Does product design really determine 80% of manufacturing cost?

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-UZ:'

WORKING

PAPER

ALFRED

P.

SLOAN

SCHOOL

OF

MANAGEMENT

Does

Product

Design

Really

Determine

80%

of

Manufacturing

Cost?

by

Karl T. Ulrich Scott A.

Pearson

WP

#3601-93

August

1993

MASSACHUSETTS

INSTITUTE

OF

TECHNOLOGY

50

MEMORIAL

DRIVE

CAMBRIDGE,

MASSACHUSETTS

02139

Does

Product

Design

Really

Determine

80%

of

Manufacturing

Cost?

by

Karl T.Ulrich Scott A.

Pearson

WP

#3601-93

August

1993

Does Product

Design

Really Determine

80%

of

Manufacturing

Cost?

KarlT. Ulrich* and Scott A. Pearson

Massachusetts Instituteof

Technology

Sloan School of

Management

Cambridge, Massachusetts

02139

Abstract

Many

design researchers and practitionersmotivate their

work

with the claim that

80%

ofthe eventual manufacturingcost ofa productis determinedby the product design.

The meaning

of

this assertion hasnot been well defined, nor has

much

empiricalevidence been presentedto

support it. This paperaddresses thequestion of

how much

product design influences the

manufacturingcostofa product. Indoing so,

we

define the research question formally,

we

develop a

methodology

for answering thequestion, and

we

provide a specific answer, undera particularsetof assumptions, fora class ofhigh-volume, electromechanical

consumer

products

—

automaticdrip coffee makers.

Our

methodology

includesproductarchaeology, the useofthe product artifactas a sourceofdata, and manufacturingcost modeling.

We

find thatforcoffee

makers, the variation inmanufacturing costs attributable todifferencesin product design is

slightly smallerin magnitude than the variation incosts attributable todifferences in

manufacturingsystems, for a specific range of

assumed

manufacturing systemparameters.

Acknowledgments

The

researchdescribedin thispaper

was

supported bythe National Science Foundationas

pan

of a Strategic Manufacturing Initiative Grantand by the

MIT

Leaders forManufacturing Program, a partnership

among

MIT

and 13 major corporations. E.

Yung

Cha

gathered

much

ofthe data

on

component

prices and

wage

rates.

We

are grateful forthe

many

people at Tredegar

Molded

Products

who

generouslyprovided time, data, and insights atvarious stages ofthisproject; in

particularCarl Peasley,

Guy

Vachon,

and

Doug

Miller.

The

staffofProductGenesis, Inc.

contributed to this research byevaluating the industrial designoftheproducts inourdata set.

We

also

acknowledge

helpful

comments, on

a previousdraft, by Steven Eppinger, Stephen

Graves, Chris Kemerer, Richard Locke, and MarcieTyre.

*

Addressallcorrespondenceto thisauthorat

MIT

SloanSchoolofManagement,50MemorialDrive,

Room

E53-390, Cambridge,

MA

02139,email:ulrich@mit.edu.

1. Introduction

Countless product design and developmentresearchers motivate their

work

with references to

studies that reveal thatproduct designdetermines

80%

(or

some

large percentage) of the

manufacturing cost ofa product;

we

have used suchreferences

many

times ourselves.

However,

few

references are

made

tothe original studies and little explanation is given for what such a

result might reallymean. For example, awidely usedengineering design textby

Ullman

(1992)

displays a table

showing

thatthe design of the product influences

70%

ofits manufacturingcost.

The

table in Ullman's textis

drawn from

an article in Manufacturing Systems (Miller 1988).

The

information in the article is derived

from

an internal Fordstudy.

When

we

tracked

down

the

Ford study, aFord

employee

said, "Oh, that

was

justan informal survey, I wouldn't base too

much

on

it." Anotherreference, usedto supportthe claim thatdesign determines

80%

ofcost,

describes a study in

which

engineers at Rolls

Royce

analyzed

2000

partdrawings anddiscovered

that

80%

ofthecostreduction opportunities required changes to the partdesign

(Symon

and

Dangerfield 1980).

The

beliefthatdesign determines

80%

ofthe manufacturingcostofa product has

become

partof the folkloreof product design and developmentresearchand practice

(we

use

80%

for

convenience, although the quoted figurevaries

from

70%

to

90%).

The

beliefis intuitive,

compelling, and is an irresistible introduction toapaperortalk.

The

belief, iftrue, has profound

implications formanufacturers. Itsuggeststhat productdesign is a

much

bigger leveron

manufacturingcost than otherfactors, such as plant location or operations

management

practices. Consider, however,

what

"design determines

80%

ofmanufacturingcost" mightreally mean.

One

widely held interpretation is thatoncea productis designed,regardless ofthe

way

the

manufacturing system isdesigned andoperated, the

minimum

possible manufacturingcost is

80%

ofthe

maximum

possible manufacturing cost. There isa basic conceptual flaw in such a

definition.

How

can there bea

maximum

manufacturingcost? Imagine, forexample, the rise in

cost ofa

molded

plastic product as injection

molding

yieldsdecline

from

99%

to

1%

due topoor

choicesofproduction process parameters.

Thereis also a basic logical flaw in the argumentthatifthe

minimum

possible manufacturing

cost is

80%

of the

maximum

possiblemanufacturing costthen product design is a critical activity

ofthe firm.

The

flaw arises

from

the assumption that

much

ofthe

80%

ofthe cost ofthe product

is underthe control ofthe productdesigners. Consider, for example, a firm designing and

producing electrical

components

that forfundamental physical reasons

must

contain a certain

amount

of gold.

The

manufacturingcost of the

component

may

be largely determined by the costofthe gold.

While

in thiscase the design ofthe productdoes

impose

a lower

bound

on manufacturingcost corresponding to the costofthe gold, the product designers have littlecontrol

over the cost. For this firm, trading on the gold market, and not product design,

may

be the

critical activity.

This paperaddresses thequestion of

how

much

product design influences the manufacturing cost ofa product. In doing so,

we

define the question formally,

we

develop a

methodology

for

answering the question, and

we

provide a specific answer fora class ofhigh-volume,

electromechanical

consumer

products

—

automatic drip coffee makers.

The methodology

we

present isnot intended for academic inquiry only. Rather,

we

believe the

methodology

is useful

to firms attempting to understand the relative leverage they can achievethrough theirdesign and

manufacturing efforts.

The methodology

consistsof

two

basic steps: (1) useproduct archaeology,orthe study ofthe product artifacts in the marketplace, todetermine the design content ofa groupof products

satisfying the

same

set of requirements, and (2) use a cost

model

toexplore

how

the differences

in design contentrelate todifferences inmanufacturing cost for a set ofdifferent manufacturing

scenarios.

The

paperis organized into six remaining sections. In section 2

we

provide theconceptual

framework

for ourstudy and

we

define the

"80

percent"

problem

formally. In section 3,

we

describe ourresearch approach. Section4describes the product archaeology

methodology

as applied to the coffee

maker

domain. Section 5 describes the manufacturingcostmodel. Section

6details the results and Section 7 is adiscussionofthe results andtheir implications.

2.

Conceptual

Framework

Figure 1 is a simple input-output

model

ofa manufacturingsystem.

The

system utilizes

equipment, information, tooling, energy, supplies, services, and aworkforce to transform

raw

Costs

may

be incurredin procuring these resources and in disposing ofthe wasteproducts.

Over

along timeperiod, the unit costofproducing finished goods can be thoughtofas the costofall

ofthe resources

consumed

(and ofthe waste disposal) overthattime period divided by the total

number

ofunitsproduced.

Equipment Information Tooling

polycarbonate), and part production processselection (e.g. molding vs. machining). These

decisions in turn constrain the manufacturing activities required toproduce the product.

Conversely, even given a particularproductdesign, manufacturing

managers

and engineers possess substantial latitude in determining the characteristics ofthe manufacturing system.

By

manufacturing system,

we

intend not only the basic layout of the plant and choice of process technologies, but the

management

practices as well.

They

can choose different site locations, different

make-buy

arrangements, anddifferent operations

management

practices.

More

formally, for agiven setof product requirements, R,

assume

n different product design alternatives, Dj (i= 1 to n). Also

assume

m

differentmanufacturing system alternatives,

Mj

(j=l

to m). R,

Mj

and Dj can be thought ofas vectors ofattributes. (In

most

cases, therewill be

infinite choices of design and manufacturing alternatives, but for simplicity

we

assume

a finite

set.)

The

combination ofadesign and manufacturing system determine a manufacturing cost.

We

define Cjj as the unitcost ofmanufacturing design Dj on manufacturing system Mj. Table 1

illustrates this concept.

We

define the design range,

DRj

,as the range ofthe manufacturingcostsof

D\

through

D

n

made

withmanufacturing system Mj.

We

definethe manufacturing range,

MRj

, as the range of

the manufacturingcosts ofDj

made

with manufacturing systems

M\

through

M

_m

.

For a given setof design and manufacturing alternatives,

we

can

now

compare

the design ranges with the manufacturingranges. Ifthe set of designs represents the range ofpossibilities

we

can

considerin aproductdesign and ifthe setofmanufacturing systems represents the range of

possibilities for the manufacturing system, then

we

have a

way

of

comparing

the latitude in

manufacturingcostdetermined by ourchoice of design tothe latitude inmanufacturingcost

determined by ourchoice ofmanufacturing system. If, for a particular context, the design range

is

much

larger than the manufacturing range then

we

would

conclude that product design is an important area of focus for the firm. Conversely, ifthe design range is smallrelative tothe

manufacturing range,

we

would

concludethat a focus

on

the manufacturing system

would

be

more

appropriate.

Although

aconfounding factor in any resource allocation decision is the required investmentto achieve eachofthe alternativesunderconsideration. Also note that in

general aproduct

development

organization does not simplychoose adesign

from

a set offully

ofskill andresourcesto be applied tothe design effort in the hope thatthey willachieve a

particular levelof design performance.

Table

1: Unit cost, _Qj, arises

from

achoice ofdesign,

D

_u and achoice ofa

manufacturing system, Mj.

The

manufacturing range,

MR,

is the range ofcosts for the

same

design

made

in different manufacturing systems.

The

design range,

DR,

is the range ofcosts forall the different designs assuming the

same

manufacturing system.

unique process technologies, the coupling between design decisions and manufacturing

capabilities

must

be considered

when

the design range and manufacturing range are interpreted.

3.

Research

Approach

At

least three questionsarise

from

the conceptual

framework

we

present:

How

does one

determine the set of design alternatives for a particular setof product requirements? (After all, if

one

knew

the setofalternatives, one

would

simply choose the best one.)

How

does one

determine the setofmanufacturing systemalternatives? and

How

can the design alternatives and manufacturing system alternativesbe used toestimate manufacturing costs? In this section

we

present ourapproach to these three questions anddiscuss ourchoice of an

example domain

of application.

Although

we

take the perspective of researchers in this work,

we

contend that the

methodology

we

present isappropriate for use by manufacturing firmsas well.

How

todetermine the setofdesign alternatives

Within ourconceptual

framework

adiscrete setof designs is used torepresent the latitude a firm possesses in designinga

new

product.

We

use the product designscurrently available in the

marketplace toapproximate the setofalternativesavailable toa firmdesigning a

new

product. This approach requires thatthere be a relatively large

number

of products and firmscompeting in

the marketplace

from which

we

can infer the expectedcharacteristicsofa

new

design.

The

approach also

assumes

thatthe range ofcapabilities anddesign effort

among

the different firms represents the distributionofcapabilitiesand design effort thatcould be exhibited in a

new

design. In taking this approach

we

explicitlyexcluderadical departures

from

the practices ofthe existing firms in the marketplace. Radicaldesign approaches might be classified as

advanced

developmentrather than productdesign.

Inorder todetermine the attributes ofthe setofdesigns,

we

analyzethe actual physical products available in the marketplace.

We

call this approach product archaeology

—

the study of

industrial practices by measuringcharacteristics ofthe physical product itself. Product

archaeology is similar to the competitive

benchmarking

some

firms perform

when

analyzing their

competitors' products

(Camp

1989). In fact,the

methodology was

inspired bya visit tothe

General

Motors

Vehicle

Assessment

Center

where

dozensof competitors' products are

directly observe factors like the

number

ofpans and the

number

offasteners, and

we

can use established estimation techniques fordetermining otherfactors such as the assembly labor

content and the processing requirements forthe fabricated parts.

While

several researchers have used the productas the unit ofanalysis (Clark and Fujimoto

1991,

Henderson

and Clark 1990, Sanderson and

Uzumeri

1992),

we

know

of noresearch on

product design that has

examined

the artifact itselfas a source ofdata.

As

aresearch

methodology, product archaeology offers several benefits. First, dataderived from observations

ofthe product itselfare highlyreliable. Unlike the

human

subject of an interview, the product

cannot forget and cannotmisrepresent facts. Second, the dataarereadily available. Researchon

dozens ofmanufacturers' products can be performed without permission, access tothe

company,

ortravel. Third, the data obtained from productarchaeology are public information. This allows

researchers to talk about specific manufacturers by

name

and allowsthe actual undisguiseddata

to be published.

How

todetermine the setof manufacturing systemalternatives?

The

setofmanufacturing systems in ourconceptual

framework

represents the set ofalternatives a manufacturer

would

have in setting up and operating a manufacturingsystem. Ifthis analysis

were performedwithin the context ofa specific firm, the setofalternatives mightrepresent the

different possible operating conditionsfor the firm's existing plantsand any

new

plants under

consideration.

These

systems mightbe characterized by, forexample,

wage

rates, available

raw

materials prices, and expected processingyields.

As

mentioned inthe introduction, there is

no

theoretical upper

bound on

manufacturingcost, sothe rangeofmanufacturing systems should represent the bestand worst systems thatcould reasonably be considered fora

new

product. For

the purposesofthis paper,

we

will

make

assumptions about the operatingparameters of a setof

manufacturing systems based

on

the literatureand ourpreviousresearch.

How

to

combine

a designalternative

and

a manufacturing systemalternative todeterminea manufacturing cost?

We

use a cost

model

toestimate a manufacturingcost for a particulardesign produced bya

particularmanufacturingsystem.

Our

model

is based

on

many

previous

modeling

efforts byus

and other researchers (Surietal 1993,

Mody

et al 1991,

Busch

1987, Ulrich etal 1993).

The

model

can be

more

or lesssophisticated, but

must

capture the impactofthe majordifferences in

design factors and in manufacturing system factors. For example, one aspect ofthe

model

might

be assembly cost.

The

model

might take the estimated assembly content ofa product and apply an assembly productivity factor anda laborcost factor to estimate the assembly cost.

The

assembly content is derived from the design, while the productivity and labor cost factors are

characteristics ofthe manufacturing system.

Example

Domain:

Coffee

Makers

We

use an

example

to illustrate the

methodology

andto

make

the conceptual

framework

specific.

We

chose automatic drip coffee

makers

as the product forour study for three

main

reasons.

First, there are

many

coffee

makers

that

implement

the

same

setof product requirements.

Each

model

in our sample isdesigned around the

same

brewing process and, according to

Consumer

Reports, delivers coffee that is ofequalquality

(Consumer

Reports 1991). Thisallows us to

avoid differences in manufacturing costs due todifferences in product requirements. Second,

coffee

makers

are relatively simple.

The

components

of coffee

makers

are large

enough

to

examine

easily and sufficiently limited in

number

to

make

the study manageable. Third, coffee

makers

are produced by adiverse groupofmanufacturers

—

large and small, U.S. and

international.

We

anticipate that this diversity will be associated with a wide range of

approaches todesign.

We

believe thatthe design of coffee

makers

involves

many

ofthe

same

issues as the designof

many

consumer

and industrial products including

power

tools, automobile ins jment panels, and

consumer

appliances.

These

products are high-volume, discrete, assembled

goods

involving

mechanical and electrical components. Similar core technologies that remain relatively stable

overtime are

employed

withineach of these classes.

The

specific

models

and manufacturers forour sampleare

shown

in table 2. For reference purposes,

we

listthe retail priceofeach coffee

maker

(adjusted fordifferences infeatures, such asclocks

and

timers), the market share ofthe manufacturer, the

number

ofunits sold by each manufacturer each yearin the United States, and the country in

which

the product is made.

Table

2: Basic information about the coffee

maker

manufacturers and models.

Figure2:

An

example

coffee

maker from

the data set, the

Rowenta

FG22-0.

4.

Using Product Archaeology

to

Determine

Design

Content

In order todetermine the design contentofthe 18 coffee makers,

we

first established values for a

setof metrics through directobservations ofthe products and theirconstituent pans.

We

then estimated additional metrics throughcalculations orbysoliciting information

from

vendors.

We

disassembled eachproduct andcreated abill ofmaterials

(BOM)

and a feasible sequence of

assemblyoperations.

An

example

BOM

is included in

Appendix

A. Four metricscan be

observeddirectly

from

the

BOM

and the piece parts: the total

number

ofparts, the

number

of part

numbers

(unique parts), the

number

ofplastic

molded

parts, and the

number

offasteners (includes screws, nuts, and clips).

The

parts fabricated by the manufacturerare either injection

molded

plasticorstamped sheet metal. For each injection

molded

part,

we

determined the type ofpolymer, the

pan

mass, the

geometric complexity, the

pan

wall thickness, the

number

ofactions

(moving

parts) required for the mold, and the percentage ofthe part surface corresponding toeach ofthe five standard

surface finish designations. For each sheet metal part,

we

determined the type ofmetal, the thicknessofthe metal sheet, the requiredlength and width ofsheet

consumed

foreach part, and

an estimate ofpartcomplexity

on

a scale of 1 to 5.

The

purchasedparts included fasteners, tubing, switches, wiring, heaters, and carafes.

We

described the fasteners interms oftheir type and size, tubing in terms of length anddiameter,

switchesin termsofthe type (slideror rocker, lightedornot), andwiring in terms oflength,

material, strain relieftype, gage, and color.

We

photographedthe heaters andcarafes. Using the

component

data and the photographs

we

solicitedprice quotes

from

U.S. suppliers forproduction quantities of 250,000, 500,000 and 1 million units peryear. (Forour study

we

assume

an annual

production

volume

of 1 million units, but

we

were interestedin what

economies

ofscale

may

exist in

component

procurement.

The

quotedprices drop

by

about

10%

asquotedproduction quantities double

—

a

90%

"learningcurve".)

The

metrics

we

estimated are

shown

in table 3.

A

summary

ofeachestimation techniqueis

listed. (The details oftheseestimation techniques are in [Pearson 1992].)

The

netresultofthe product archaeology andassociated estimation is the "design content"for

each product. This design contentcan be thought ofas theDj's inourconceptual framework.

Table 4

shows

the valuesofall ofthe design metrics foreachofthe coffee makers.

Table

3:

The

design metrics derived from the 18 coffee

makers

through the use of product archaeology. All metrics are estimates.

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5.

Modeling Manufacturing

Costs

We

adopt the basic cost

model

represented inequation 1. Following is a briefexplanation of

how

each term is modeled.

Appendix

B

gives the specific algebraic expressions relating the

manufacturing system parameters and the design parameters from the product archaeology to the

terms in the cost model.

C

=

C

assembly

+

Cpurchased-parts + ^molded-parts

+

^sheet-metal-parts+ Qooling + ^supervision

+

^inventory

+ Cf

aciiities +

C

energy ₍₁₎

Where,

forexample,

r

_{assembly -} assembly-content x assembly-labor-cost

assembly-productivity x assembly-yield ^ '

and assembly-content is in unitsof

Boothroyd-Dewhurst

hours, assembly-labor-cost is indollars per hour, assembly-productivity is anon-dimensional ratioreflecting the productivity ofthe

assembly workforce relative to the

Boothroyd-Dewhurst

metric, and assembly-yield is the fractionofproducts assembled correctly.

Assembly

content is a characteristic ofthedesign, while labor cost, assembly efficiencyand assembly yield are characteristics ofthe manufacturing

system.

The

costofpurchased parts is

modeled by

the pricequotes

we

obtained

from

U.S. suppliers divided by asourcing efficiency, reflecting either

more

orlesseffective purchasing efforts, anda

purchased

pans

yield.

The

cost of

molded

parts isdetermined by

raw

material usage, cycle time, requiredcapacity,

machine

cost, operator wages,

molding

yields, andthe

number

of

machines

run by each

operator.

The

costof sheet metal partsis determinedin a similar fashion.

The

cost of tooling is determined bythe estimatedtooling fabrication time times the tooling shop

rate,divided by the tooling life.

The

cost ofsupervision is determined

from

the estimatedassembly cost, the assembly laborcost,

The

costof inventory is determined from the inventory level, expressed asequivalentdays of finished goods inventory, the unit variable cost, and an inventory holding cost rate.

The

cost offacilities isdetermined byestimating the relative size ofa production facility

required toproduce 1 million units per year given theassembly and fabrication requirements

determined by the design and other

assumed

manufacturing parameters.

A

baseline of

5000

square meters of spaceis assumed.

The

cost ofenergy is determinedby estimating the costofmelting and processing the plasticin

the product. This is the

most

significant energy consumption associated with the product.

We

did notattempt toestimate the otherenergy requirementsfor stamping, materialshandling, or

small

power

tools.

The

cost

model

does not include

much

ofwhat

would

normally be considered plantoverhead.

There is

no

estimate of purchasing, shipping, receiving, quality control, materials handling, or senior plant

management.

As

we

mentioned in section 3, the manufacturing systemparameters usedin the

model

should represent the rangeof reasonable alternatives thatcould be used in producing the product. For an

on-going manufacturing firm, these alternatives

would

represent the setof operating conditions

thatmight be encountered in theexisting production facilitiesofthe firm orin any

new

facilities

underconsideration. For ourpurposes,

we

considerthe setofmanufacturing systemalternatives

that

may

be usedby any ofthe manufacturersinourdata set.

We

know

withcertainty that these

manufacturers

make

coffee

makers

in a variety of countries with markedly different

wage

rates.

We

do

not

know

with certainty

what

the othermanufacturing parameters are for thesesystems.

Our

approach is tobase the assumptionsabout differentmanufacturing systems

on

published

parameters foranalogous production systems inorderto

make

reasonable estimates ofthe range ofmanufacturingcoststhat could be encounteredby these differentmanufacturers.

The

manufacturers inourstudy

make

productsin atleast 12 different plants (the

sum

ofthe

number

ofdifferentcountries in

which

each manufacturer assembles products). Rather than

consider 12manufacturing system alternatives,

we

willconsideronly 6,

assuming

that several of the manufacturers' plants have quite similarcost structures.

The

six plants

we

consider

correspond toa well run and poorly run plant in a low,

medium,

and high-cost

economic

environment.

The

manufacturing parameters driven by the

economic

environmentare

shown

in

table 5, while those parametersdriven by the

way

the plant is run are

shown

in table 6.

The

parameters

we

assume

to be constant forall the plants are

shown

intable 7.

Table

5:

Assumed

manufacturing parameters corresponding to a low,

medium,

and high-cost

economic

environment. All values are derived either

from

data supplied by the U.S. Bureau of

Labor

Statisticsor from analogous systems

Table

6:

Assumed

manufacturing parameterscorresponding toapoorly run and

well runplant.

The

values based onlyon ourobservations and assumptionsare derived

from

ourpriorexperience with

more

than adozen analogous molding,

Table

7:

Assumed

manufacturing parameters shared across all plants.

Molding machine

cost (US$), (Busch 87) basic

molding

machine

cost

y y y

X

y ~~ _'y •J ^ a

c

C '-* Ml

Table

9: Detailed

breakdown

of estimated costs for the

Rowenta

FG22-0. These

estimatedcostscorrespond to awell run plant in the

medium-cost economic

environment.

Considera small appliance manufacture with

two

existing manufacturing systems: a well run plant in a high-costenvironment and a poorly run plant in a low-cost environment. Ifthis

manufacturer were considering entering thecoffee

maker

market, the manufacturing range might

be defined by the

two

existing plants plus a well run plant in the low-costenvironment. This set

assumes that the firm could invest in improving the performanceof theircurrent poorly run plant

in the low-cost environment and

would

notlet theother plant's operationsdeteriorate.

Under

theseconditions, assuming the manufacturing parameters in our study, themanufacturing range

would

be only

31%

ofthe average manufacturing cost, while thedesign range

would

be

48%.

Conversely, one can imagine a situation in

which

a firm with an existing low-cost design might have very littledesign range and a large manufacturing range.

Industrial designissues

Although the coffee

makers

are functionally identical, they exhibit significant differencesin

industrial design, the aesthetic and ergonomic characteristicsofthe products.

We

suspect that

industrial design influences

consumer

behaviorand therefore firms

may

be willing to suffer highermanufacturingcosts inorderto achieve higher levelsof industrial design. In a related

study (Pearson 1992)

we

tested the hypothesis that thequality ofindustrial design is positively correlatedwithmanufacturing cost.

We

measured

industrial designquality by asking9

professional product designersto rank orderthe 18 products withrespect to aestheticsand

ergonomics. In

summary,

we

foundthat the designers' opinions were consistent with one

another.

However,

there

was no

significantcorrelation ofeitheraestheticsorergonomics with

manufacturingcost.

We

didfindthat industrial designquality is positivelycorrelated with our

estimate ofone element ofmanufacturing cost, toolingcost, and is positivelycorrelatedwith

estimated toolinglead time (p

<

0.01).

One

explanation forthisresult isthat industrial designers

almost alwaysadd geometric complexity toaproduct inorder tocreate visual interest. This

additionalcomplexity

may

notrequire

more

materialorprocessingtime, but

may

require

more

toolingcomplexity andtherefore

more

tooling costand tooling fabrication time. Becausethe production

volumes

ofcoffee

makers

are so high, the tooling cost differences

amount

toonly a

few

cents perproduct and soare probably not significant factors in determining the costsof

good

industrial design.

Costvs.price

The

manufacturers suggested retail prices for the coffee makers in ourstudy range

from

$19.99

to $79.99.

Some

ofthis range in price isrelated todifferences in features, such as timers and water level indicators,

which

we

did not include in our study ofmanufacturing costs. In our related study,

we

adjusted the retail price for these differences in features.

The

details ofthis

adjustment are in [Pearson 1992]. Although ourcost adjustment procedureis approximate, the hypothesis that cost and price are positively correlated is notsupported byour data.

Some

ofthe

most

expensive

models

have the lowest manufacturing costs, and

some

ofthe least expensive

models

have relatively high manufacturing costs. For example, the

Rowenta

FG22-0

sells for a feature-adjusted price of$40.60(unadjusted price is $49.99) while

we

estimatedits costat $5.92 for a well run plant in a

medium-cost

environment.

The

Toastmaster sells for a feature-adjusted priceof$18.70 (unadjusted price is $22.99) while

we

estimated its cost at $7.61.

Quality

Perhaps there are differences in manufacturing costs arising from differences in product quality.

In this context

we

intend quality to

mean

durability, reliability, androbustness, because as

we

have noted, the quality ofthecoffee

made

bythe

models

isuniform. There are not

many

failure

modes

forcoffeemakers.

Based

on interviews with

two

coffee

maker

designers,

we

found that

failure ofthe heating elements dueto calcification ofthe heatertube is the primary failure

mode

ofthe product. Because allofthe heatingelements have basically the

same

tube geometry, this

calcification should occurwith equal frequency in all the models. Occasionally the

electromechanical components, the thermostat andswitch, fail.

We

found the costdifferences

among

the

most

expensive and leastexpensive switches and thermostats to be on the orderof

$0.20, so the relationship betweenquality andcost is slight. Also, the products with apublic

perception ofquality, primarily the

German

products, exhibitcosts

no

higher than average.

Plant location vs. design vs. operations

improvement

Given

the cost

model

and thedesign data,

we

can explore

some

ofthe decisionsa firm faces

when

trying toreduce costs. Within ourconceptual

framework

there are atleast three

approaches toreducing costs:

improvements

in design, changes in the

economic

environment, and changes in production

management

practices. Considera firmin ahigh-costenvironment, such as

Germany,

with a poorly run plantand an expensive design.

The

firm could

move

their

operations toa low costenvironment such as Mexico; they could attempt to improve the

efficiencyof theirproduction system; or they could improve the design ofthe product.

One

of

the resultsof thisresearch is toquantify the benefits available through an

improved

design.

Consider the specific

example

ofthe

Krups

178, the most costlydesign in our study.

Assume

(for purposesofillustration only) that it were

made

in apoorly run plantin ahigh-cost

economic

environment.

We

estimate the manufacturing cost underthese conditions tobe $14.54.

Krups

could

move

toalow-cost environment, retaining the

same

design. Iftheir

new

plant were poorly run they could reduce theircosts to$9.73. Ifthe plantwere wellrun, they could reduce their

coststo$8.06.

Krups

couldalso redesign theirproduct.

Assuming

they couldachieve adesign

like thatofthe

Rowenta FG22-0,

Krupscould reduce theircosts to $9.72 in theiroriginal plant. Ifthey

improved

their plantoperations atthe

same

time,they could reduce theircosts to$6.98.

Perhaps they could improve theirdesign,

move

their plant,

and

improve theiroperations.

Under

theseconditions they could achieveacost of$4.98.

Of

course adecision about

where

tofocus

improvements

depends notonly on the savings buton

the required investment.

The

result

we

find

most

interesting is thatcost reduction through redesignof the product

may

be an extremelyattractive alternative to

moving

operations toa

low

cost

economic

environment.

Have

manufacturers adoptedconsistentdesign

and

plantlocation strategies?

O

mightexpectthatfirms operating in high-cost environments

would

minimizethe assembly

contentoftheirdesigns andthose in low-costenvironments

would

not

The

average estimated

assembly time for the fiveproducts assembledin China,Taiwan, and

Mexico

is 0.105 hours.

The

average estimatedassembly timefor the seven productsassembled in the UnitedStates is

0.109 hours.

The

six products assembledin

Germany

had an average estimated assembly time of

0.094hours.

Given

thatthe averageestimated assemblytime forall productsis0.100 hoursand

the range is0.086 hours,

we

do

not find thedifferences

among

the locations significant.

How

todesign a low-costcoffee

maker

Based

on

ourobservationsofthe 18

models

in ourstudy,

we

can suggest

some

guidelinesfor

minimizing thecost ofa high-volume electromechanical product like acoffee maker.

Some

of these guidelines are:

•

Use

inexpensive materials.

The dominant

material forcoffee makers is polypropylene,

however

some

ofthe

components

on

some

ofthe

models

are

made

of polycarbonate, a

much

more

expensive(by a factorof

two

or three) polymer.

The

relative merits of the

two

materials is covered at length in [Freeze 1991].

•

Minimize

the use of material.

The

costof the materials in a coffee

maker

is quite

significant. Both wall thickness and overall

pan

dimensions should be minimized in

orderto reduce the use ofmaterial. Careful structural design can achieverigidity while

minimizing the use ofmaterial.

•

Minimize

the

number

of pans. This is a standard design-for-manufacturingguideline.

Adherence

to this guideline through the consolidation of plastic pans results in less

expensive

molded

pans, because consolidaung

two

plastic pans reduces tooling costs and minimizes the plastic that

much

be scrapped with each shot ofthe injection mold.

However,

note thattooling lead times

may

beextended ifone particularly

complex

part

results

from

the consolidation offunction. (See [Ulrich et al 1993] for a thorough

discussion ofthis issue.) Minimizing the

number

ofpans also, ingeneral, reducesthe

assembly content ofthe product.

• Concentrate high-quality surface finishes only

where

surfaces are visible. Surface finish

is one ofthe

pan

attributescontributing totooling cost and lead time.

The

inner surfaces

of

pans

do

not have toexhibithigh quality finishes.

•

Work

closelywith suppliers tominimize purchased pans costs.

From

25%

to

50%

of the

cost ofacoffee

maker

is

made

up ofpurchased components.

Product

Archaeology

as a research

methodology

Much

ofthe research thathas been

done

in productdevelopment hasrelied on subjectivedata

drawn from

interviews and surveys. For example, in the

MrT

International

Motor

Vehicle

Research

Program

study (MacDuffie 1991), the design-for-assembly variable forautomobiles

was

determined byasking manufacturers to subjectivelyrate the ease ofassembly of other manufacturers' products. In ourview,

many

of the success factorsofproduct development are

difficult to address at an aggregate level based

on

subjective data.

We

have developed the

product archeology

methodology

as an approach to gathering objective datafor product

development

research.

The methodology

offers several benefits.

A

relatively large sample size

can be explored withoutintensive interaction with

many

manufacturers.

The

artifact provides

completely accurate data; itdoesn't forget, omit,ormisrepresent information.

Because

the

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Busch, John V., "TechnicalCost

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Department of Materials Science and Engineering, Cambridge,

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R.C.,Benchmarking,

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—

FlexibleProduction Systems and Manufacturing Performance in the

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ManufacturingSystems,

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Appendix

A. BillofMaterials for the

Rowenta FG22-0

Coffee

Maker

PART

Main

tank Base piece Filtercone

Machine

cover

Tank

cover Base plate Potcover Pot handle Potring

One-way

elbow

valve

Elbow

valve

Condenser

Filterbaffle Heaterplate Heat shield Heaterbracket Heatertubes (4) Heater seal Carafe Heater Circlips (5)

Screw

(tamperproof) Switch

Power

cord

Wirel

Wire2

Wire3

Wire4

Wire

sleeves (3) Feet (2)

Check

valve-part

A

Check

valve-part

B

Handle

adhesive

Thermostat Thermostat nut

Temperature fuse

TYPE

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polypropylene

injection

molded

polycarbonate injection

molded

polycarbonate injection

molded

polycarbonate injection

molded

polypropylene

injection

molded

polypropylene

stamped

aluminum

stampedcold- rolled steel

stampedcold-rolled steel

purchased, rubber

purchased, silicone rubber

purchased(Schott)

purchased

purchased fasteners

purchased fastener

purchased toggle, painted

1000

mm,

zig-zag strain relief,one spade, one crimp 100

mm,

two

crimps

100

mm,

one bare, one spade 100

mm,

onebare, one crimp 100

mm,

two

crimps purchased, Teflon purchased, rubber purchased, plastic purchased,plastic purchased, thermoset purchased purchased purchased

Page

28

Appendix

B:

Formulas

for

_{Manufacturing}

Cost

Model

The

manufacturing cost

model

consists ofthe terms in the following expression:

C

=

C

assembly + (-purchased-parts + ^-molded-parts +

C

sheet-metal-parts + Ctooling

+

^supervision +

Qnventory + Cfacilities

+

Cenergy

In turn, each ofthe terms is

modeled

as follows (all variables are expressed as hyphenated versions of

the labels in tables 3, 4, 5, 6 and 7):

assembly-content x assembly-labor-cost assembly -assembly-productivity x assembly-yield total-purchased-parts purchased-pans

-sourcing-efficiency x purchased-parts-yield /- . Cpias UC

+

Imolding <~molded-pans

"

molded-part-yield

where

Cpiastic

=

plastics-use x polypropylene-cost x (1 - _{plastic-regrind-rate)}

Cmolding

=

molding-processing-time x

(base-machine-rate

+

machine-capacity-rate x molding-machine-requirements

+

operator-labor-cost molding-machines-per-operator and ) r(1

+

r)n base-molding-machine-cost base-machine-rate

-^

. _r ^ n . j x

days-per-yearx hours-per-day xequipment-utilization

r(1

+

r)n molding-machine-capacity-cost

machine-capacity-rate

-(1 . r)n . j

x

days-per-yearx hours-per-day x equipment-utilization

r

_

C

meta]+

C

stamping

<~sheet-metal-parts

-stamped-part-yield

where

CmeiaJ= sheet-metal-use xmild-steel-cost

Qtamping

=

sheet-metal-processing-time x (base-press-rate

+

press-capacity-rate x

, . _. operator-labor-cost \ sheet-metal-press-requirements_{r n}

+

—

r-* r-. ) stamping-machines-per-operator7 and

r(l+r)

n _{base-stamping-machine-cost} base-press-rate

=

x j r £

—

°\ : _rp

—

:

—

(1 - _r)n - 1 days-per-year x hours-per-day x equipment-utilization

r(l+r)

n stamping-machine-capacity-cost size-press-rate

=

x j 1

—

j

—

• t=

—

=

—

(1 - r)n - 1 days-per-year x hours-per-day xequipment-utilization

and

where

r is the cost ofcapital and n is the useful lifeof the machines.

r

(mold-fabrication-time

+

sheet-metal-tooling-fabrication-time) x tool-making-cost

tool-life

division

=

assembly._labor

C

^

t

m

x b 'lpan-of-conrxol X supefyisorylabor-cost

_

inventory-level ,, , ... inventory

=

days-operation-per-year x Cvanable x mventory-holding-cost

where

Cvariable

=

^assembly

+

Cpurchased-parts

+

Cmolded-parts

+

Csheet-metal-parts

+

Csupervision

+

C

energy

„

. . ... base-vearly-hours

Cfaciliues

=

base-facility-size x-j ; ' _r 3

—

[dciuucb ^

days-operation-per-year x hours-per-day

x space-utilization-factor x facility-cost x

production-rate

where

space-utilization-factor =

3

(ass'y-productivity x ass'y-yield + equip't-utilization x mold-yield + base-inventory/inventory-level)

and base-facility-size is

5000

m

2,base-yearly-hours is

4000

hours/year, and base-inventory is

60

days.

The

space utilization factor

assumes

that the required floorspace for agiven annual production is

proportional tothe average ofthe yield-adjusted assembly productivity, the yield-adjusted equipment

utilization, and the inventory levels in the plant.

Qnergy =

total-plastic-mass x plastic-processing-energy xenergy-cost

where

plastic-processing-energy hasa value of 0.75 kw-hr/kg (Busch 87).

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