hence (in the absence of price information specific to clothes washers with an MEF value of 0.817),

the Department used $400.25 as the baseline retail price for the clothes washer rulemaking analysis.

Adding a 5.2% sales tax results in a baseline consumer price of $421.10.

Looking at Table 6.7, the retail mark-up, on average, in the past three years has been around

1.40. Adding a sales tax of 5.2% on top of the retail price results in a manufacturer price-toconsumer price mark-up of 1.473. This mark-up of 1.473 is in agreement with the mark-up of 1.475

used in the 1991 report to AHAM entitled "Financial Impact of DOE Top Loading Horizontal Axis

Standards on U.S. Washing Machine Manufacturers." 6 Hence, the Department of Energy used a

retail mark-up of 1.40, and a sales tax mark-up of 1.052 to arrive at the consumer price for the

clothes washer rulemaking analysis.

6.4 MANUFACTURER MARK-UPS

The objective of this section is to outline a methodology for estimating the mark-up from

manufacturing cost to manufacturer price for the clothes washer rulemaking analysis.

6.4.1 Background

In order to meet the new appliance efficiency standards, manufacturers may have to introduce

design changes in their product lines. These design changes usually result in increased

manufacturing costs. The increased manufacturing costs are "passed-through" from manufacturers

to retailers and eventually to consumers in the form of higher purchase prices.

In this section the manufacturing cost to manufacturer price mark-up is estimated. This is

referred to as the manufacturer mark-up. The manufacturer mark-up has an important bearing on

the manufacturers's profitability, as a higher mark-up suggests that manufacturers can pass-through

the variable costs and some of the product conversion costs (the fixed costs) to retailers and

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eventually to consumers; whereas a lower mark-up implies that manufacturers will not be able to

fully recover the necessary investment in plant and equipment.

6.4.2 Manufacturer Price and Mark-up for the Baseline Standard Clothes Washer

The average retail price of a clothes washer in 1994 was $400.25 (as discussed in Section

6.3). Using a retail mark-up of 1.40 (also discussed in Section 6.3), the baseline manufacturer price

would be $285.90.

Manufacturing cost estimates for the baseline clothes washer can be estimated from the

baseline manufacturer price ($285.90) and the industry cost structure developed in Section 3.10.

This is shown in Table 6.9. The break-up of the price is based on the assumption that in order to

earn a satisfactory return, revenues from the sale of goods (and hence the manufacturer price) must

be large enough both (1) to recover costs and (2) to earn a profit that provides a satisfactory return

on investment.

Table 6.9 Manufacturing Cost of a Baseline Clothes Waher Estimated from the Industry

Cost Structure

Per Unit Cost ($)

Material 148.7

Labor 29.3

Overhead 33.5

Full Production Cost 211.5

The full production cost of a baseline clothes washer is estimated to be $211.50. The full

production cost (also called the inventory cost) and the non-production cost together constitute the

full cost of a product. Full production cost is the sum of the direct material cost, the direct labor

cost, and the overhead cost which includes depreciation (-3.5% of revenues). The non-production

costs include selling costs, general and administrative costs, research and development costs, and

interest costs. The full cost of a product and its components are shown in Chapter 5, Figure 5.1.

Baseline manufacturer mark-up is defined as the increase in price over the full production

cost of a baseline clothes washer, and is calculated as:

Manufacturer Price Baseline Manufacturer Mark-up

= Full Production Cost

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