Can Opener Optimization
By
Robert Bartz
Alex Hsu
Bendy Lin
ME 599
Fall 2003, Section 06
Project #13
December 15th, 2003
Final Report
Abstract
We optimized the design of a simple household can opener. First, we optimized around the
design trade-off for low mass and for maximum mechanical advantage given constraints on the
stress and deflection allowed in the can opener, giving a length of 7.8 inches and a mass of 9.5
oz. Next, we formulated a micro-economic model for our can opener and postulated how the
demand would be affected by changes in the design, guessing a larger sturdier can opener would
be preferred. Using the micro-economic model, we optimized the design for maximum profit,
given the previous technical constraints, which gave 9.8 inches in length, 9.9 oz in weight, and
$6.04 in price. Then, we made a market model by conducting surveys about people’s
preferences and discovered that they prefer a shorter and lighter can opener. These preferences
forced the optimization to a length of 5.9 inches, mass of 8.0 oz, and a price of $5.47. Finally,
we used the same model to produce a product family and solve the production mix problem. We
found that the product mix would give us 74% of the market as compared to 70% for one product
alone and would also increase our profits.
Table of Contents
Nomenclature
............................................................................................................................ 2
1. Introduction .............................................................................................................................. 3
1.1 Product Selection and Design Problem....................................................................... 3
1.2 Description of Design Requirements ......................................................................... 3
1.3 Analytical Product Development Model ................................................................... 4
1.4 Product decisions to be made in the Design Phase .................................................... 4
1.5 List of design requirements (product characteristics) ................................................ 5
2. Engineering Design Model ...................................................................................................... 5
2.1 Design Requirements quantifiable with Engineering Analysis ................................. 5
2.2 Definition of the Design Optimization Problem ........................................................ 6
2.3 Analysis Models Required for Computation ............................................................. 7
2.4 Design Optimization Model ....................................................................................... 9
2.5 Excel Solver Model .................................................................................................... 10
3. Model Extension to Microeconomics ...................................................................................... 12
3.1 Benchmarking & QFD ............................................................................................... 12
3.2 Patent Search Review ................................................................................................. 14
3.3 The Profit Model ........................................................................................................ 14
3.4 The Demand Model ................................................................................................... 15
3.5 The Cost Model .......................................................................................................... 16
3.6 Solved Optimal Design Problem ............................................................................... 17
3.7 Net Present Value ...................................................................................................... 17
4. Model Extension to Marketing ................................................................................................ 19
4.1 Market Size Estimation .............................................................................................. 19
4.2 Functional Relationship ............................................................................................. 19
4.3 Applied Logit Model and Survey .............................................................................. 19
4.4 Market Demand Model .............................................................................................. 21
4.5 Baseline Comparison to Micro-Economic Model ..................................................... 21
4.6 Re-Optimized Design ................................................................................................. 22
5. Product Family Design ............................................................................................................ 23
5.1 Market Segmentation ................................................................................................. 23
5.2 Individual Segment Optimization and Results .......................................................... 23
5.3 Product Family Optimization and Results ................................................................. 24
6. Conclusions .............................................................................................................................. 26
References .................................................................................................................................... 27
Appendix
A. Business Plan ........................................................................................................................... 28
1
Nomenclature:
L
w
G
C
H
Y
t
D
ρ
x
FH
FC
M
KM
E
I
r
q
SF1
SF2
W
f1
f2
P
q
П
λP
λF
λW
λL
θ
S
qm
β
Overall length of can opener (also z2)
Overall width of the can opener
Pivot distance from edge
Distance between pivot and punch
Distance between pivot and location of applied force
Distance from end of handle to location of applied force
Thickness of the handle material
Overall depth including crank
Material density (also Rho)
Crank handle length
Force applied by the hand
Force from can
Overall mass (also z3)
Correction/scaling factor
Young’s Modulus
Moment of Inertia
Thickness of large end of one handle
Thickness of smaller end of one handle
Safety factor for stress in the large section of the handle
Safety factor for stress in the small section of the handle
Objective function weighting factor
Objective function one (equal to FH)
Objective function two (equal to M)
Price of one can opener (also z1)
Quantity from Microeconomic model
Profit
Price elasticity of demand
Force elasticity of demand
Weight elasticity of demand
Length elasticity of demand
Intercept of demand (economic model)
Market size (market model, analogous to intercept of demand)
Quantity from marketing model
Utility for a certain choice (aka part-worths)
2
1. Introduction
In this report, we summarize our work of optimizing a household can opener, considering its
basic design elements. First, we optimized solely using technical objectives, such as weight and
force, to find a technically superior design. Second, we postulated a micro-economic model of
how our can opener and optimized our design by maximizing profit. Third, we conducted a
market survey and used that data to maximize our profit and the design of our can opener.
Lastly, we took a look at how creating a variety of can opener lengths would affect our profit.
1.1 Product Selection and Design Problem:
Our product design team started brain storming for product ideas by coming up with some
everyday mechanical tools. After much debate, we finalized on designing a common kitchen
tool, a can opener. A can opener is one of the most basic kitchen aids that can be seen in a wide
range of places. From restaurants used by professional chefs to dorm rooms used by students, a
can opener is the definition of a consumer-oriented product. Thus, it incorporates the
engineering know-how of us as engineers with other aspects of product development such as
marketing and consumer psychology, which will come into play later in this course. Although
the product has been studied for a long time by appliance makers to achieve professional results,
we feel there is still room for improvement on can opener design. The main design problem
which we are hoping to focus on is to create durable high impact resistant, as well as machinewashable, ergonomic handles for easier gripping and increase the ease to use by reducing the
forces required to turn the crank and squeeze the handles together. The challenge on designing a
different can opener should come from the fact that we are trying to improve a popular consumer
product with a proven track record in the market. Obviously people use the existing design on a
daily basis already; our true test will come when we need to convince then general public that
our can opener design has enough enhancements to differentiate itself from the existing varieties
on the open market to create a competitive advantage.
1.2 Description of Design Requirements:
The design requirements for our can opener are the following. First, since it is a kitchen tool, its
dimensions are limited by the size of the common kitchen drawers. The handle and crank
designs have to be compact enough to fit reasonably into a drawer and still allow it to close
properly. Second, the handle is to be improved by reducing the force needed to cut through the
inner rim of a can while keeping an ergonomic objective in mind to let the user have easy
gripping while operating the can opener. Third, the material used for the handles will have to be
durable and heat resistant enough to be used in dishwashers. Fourth, the gears designed to
translate the torque applied on the crank to the cutting wheel has to be efficient and yet simple so
a young adult or an older person can use the can opener. Finally, the cutting wheel has to remain
sturdy when opening a can. It is often found that the blade has dulled or rusted through regular
usage to the point where it can’t bite onto the rim of a can any more. Our design team will
attempt to improve the current can opener design to satisfy each the above stated objectives,
though in this report we are mainly concerned with a dimensional analysis and we are using a
simplified model. In summary, we used constraints on many dimensional sizes, stress, and
deflection to optimize the mass and length (directly affects mechanical advantage) of our can
opener.
3
1.3 Analytical Product Development Model:
Input: Suggestions to produce a can opener
Output: Concept of producing a can opener
Idea Generation
(anyone)
Requirements
Process
Competitive
Benchmarking
(Finance, Marketing,
Engineering)
(Market research, engineering)
Production Design
Phase
(Product Engineering)
Production Design
Validation
(Product Engineering, Marketing)
Mass Production
(Manufacturing)
Customer Data
Feedback
(Quality)
Input: Directive to produce a better can opener
Output: Cost targets, Consumer requirements,
Knowledge of competitive designs
Input: Initial design for the can opener
Output: A mass production viable can opener design, adding
mass production considerations, materials, and processes, that
is fully complete and has accounted for all requirements.
Input: Complete production design of a can opener
Output: Validation that the can opener meets its end user
and in-house specifications necessary for mass production
Input: Complete production design of a can opener
Output: A whole lot of great looking can openers
Input: Customer buys, uses design, complains if unsatisfied
Output: New design considerations for production and design
Removed initial product development and verification for the can opener, since it is a saturated
market and the basic layout for a can opener is a known quantity.
1.4 Product decisions to be made in the Design Phase:
• Quality
• Materials
• Ease of use
o Torque and speed required to turn crank,
o Force and distance required to squeeze handles together and puncture can
• Aesthetic Appeal
o Colors, surface finish, ergonomic shape
4
•
•
•
•
1.5
•
•
•
•
•
•
•
•
•
•
•
•
•
Design Layout
o Crank design
o Gear reduction
o Dimensions, including lengths of the handles
o Mechanical advantage
o Type and shape of handles
o Torque transfer mechanism
o Can attaching mechanism
Robustness/Reliability of product
Costs targets
Mass production processes and Manufacturability concerns
List of design requirements (product characteristics):
Folded length, width, and height
Temperature at which any part of the can opener melts
Force at blade
Force required by user to operate (hold opener & turn gears/crank)
Number of twists of crank (or alternative) required to open can
Time needed to comprehend how to use
Time needed to open can
Percentage of users that develop injuries
Percentage of users that cannot operate
Time it takes for blade to become unusable (will not cut with appropriate force)
Time it takes for gears to become unusable (will not turn with appropriate force)
Time it takes for can opener to become unattractive
Maximum force on user’s hand
2. Engineering Design Model
We took our customer desires and translated them into terms we could optimize using
engineering analysis. We modeled the basic dimensions of the can opener, along with many
inherent internal size constraints. Also, we used an equilibrium analysis to predict the force at
the user’s hand, which we believe should be minimized. Furthermore, we modeled robustness
by placing large safety factors on the stress and deflection that we would allow in the handle of
the can opener. Lastly, we calculated the weight using a simply modified method based on
density.
2.1 Design Requirements quantifiable with Engineering Analysis:
• Folded length, width, and height
• Force at blade
• Robustness will be modeled using stress and deflection
• Minimal weight
5
2.2 Definition of the Design Optimization Problem:
Objectives:
1. Minimize Force applied by the hand (FH)
2. Minimize the overall mass (M)
Define scalar substitute problem giving applied force minimizing W rating and overall weight
(1-W) rating. A correction factor (KM) will be needed to ensure that the magnitudes of the
objectives are comparable. We will obtain this value during the optimization phase.
F* = (.7) (FH) + (.3) (KM) (M)
Variables:
Lengths
L, overall length of can opener
w, overall width of the can opener
G, pivot distance from edge
C, distance between pivot and punch
H, distance between pivot and location of applied force
Y, distance from end of handle to location of applied force
t, thickness of the handle material
D, overall depth including crank
Rho, material density
x, crank handle length
t, material
thickness
w
C
G
H
L
Y
Force applied by hand
x
6
2.3 Analysis Models Required for Computation
Pick the following parameters:
G = 12 mm (To preserve adequate material and strength near the edge)
Y = 40 mm (Approximation of location of the mean force applied)
Rho = 7800 kg/m3 (Low carbon steel chosen for formability and surface finish)
X = 50 mm (Human hand size physical constraint)
C = 30 mm (Physical interference constraint)
Relationships:
M (mass) = Kv x Rho (Length x thickness x width)
H = L – 52 mm (Using the drawing)
L ≤ 250 mm (Constraining the overall size of the can opener to fit in a small space)
40 mm ≤ w ≤ 70 mm (Constraining the size to fit in a small space and for physical interference)
Equilibrium Analysis:
(FC), Force from can
q
r
C
(FH), Force from hand
20 mm
H
Summing Moments about the pivot:
(FH) H = (FC) C, so
(FH) = (FC) C / H
Stress Analysis:
We modeled the can opener as a simple beam model with two different cross sectional areas. To
find the maximum stress due to bending, we will have to check the points of maximum moment
in both the smaller and larger sections of the handle.
For the large section, the largest moment occurs at the blade: FH x (H – C)
For the smaller section in the handle, the largest moment occurs when it meets the larger section,
thus: FH x (H – 20mm – C)
For the centroidal distances, we have ½ r and ½ q for the large and small sections, respectively.
7
For the second moments of inertia, I1 = 1/12 x (t x r3) and I2 = 1/12 x (t x q3)
This gives us the following equations for stress σ1 and σ 2:
σ1 = FH x (H – C) x 0.5r / (1/12 x (t x r3))
σ2 = FH x (H – 20mm – C) x 0.5q / (1/12 x (t x q3))
Using a safety factor of 10 versus the yield strength would allow for the case of excessive
loading of the handle. Also, r = 0.6W and q = 0.4W would also be linking equations to tie these
sizes back to the overall problem.
Deflection:
We are considering the deflection of the small cross section of the handle, since the large cross
sectional area piece is short and has a much greater second moment of inertia. This also greatly
simplifies the problem. Therefore, we assume that the handle is a cantilever beam built in at the
point where it meets the larger cross section.
As such, the analysis up to the point of the force can be found in a simple static’s reference book.
The deflection = “FH x (H – C – 20mm)3 / (3 x E x I)” and the slope = “FH x (H – C – 20mm)2 /
(2 x E x I)”. Since the end section beyond the force bears no load, its deflection can simply be
approximated by the slope at the end point times the distance from the end point of our previous
simple beam model. This gives an added deflection of “FH x Y x (H – C – 20mm)2 / (2 x E x I)”,
where Y is the distance from the force to the end of the handle.
The force from the can would need to be modeled by contact mechanics or derived from
experimentation and use of this analysis. We are approximating FC as 200 Newtons, an estimate
of the static load required from the blade to puncture the top of the can.
8
2.4 Design Optimization Model
minimize
f = 0.7 × f 1 + 0.3 × K M × f 2
where
C
H
f 2 = M = Kv × ρ × ( L × t × w) + 2 × ( x × A) × ρ + Mgear
f 1 = Fhand = Fcan ×
subject to
H - L + 0.052 = 0
L − 0.25 ≤ 0
w − 0.04 ≥ 0
w − 0.07 ≤ 0
0.5Fhand × ( H − C ) σ y
−
≤0
1 × t × (0.6w) 2
SF1
12
0.5Fhand × ( H − C − 0.02) σ y
−
≤0
1 × t × (0.4w) 2
SF2
12
Fhand × ( H − C − 0.02) 2 ⎡ ( H − C − 0.02) Y ⎤
×⎢
+ ⎥ −δL ≤ 0
3
2⎦
⎣
E × 1 × t × (0.4w) 2
12
M is defined as the total mass of the can opener. The first term is the volume of the space
occupied by the can opener multiplied by the material density, and multiplied by a volume ratio
constant, Kv, which estimates the portion of the space that has material. The second term is the
volume of the crank given by length multiplied by cross sectional area. This number multiplies
the material density to give the mass of the crank. The last term is the mass of the gear and the
cutting wheel, which are taken as givens in our case.
For the two stress equations, SF1 and SF2 are safety factors on the yield stress designed to
account for abusive use and for the possibility of a misaligned stress, which would greatly
decrease the moment of inertia. Both were set to be 10 during the analysis.
9
2.5 Excel Solver Model
To establish the correct weighting, we checked several different weightings and interpolated
between the points to establish the Pareto Frontier. Both the higher and lower endpoints
encountered the reasonability limits we established for the model or the graph would appear to
be more hyperbolic. We chose W=0.7 since it gives us a good trade off between keeping the
weight down and having a lower clamping force. This trade off is between having a longer
handle, which also needs to be thicker due to stress, for lower clamping forces and having a
minimized weight.
Figure 1 Pareto Frontier between Handle
Pareto
Frontier
Force and
Weight
0.32
Weight in Kg
0.3
W=0.8-1.0
0.28
0.75
0.7
0.26
0.24
0.6
0.22
W=0-0.5
0.2
20
30
40
50
60
70
Clamping Force in N
The Pareto Frontier shows the trade-off between clamping force and weight
of the can opener depending on the weighting our objective function.
As such, we used W=0.7 and the following constants as the basis of our model.
Constant
G
Y
C
F_c
K
Rho
Mgear
A
K_m
Value
0.012
0.04
0.03
100
0.6
7850
0.1
0.0001
840
10
Units
meters
meters
meters
Newtons
<none>
kg/m^3
kg
m^2
<none>
KM was obtained by using sensitivity analysis by observing values at upper and lower bounds.
This factor makes f 2 have an equal sensitivity to f as f1 .
Results:
Variable
L
w
t
H
f1 = 40.66
Value
0.200
0.070
1.380
0.147
Units
meters
meters
millimeters
meters
f 2 = 0.268
K M = 840
Optimal (minimized) f = 0.7 × f 1 + 0.3 × K W × f 2 = 96.1
Our optimal can opener design will have:
• Length of 200 mm or 7.8 in
• Width of 70 mm or 2.8 in
• Force on hand of 40.66 N
• Total Mass of 0.27 kg or 9.5 oz
The solution for this optimization had two active constraints. The first active constraint is the
width reached its upper bound “reasonable” size constraint. The best way to minimize weight
and decrease mass is to increase the width, so it was necessary to constrain this dimension to
what is normally acceptable for a can opener. The second active constraint was the stress
condition at the beginning of the smaller section. Given the current geometry, this is the
maximum stress in the can opener and it has a strong influence on the thickness depending on the
length. The trade-offs also depend on the weighting factor, discussed previously in relation to
the Pareto frontier. This solution is meaningful since it has minimal constraints by trivial
bounds.
11
3. Model Extension to Microeconomics
We further extended our technical model of a can opener to include the aspects related to
demand. We critically examined many can opener attributes and related those which we could
quantify back to our technical model. We modeled how the design characteristics of length,
mass, and effort force would affect demand. Also, we did a financial analysis to investigate
profit from our revenues and costs.
3.1 Benchmarking & QFD:
In order to perform product benchmarking, we purchased several models of can openers,
encompassing the wide range available. By observing and comparing these with one another, we
were able to figure out where our product might sit in the can opener market. Can openers used
to benchmark were:
•
•
•
•
•
•
•
•
Faberware
Generic (white)
Good Cook (metal)
Good Cook (black)
Good Cook Safe Cut
Hamilton Beach Deluxe
OXO Good Grips
OXO Good Grips Smooth Edge
These can openers were benchmarked with the assistance of a QFD Analysis. This can often be
difficult and time consuming. We have only used the most critical Design Requirements in order
to simplify and focus our product design efforts.
12
QFD Analysis
²
²
²
Technical Benchmarking
Importance (1-5)
1
Easy to attach opener to can
2
Easy to start (cut/puncture)
3
Easy to turn
3
Easy to learn
2
Looks
4
Longevity
2
Safety
2
Comfortable
3
Technical Difficulty
Percentage of Total
Our Product
Faberware
Generic (white)
Good Cook (metal)
Good Cook (black)
Good Cook Safe Cut
Hamilton Beach Deluxe
OXO Good Grips
OXO Good Grips Smooth Edge
Design Targets
2
↓
↓
Number of twists of crank
required to open can
Customer
Requirements
↓
Force required by user to
turn crank
Design
Requirements
↓
Force required by user to
puncture can
↓
○ Target
Weight
↓ Min
Size
(Length,Width,Thickness)
↑ Max
3
4
5
∆
∆
∆
∆
∆
∆
∆
∆
∆
35
23%
5
3
2
1
3
4
5
4
5
4
9
6%
4
3
2
1
3
2
4
4
3
4
32
21%
4
2
2
1
3
5
4
4
5
4
38
25%
3
3
2
1
3
3
3
3
5
4
36
24%
3
3
2
2
3
3
3
3
2
4
From this analysis, we can see that our product is positioned well when compared with other can
openers in the marketplace today. However, issues regarding the crank – force required to turn
and number of turns required – may need to be revisited and may warrant a change in design to
improve performance of these important attributes.
13
3.2 Patent Search Review:
After preliminary patent search and market statistics analysis, we feel our can opener design is
strongly positioned in the current house kitchenware market. In general, can opener designs can
be grouped into the following four market categories: manual handheld, electric handheld,
manual stationary and electric stationary. In order to simplify our analysis, we assume these four
categories are none-competing when it comes to consumer preferences. That is, the main criteria
to purchase for a given consumer is functionality as oppose to novelty, and the person who is
intending to buy a can opener makes up his or her mind which one of the four basic types to buy
before he or she starts the browsing process.
Based on the existing design, our product falls into the most popular section of manual handheld
can openers. We performed a patent search from the US Patents and Trade Office database on
this particular type of can openers in order to review the available designs out there on the
market. The patent search review serves as a very broadly based benchmarking for our can
opener design since all these patented designs out on the open market are potentially our
competitors.
After much examination, we have noticed that most of the patents granted on manual handheld
can openers have to deal with ornamental designs only. Regardless of their exterior appearances,
these can openers still have the same functionality based on a traditional crank and gear
mechanism. Since the objective of our can opener design has to involve mathematical
optimization, we concluded that because decorative design is not quantifiable in our rudimentary
mathematical formulation, the best way to treat these different can openers is by bundle them
together and only compare their dimensions and/or material used to our preliminary design
dimensions and material. After this procedure, we still feel our product stands a good chance in
the current market of can openers.
It should be pointed out that in the category of manual handheld can openers, there exists a new
design on the cutting mechanism which uses the traditional crank-gear-cutting wheel system.
However, it is setup in such a way to allow the user to cut from the side of a lid rather than from
the top. Our design team decided to go out and purchase one of these side-cutting can openers to
see how well it works. The product, as expected, was not cheap due to its new design and brand
name, about 25 dollars. We tested it on a soup can, and the cutting was smooth and effortless, so
much to the point it was hard to tell if the lid was off after one turn around. The new design
definitely has its advantages and disadvantages, namely its ease to use and its price respectively.
However, we believe that due to the various reasons mentioned above, the idea of novelty plays a
major role in affecting a consumer’s decision making process to purchase one of these new-type
of can openers. Thus, it was decided to not include the newly designed side-cutting can openers
in our benchmarking, mainly because they are not wide-spread enough for people to make their
purchase decisions based solely on functionality.
3.3 The Profit Model:
Generally speaking, profit is defined as revenue minus cost. In our current model, we are going
to simplify the analysis by limiting the factors which can influence profit; such quantities include
the demand intercept, number of units produced, product characteristics, price elasticity, product
characteristic elasticities, fixed cost, operational cost, material cost and chroming cost. Material
14
cost is a function of the total mass of steel used to make the can opener and the chroming cost is
a function of the surface area to be chromed.
This leaves us with the following profit model:
Profit = ∏ =
θ
1
1
q − q 2 + q (λWM + λLL + λFFHand ) − [Co + q(COp + CMat + CChr )]
λP
λP
λP
= 20q − 0.0002q 2 + q(−0.05M − 0.2 L − 0.1FHand ) − [407500 + q(1.58 + CMat ( Mass) + CChr ( Area))]
The new objective function of the optimization problem is now to maximize the above profit
equation.
3.4 The Demand Model:
The Demand Curve: Quantity is equal to the intercept of demand, θ, minus price elasticity, λp,
times price, P. The equation is then solved for price.
q = θ − λ PP ⇒ P =
θ
1
− q
λP λP
The Demand Curve with Change in Product Characteristics
θ
1
1
− q + ∑ λα∆α
λP λ P
λP
1
1
θ
P=
− q + (λWM + λLL + λFFHand )
λP λ P
λP
P=
Revenue with Change in Product Characteristics
Re venue = P × q
Re venue =
θ
1
1
q − q 2 + q(λWM + λLL + λFFHand )
λP
λP
λP
Elasticity
Price Elasticity – λP is calculated as
∆q
. From empirical data, the numerical value used for price
∆P
elasticity is 50000.
∆q
. From estimation, the numerical value used for
∆W
weight elasticity is -25000.
∆q
. From estimation, the numerical value used for length
Length Elasticity – λL is calculated as
∆L
elasticity is -10000.
Weight Elasticity – λW is calculated as
15
∆q
. From estimation, the numerical value used for force
∆F
elasticity is -5000.
Force Elasticity – λF is calculated as
Quantity Intercept
Theta, θ, is the theoretical demand if the price is zero. From estimation, the numerical value
used as the intercept is 1000000, or the entire potential consumer base.
The Final Revenue Equation
Re venue = 20q − 0.0002q 2 + q(− 0.05M − 0.2 L − 0.1FHand )
3.5 The Cost Model:
Cost in general can be broken down into two parts, fixed cost and variable cost. Most of the
time, fixed cost is incurred regardless of production, as oppose to variable cost which is a
function of quantity produced. To estimate what the manufacturing costs would be, we first
broke down the can opener into the basic process steps necessary to make all of the basic parts.
From there, we estimated the approximate equipment costs and operating costs for each step,
along with finding good sources for the costs most directly related to the design variables.
Cost = CFixed + CVariable = Co + qCVar
Fixed Cost
The fixed cost, Co, is mainly determined from the cost to set up production. In the case of a new
can opener design, that includes the cost of buying or renting land and office space, the cost of
constructing a manufacturing plant and assembly line, the cost of renting or buying equipment,
the cost of performing market research and lastly, the cost of producing the prototype. From
estimation and bench mark analysis, the value of our fixed cost is going to be $407,500, which is
dominated by the cost and space necessary for production.
Variable Cost
The variable cost can be further categorized into separate production requirements. For our can
opener, we simplified them into three parts, operating cost per unit, material cost per unit and
chroming cost per unit. The operating cost per unit mainly refers to the cost of labor used in the
production of one can opener from scratch to finish. The material cost is the cost of steel to
make one unit of the new design, which we found to be $400 a ton ($0.20 per lb) for sheet steel
(market price).[1] The chroming cost refers to the cost of the chrome used to coat one can
opener, which is based on area at $0.0127 per square meter.[2] As expected, we found that
producing a can opener is a labor intensive process and thusly the operating cost per can opener
dominates the variable cost at $1.58 depending on your manufacturing efficiency.
CVar = COp + CMat ( Mass ) + CChr ( Area )
16
The Final Cost Equation
C = Co + CVarq = Co + q (COp + CMat + CChr )
C = 407500 + q (1.58 + 0.20 × Mass(lbs) + 0.0127 × Area(m 2 ))
3.6 Solved Optimal Design Problem:
Using the demand and cost Models we developed, we are now able to apply this to our profit
model introduced previously, and optimize the profit objective with respect to quantity and
design parameters. We used the Solver function in Microsoft Excel to optimize and solve our
objective. The Excel Worksheet is included at the end of this report.
Results
(Values for Technical Optimization from Assignment 2a shown in parentheses)
• Length of 250 mm (200 mm)
• Width of 44 mm (44 mm)
• Thickness 1.56 mm (1.38mm)
• Force on hand of 30.3 Newtons (40.7 Newtons)
• Total Mass of 0.31 kg (0.27 kg)
• Price $6.04
From the results obtained, we see that the solver hit the upper bound we had set for length. In
general, the Profit Optimization has resulted in a longer and heavier can opener when compared
to our can opener resulting from our Technical Optimization from Assignment 2a.
3.7 Net Present Value:
By solving this can opener project problem using a net present value (NPV) calculation, we are
able to consider what will happen over multiple time periods and over the projected life a can
opener’s product life. Also, NPV calculation is an essential way to communicate the value of a
product to management and those who make the financial decision to invest money in making a
product.
Examining the financial situation for several years into the future is accompanied with a great
deal of uncertainty. We foresee no new technological developments in the future that would have
a significant impact on the canned foods or can opener industry. In five years we expect a newly
designed can opener to be developed and introduce. The current can opener design will be
discontinued at this time. By looking to market data and research, we can resolve some financial
values needed in our calculation. An inflation rate of 3% and a real discount rate of 4% are
assumed.
Uncertainty arises as a result of the dynamic nature of market conditions. Inflation, discount rate,
demand, price, and other values will be revised as time progresses and we learn new information.
However, a relatively short product life of five years means that the magnitude of uncertainty
resulting from our forecasts should be small.
The net present value was calculated as follows:
17
Year
0
Demand (units)
Price
Revenue (Cash Flow)
Costs
1
55000
$
6
$330,000
2
55000
$
6
$330,000
3
55000
$
6
$330,000
4
55000
$
6
$330,000
5
55000
$
6
$330,000
$ (86,900)
$ (89,507)
$ (92,192)
$ (94,958)
$120,000
$ (97,807)
Fixed Costs
Variable Costs
$(407,500)
Net Cash Flow
Discount rate
$(407,500)
$243,100
7%
$240,493
7%
$237,808
7%
$235,042
7%
$352,193
7%
Discounted Cash Flow
$(407,500)
$227,196
$210,056
$194,122
$179,312
$251,109
Note: All values above shown in nominal terms
By summing the discounted cash flows from each year, we obtain:
Net Present Value: $ 654,296
The NPV for making this product is positive, which indicates that we should do it because it will
add value to our company. However, many factors and uncertainties can affect this NPV value.
These include general economic conditions, competitors, stock prices and many others.
18
4. Model Extension to Marketing
To further investigate customer preferences for purchasing can openers, we conducted a survey
of likely future customers. The aim of our survey was to develop more detailed functions for
customer trade-offs than our previously postulated elasticities, which currently predict that more
or less of one product characteristic is better.
4.1 Market Size Estimation:
We chose our market size, S, to be 500,000 for this assignment. In our micro-economic model
we chose 1,000,000, but we felt that this was too large given the differences in the models. Our
marketing model assumes a single product monopoly, which is very different from our microeconomic model. The micro model just assumed that one million customers would take can
openers if they cost zero dollars.
4.2 Functional Relationship:
We chose price (z1), length (z2), and mass (z3) as the characteristics we wished to study and how
they related to demand for a can opener. In our initial informal surveys, there seemed to be a
preference for a bigger and more massive can opener. Most people implied that it had a sturdier
feel. We are also curious about the affect of handle length, which directly changes the lever arm
and the ease of use of the can opener, so we also included this characteristic in our survey, in
addition to mass. So our micro-economic model assumed that a longer, more massive can
opener was preferable and that people would obviously prefer it to be less expensive with all
other things being equal.
4.3 Applied Logit Model and Survey:
We used SAS to generate a fractional factorial survey to test how people would react to different
combinations of product characteristics. Using this method, we aimed to isolate people’s desire
for each of the characteristics independently. We had picked values of 5, 7, 9, and 11 inches
long and 5, 9, 12, and 16 ounces in weight for our survey. We used a wide spread to try to
accurately map the curves. Since we had some difficulties generating the surveys, we had more
questions than were necessary. So we cut the number of price levels to $4 and $6 to reduce the
number of questions on the survey, since price should be relatively linear near these values.
We administered a survey consisting of 32 questions, each question having a no choice option
and three can opener choices, with a different combination of price, length, and mass. We used a
maximum likely-hood formulation to find the betas (utilities) associated with each product
characteristic level. We found the following from our data, which can be compared to a beta of
zero for our no choice option, since the beta’s really only hold relative values to the one trade off
being compared. Using data from the first 32 respondents, we discovered the following:
19
Figure 2: Utility vs. Price
0.0
-2.0
Beta1
-4.0
-6.0
-8.0
-10.0
-12.0
0
2
4
6
8
Price in $
As expected, people preferred a lower price, which
is shown by $4 having a higher β1 value.
Figure 3: Utility vs. Length
4.0
Beta 2
3.6
3.2
2.8
2.4
2.0
2
4
6
8
10
12
Overall Length in Inches
People preferred a medium length can opener, though there utilities do not change
much near 7 inches as shown by the near constant β2 around 7 inches. There is a
significant drop towards 11 inches, which is probably too large for a can opener.
We found that people had a strong dislike for a can opener that was too large, e.g. 11 inches
long, as expected. This result is seen clearly in Figure 2. However, we did not find the same
behavior for a can opener that we believed that was too small, e.g. 5 inches, as we had expected.
We believe that this maybe due to a flaw in the survey, though the questions ask people about
their logical preferences, it did not take into account the experience a person might have by
seeing and feeling different size can openers. We think that if a person used or held a 5 inch
long can opener, they would think it would be too small and not sturdy enough. However, we
will proceed to use this survey result throughout the rest of our analysis.
20
Figure 4: Utility vs. Mass
6.4
Beta3
6.2
6.0
5.8
5.6
5.4
0
5
10
15
20
Can Opener Mass in Oz
People showed a strong preference for a lighter can opener, as shown by higher
utilities (β3) for lighter masses. This is contrary to the expectation that people
would consider a heavier can opener to be sturdier and more desirable.
We found people strongly preferred a lighter can opener, which did not meet expectations. We
expected people to realize that if a can opener was too light, that it would not be very sturdy.
However, we did find that people did not like can openers that were too heavy, e.g. a one pound
can opener. With the same reservation as our length data, we will proceed to use this data
despite these findings.
4.4 Market Demand Model:
We used a single product monopoly for our market model. In this model, the consumer can
simply choose between our product and buying nothing. Our model calculates quantity by
multiplying the market size by the probability that the consumer would pick our product instead
of nothing. This probability is a function of the product characteristics.
Quantity (qm) = Market Size (S) x Probability of Choice (Pr(j))
The probability is calculated by summing the betas, one from each product characteristic, and
using the logit model. This model takes the sum of the betas and uses the exponential of that,
divided by the exponential added to one, since one represents e0 which is the betas for our nochoice option. Hence, in the simplest form, we have US/(US + THEM).
Logit Model: Pr(j) =
exp[ β Pr ice ( z1 ) + β Length ( z 2 ) + β Mass ( z 3 )]
1 + exp[ β Pr ice ( z1 ) + β Length ( z 2 ) + β Mass ( z 3 )]
4.5 Baseline Comparison to Micro-Economic Model:
We used our optimization model and a central difference scheme to estimate the elasticities of
price, length, and mass. We changed price (in dollars), mass (in ounces), and length (in inches)
21
by ±0.2 from their equilibrium values and used a central difference approximation for the slopes
(hence elasticities) near the previous equilibrium point form assignment #3. We found that the
price elasticity had the same sign so lower prices were still preferred, but our newer model was
much more sensitive to changes in price with an elasticity of 700,000 as compared to 50,000 in
units of quantity over dollars (14 to 1 change). For length and for mass, we found that the price
elasticities had the opposite sign, meaning that our micro-economic model predicts larger can
openers will be more profitable and our market model predicts smaller ones will produce more
profit. The elasticity of length was -10,000 in our previous model and changed to 1,820,000 in
our market model in units of quantity per meter (-182 to 1 change). Furthermore, the elasticity
of mass changed from -25,000 to 108,000 in units of quantity per kilogram (-4 to 1 change). A
large part of the differences have to do with the scales of our postulated micro-economic model
and our market model, though length appears to have a much larger affect than we originally
estimated.
4.6 Re-Optimized Design:
Using our new market model, we re-optimized the design, with maximum profit as our objective,
using the excel solver schemes we had used previously, except we made a few simple changes.
Quantity is predicted as stated above and revenue is now simply the price times the quantity.
Solving, we found the following for our can opener.
Price: $5.47
Length: 5.9 inches
Mass: 8 ounces
The length hit its lower bound, which we put into the engineering model to prevent the can
opener from being too small. It was driven to this bound by a strong response on the survey to
smaller can openers, though we have the previously stated reservation about trusting the survey
data. We expected trade-offs would cause people in a more realistic scenario to pick a medium
size and a medium length. So both the mass and length are much smaller than in previous
iterations of our optimization.
The width hit its upper bound (7cm) from the engineering model, this was because the width is
the most important factor in satisfying the stress constraints and it quickly goes towards the
upper bound. This has been typical of our results so far.
The thickness was optimized at just over one millimeter (1.02mm), which is quite a bit smaller
than in previous designs (1.56 mm), which usually had longer handle lengths in order to
minimize the user’s force applied at the handle. From our previous results, a longer handle
length required the handle to be thicker to meet our stress requirements.
Profit Picture
Our financial picture is as follows, using the same cost structure we had in our previous work.
This picture seems a little optimistic, which is attributed to our cost model being scaled relative
to our micro-economic model, instead of the single product monopoly in our market model.
22
Quantity:
Revenue:
350,000
$1.9 mil
Fixed Costs:
Operating Costs:
Material Costs:
TOTAL COSTS:
$408K
$553K
$35K
$996K
First Year Profit:
$918K
5. Product Family Design
In studying a product family design mix, we aim to design the best three possible can openers
with given lengths and optimize the other parameters, such as quantity, mass, and price to give
the most profit possible. The following section outlines are results, which show that a product
mix is more profit than a single product monopoly and is also more profitable than the individual
optimized can openers competing in the same market.
5.1 Market Segmentation:
There are three market segments which we try to target with our initial can opener design. The
resulting three models, “basic”, “deluxe” and “premium”, have lever arm length 6 in., 7.5 in. and
9 in. respectively. In this case, length of the can opener is the variant in our optimal design. We
are also establishing the overall market size to be 500,000. The thinking behind categorizing our
original can opener design into three products is to target different segments of the overall
market based on different consumer needs. According to our market survey from assignment #4,
it is evident that the overall length and the resulting weight of the can opener design play a major
role in consumers’ choice making when considering which can opener to purchase. Therefore,
length is the variable taken as three discrete values in the optimization problem follows. The
basic design is cheap, light and it does the job. College students and bachelors are the groups we
target with this model. The deluxe design is a little easier to use and is also more durable.
Housewives are the target group for this particular model. Finally, the premium design is the
easiest to use and is ergonomically detailed with a slick exterior. This model should appeal to
the gadget collectors out there.
5.2 Individual Segment Optimization and Results:
When the three designs are looked at separately, the optimization problem is the same as the
technical problem we have analyzed earlier in assignment #3 and #4 with the same constraints
and parameter considerations. The objective for each of the three can opener design length is to
maximize the profit in the given market size of 500,000. The resulting optimization is
summarized on a table on the next page.
It is apparent the minimal design with the 6 in. handle gained the highest market share at 70.0%,
and then the deluxe model at 68.2% and the premium model came in last at 64.1%. These
market share numbers translate roughly into 349921, 340751 and 320525 units produced for the
6 in., 7.5 in. and 9 in. design respectively. After multiplying the number of units produced by the
variable cost for each can opener and add the fixed cost of labor and plant, the basic design
23
actually came out with the lowest total cost at $996,006, while the premium design has the
highest total cost at $1,083,266, even given the fact that it has the lowest demand compare to the
other two.
Market Share
Quantity
Basic
70.0%
349921
Deluxe
68.2%
340751
Revenue
$ 1,913,563.98
Premium
64.1%
320525
$
1,861,934.75
$ 1,690,713.77
Fixed Costs
$
Oper. Costs Per Part $
Operating Costs
$
407,500.00
1.58
552,875.46
$
$
$
407,500.00
1.78
606,536.85
$
$
$
407,500.00
1.98
634,640.31
Mat'l Costs Per Part $
Material Costs
$
0.102
35,534.31
$
$
0.115
39,249.05
$
$
0.128
40,992.54
Chroming Costs/m^2 $
Surface Area (m^2)
Chroming Costs/part $
Chroming Costs
$
0.0127
0.02180
0.000277
96.89
$
$
$
$
0.0127
0.02736
0.000348
118.42
0.0127
0.03290
0.000418
133.92
$
$
Total Costs
$
996,006.65
$
1,053,404.32
$ 1,083,266.77
Profit
$
917,557.34
$
808,530.44
$
607,447.00
Price
$
5.47
$
5.46
$
5.27
Now we look at the profit side of things. Surprisingly the optimization model tells us that in
order to generate the desired demand to maximize our revenue, the basic model can be sold at the
highest price of $5.47 each, and the premium model can only be sold at $5.27 each. The Deluxe
model has a asking price of $5.46, in between of the other two prices. Common sense would tell
us that the basic model would generate the highest profit for our operation given its high revenue
and low cost. The numbers also show the same trend. The premium design yielded a final profit
of $607,447, the deluxe design yielded a profit of $808,530, and the basic design yielded the
highest margin at $917,557. Thus we can conclude that in a given market size of 500,000, using
profit maximization for the company as the objective, we should pour all our available resources
into producing the basic design, the 6 in. can opener.
24
5.3 Product Family Optimization:
In the family of products problem, we realize there is more potential in the market than before
when we try to push one type of product onto the entire market. The idea is to setup another
optimization problem, again using profit maximization as our objective in the same 500,000
market size. However, this time we will allow the production of all three can opener models
simultaneously in order to achieve the highest market share possible. The results of our product
family optimization are contained in the following table.
Market Share
Quantity
Basic
34.4%
172080
Revenue
$ 1,049,682.90
Fixed
$
Oper. Costs Per Part $
Operating Costs
$
Mat'l Costs Per Part $
Material Costs
$
Chroming Costs/m^2 $
Surface Area (m^2)
hroming Costs Per Pa $
CHroming Costs
$
Deluxe
25.4%
127093
Premium
14.4%
72198
Total
74.3%
371370
$
806,083.20
$
475,811.28 $ 2,331,577.39
$
$
$
$
$
$
$
$
$
$
$
$
$
$
79,221.51
1.98
142,951.08
0.192
13,850.20
0.0127
0.0329
0.000418
30.16
188,821.06
1.58
271,885.89
0.102
17,474.60
0.0127
0.0218
0.000277
47.65
$
$
139,457.43
1.78
226,225.10
0.144
18,298.81
0.0127
0.0274
0.000348
44.17
Total Costs
$
478,229.20
$
384,025.51
$
236,052.95 $ 1,098,307.66
Profit
$
571,453.71
$
422,057.69
$
239,758.33 $ 1,233,269.74
Price
$
6.10
$
6.34
$
6.59
Previously we had decided that the 6 in. design was optimal when producing only one type of
can opener, so we will make our comparison of the family of products optimization results only
with the 6 in. design optimization results calculated earlier. When all three models of can
openers are produced targeting different market segments, the overall market share for the
product family is 74.3%, up from the 70.0% mark when only the basic model is produced. This
higher market share breaks down to 34.4% of the market demands the basic model, 25.4%
demands the deluxe model and 14.4% demands the premium model. This translates into a gain
of 21,449 units in the demand of the can openers for the company. After calculating the total
cost of each design, which is $1,098,307, we notice it is higher than the total cost of satisfying
the demand of just producing the basic model because now the overall demand is bigger.
The family of products optimization also gave us a more sought after pricing trend, the basic
model is now at $6.10 each, the deluxe model at $6.34 and the premium model costs $6.59 each.
This satisfies our original goal of targeting the students for the basic model, the housewives for
the deluxe model and the gadget lovers for the premium model. Multiply the price by units sold
for each design, we get the revenues for each design. Not surprisingly, the basic model is still
the best seller generating $1,049,682, followed by the deluxe model at $806,083, and the
25
premium is last at $475,811. The total revenue created by these three can openers combined is
$2,331,577, and the total profit of the company is $1,233,269. Compare this figure to the profit
calculated previously, $917,557, when producing the basic model alone, we can deduce the
conclusion that in our potential can opener market, it is more profitable for the company to create
a product family in order to maximize the market share than producing just one type of can
opener alone.
We also considered how the market would function if we optimized each design separately and
then placed them in the same market, as compared to our product family optimization, which
optimizes profit with all three products in the same market. Under this scenario, the prices
would be reduced (about $1 per can opener) and the market share would be increased (up to 86%
compared to 74%) when considering the individualized optimized can openers now placed in a
competitive market and comparing them to the product family optimization. However, by
optimizing them for profit in a competitive market, as our product family was done, we found
that slightly higher prices and a lower market share could create more profit by approximately
10% ($1.23 mil compared to $1.12 mil).
6. Conclusions
We optimized the design of a simple household can opener. First, we optimized the design
trade-off of low mass vs. maximum mechanical advantage given constraints on stress and
deflection, giving a 7.8 inch long can opener, weighing 9.5 oz. Next, we postulated a microeconomic model estimated how the demand would be affected by changes in the design,
hypothesizing that people prefer a larger sturdier can opener. Using the micro-economic model,
we optimized the design for maximum profit, given the technical constraints, which gave a
length of 9.8 inches, a mass of 9.9 oz, and a price of $6.04. Then, we made a market model by
conducting surveys about people’s preferences and discovered that they prefer a shorter and
lighter can opener. These preferences forced the optimization to a length of 5.9 inches, mass of
8.0 oz, and a price of $5.47. Finally, we used the same model to produce a product family and
solve the production mix problem. We found that the product mix would give us 74% of the
market as compared to 70% for one product alone and would also increase our profits. This
demonstrates the economic principle of segregating the demand curve for higher profits.
One of the key limitations to this model is that we based demand entirely on price, mass, and
length. However, for a common low cost consumer product of this nature, we believe that visual
and aesthetic appeal would be one of the main drivers for consumers. This visual nature of the
product, along with the other factors, gives people the perception of quality and value that they
use to make their purchasing decisions. We believe this is a strongly limiting aspect of our
model. A study of how people perceive quality, for this and other products would be a good next
step in this process. Many design experts believe that a product that is perceived to have a
higher quality/value will be treated better by the end consumer. Therefore, products with a
higher perceived quality will have a longer and more useful life and will likely be sold more
often.
26
References
[1] http://www.trilla.com/AMM%20Aug%2016.htm, Trilla Steel Drum Corp, Nov 1 2003
[2] http://www.hard-chromesystems.com/Price_sh.htm#top, Hard Chrome Plating Consultants,
Inc , Nov 1 2003
27
Appendix A: Business Plan
In conjunction with our technical efforts, we organized most of our work into a business plan.
This outlines how we could successfully run a business with our analytically designed product.
It is separated into three parts, with the first two taking priority. First, we describe the business
opportunity available to us in building can openers. Second, we show a thorough financial
analysis that supports our profitability. Lastly, we have supporting documentation, which
essentially is the technical material contained in this report.
I
Business Opportunity
1.) Business Objective
Can-You Squeeze, Inc. is a kitchen ware development company that intends to design, patent,
and market kitchen devices related to the average house ware market. Three devices have already
been designed. One patent is initially incorporated. The company projects $2.3 million in sales
in year three with a net profit of approximately $1.8 million. The company expects to hold $2.3
million in revenue by year five. Patent application on its first market entry has already been
accomplished using a top patent law firm.
The market segment is clearly defined and is subject to a moderate growth trend. The market is
projected to exceed $200 million in the next two years. One of the founders of Can-You Squeeze
participated in the design of the current market leader in that field and has improved upon the
product significantly.
The mission of Can-You Squeeze, Inc. is to design, develop, and market new patented
technologies in the kitchenware field. The technologies will fill market niches that each account
for a minimum of $20 million in potential sales. Each technology will fill a current need in
kitchen tool design by improving upon an existing technology or device, or by designing a
device to serve a specific need. Each product shall be priced to appeal to the consumers such that
it stresses the lowest cost with the highest quality. The keys to success for Can-You Squeeze,
Inc. are as follows:
Initial capitalization obtained.
All patent applications filed.
The ability to generate early revenue from markets in Europe.
Licensing at least one technology and application to a major kitchenware device
corporation.
5. Getting low interest loans and/or grants to fully fund product development and prototype
manufacture.
6. Recruiting top-notch CEO prior to second round financing and market roll-out.
1.
2.
3.
4.
2.) Product Description
Can-You Squeeze, Inc. will manufacture kitchen equipment and tools for all areas of household
and commercial needs. Primary focus will be placed on product engineering and manufacturing
28
processes to ensure the highest quality, a high level of product features, and the most efficient
manufacturing process possible.
Can-You Squeeze, Inc. will first push three can openers called the "Easy-Lid Basic," "Easy-Lid
Deluxe," and "Easy-Lid Premium", onto the general consumer market. All Easy-Lid products
will be capable of increasing the ease of opening a can, and are specially designed to maximize
the features which consumers are looking for in each category.
The Easy-Lid Basic will perform the can opening operation with ease and yet priced very
competitively with the other existing products on the market.
The Easy-Lid Deluxe will have a longer lever arm for the user to effortlessly puncture the can.
The Easy-Lid Premium will feature the longer lever arm to maximize the leverage when the user
pushes down on the handle. However, the design is also optimal for light weight and space
saving purposes.
3.) Market Analysis
After preliminary patent search and market statistics analysis, we feel our can opener design is
strongly positioned in the current house kitchenware market. In general, can opener designs can
be grouped into the following four market categories: manual handheld, electric handheld,
manual stationary and electric stationary. In order to simplify our analysis, we assume these four
categories are none-competing when it comes to consumer preferences. That is, the main criteria
to purchase for a given consumer is functionality as oppose to novelty, and the person who is
intending to buy a can opener makes up his or her mind which one of the four basic types to buy
before he or she starts the browsing process.
Based on the existing design, our product falls into the most popular section of manual handheld
can openers. We performed a patent search from the US Patents and Trade Office database on
this particular type of can openers in order to review the available designs out there on the
market. The patent search review serves as a very broadly based benchmarking for our can
opener design since all these patented designs out on the open market are potentially our
competitors.
After much examination, we have noticed that most of the patents granted on manual handheld
can openers have to deal with ornamental designs only. Regardless of their exterior appearances,
these can openers still have the same functionality based on a traditional crank and gear
mechanism. Since the objective of our can opener design has to involve mathematical
optimization, we concluded that because decorative design is not quantifiable in our rudimentary
mathematical formulation, the best way to treat these different can openers is by bundle them
together and only compare their dimensions and/or material used to our preliminary design
dimensions and material. After this procedure, we still feel our product stands a good chance in
the current market of can openers.
29
It should be pointed out that in the category of manual handheld can openers, there exists a new
design on the cutting mechanism which uses the traditional crank-gear-cutting wheel system.
However, it is setup in such a way to allow the user to cut from the side of a lid rather than from
the top. Our design team decided to go out and purchase one of these side-cutting can openers to
see how well it works. The product, as expected, was not cheap due to its new design and brand
name, about 25 dollars. We tested it on a soup can, and the cutting was smooth and effortless, so
much to the point it was hard to tell if the lid was off after one turn around. The new design
definitely has its advantages and disadvantages, namely its ease to use and its price respectively.
However, we believe that due to the various reasons mentioned above, the idea of novelty plays a
major role in affecting a consumer’s decision making process to purchase one of these new-type
of can openers. Thus, it was decided to not include the newly designed side-cutting can openers
in our benchmarking, mainly because they are not wide-spread enough for people to make their
purchase decisions based solely on functionality.
4.) Capital and Personnel Resources
The three co-founders of Can-You Squeeze, Inc., Alex Hsu, Robert Bartz and Bendy Lin will all
assume the position of President of the new company. Mr. Bartz will also be given the title of
CTO, in charge of product development and design issues. Mr. Hsu will have the title of
company COO and be responsible for daily operations and product marketing. Mr. Lin will
assume the role of company CFO and oversees the financial strategy of the new company. CanYou Squeeze, Inc. has also recently obtained a startup loan from Citi Group, Inc. to purchase a
production and assembly line plant in southwestern Michigan. The factory currently has 30
employees divided into teams of raw material, production, assembly, packaging and shipping.
Can-You Squeeze, Inc. has also hired a top human resource firm from New York City for its
CEO search.
II Financial Data
1.) Capital Supply List
Eventually, Can-You Squeeze intends to license its new technology to a larger company. The
company becomes mature in year three with gross margins of 55% producing $1.8 million in net
earnings. The company is potentially profitable in year one. The principal objectives of Can-You
Squeeze, Inc. are as follows:
1. To achieve a 10% market penetration in the household kitchen opener market by the year
2007.
2. To achieve $1.8 million in revenue by the year 2007.
3. To raise $1 million in private seed capital in the first half of 2004.
4. To win low interest loans and grants from the government of totaling $0.5 million in
2004.
30
2.) Break Even Analysis
BREAKEVEN
discount rate
7%
Basic
Deluxe
Premium
Total
$
$
$
$
Revenue
1,049,682.90
806,083.20
475,811.28
2,331,577.38
First Costs on Annual Basis
$ (1,736,119.69)
Operating Costs
$ (1,098,307.66)
Annual Income from Rent
$
2,331,577.38
Annual Return from Salvage
$
502,849.97
breakeven point
$
$
$
$
Costs
(478,229.20)
(384,025.51)
(236,052.95)
(1,098,307.66)
0.24 Years
2.94 Months
89.37 Days
According to our break even analysis, the company should start making profits within the first
year of operation. To be exact, by the 90th day of starting up, the business already had taken in
enough income to offset the initial investment. This is mainly the result of a very low
requirement in startup capital.
31
3.) Income and Cost Projections on a Pro-Forma Basis
Net Present Value
Year
Demand (units)
Price
Revenue (Cash Flow)
Costs
Fixed Costs
Salvage Value
Variable Costs (per part)
Variable Costs
Net Cash Flow
Discount rate
Discounted Cash Flow
0
Quantity, Basic
Price, Basic
Quantity, Deluxe
Price, Deluxe
Quantity, Premium
Price, Premium
1
$
$
$
$
$
(407,500)
$
$
$
$
$
$
$
(407,500) $
$
(407,500) $
Net Present Value $
2
172080
6.10
127093
6.34
72198
6.59
2,331,577
(1.58)
(271,885.89)
(1.78)
(226,225.10)
(1.98)
(142,951.08)
1,889,806
7%
1,766,173
$
$
$
$
$
$
$
$
$
$
$
$
172080
6.10
127093
6.34
72198
6.59
2,331,577
(1.64)
(282,761.33)
(1.85)
(235,274.11)
(2.06)
(148,669.12)
1,864,163
7%
1,628,232
$
$
$
$
3
172080
6.10
127093
6.34
72198
6.59
2,331,577
$
(1.71)
$ (294,071.78)
$
(1.93)
$ (244,685.07)
$
(2.14)
$ (154,615.89)
$ 1,837,495
7%
$ 1,499,943
$
$
$
$
4
172080
6.10
127093
6.34
72198
6.59
2,331,577
$
(1.78)
$ (305,834.65)
$
(2.00)
$ (254,472.48)
$
(2.23)
$ (160,800.52)
$ 1,809,760
7%
$ 1,380,657
$
$
$
$
5
172080
6.10
127093
6.34
72198
6.59
2,331,577
$
120,000
$
(1.85)
$ (318,068.04)
$
(2.08)
$ (264,651.38)
$
(2.32)
$ (167,232.55)
$ 1,780,916
7%
$ 1,269,768
7,137,274
Based on the yearly projections of selling 172080 units of “Basic” openers, 127093 units of
“Deluxe” openers, and 72198 units of our “Premium” model, the net present value (NPV) of
Can-You Squeeze, Inc. is $7,137,274. This analysis is based on the assumption that the business
has an increasing variable cost for each design from year to year, according to an estimated
inflation rate of 4%, and a salvage value of $120,000 at the end of the 5th year. Also, we have
discounted using a discount rate of 7%. In addition to being NPV-positive, note that the increase
in value this project provides is large when compared to the investments required.
III Supporting Document
1.) Existing Patents
There is one exiting patent application of the initial can opener design from Can-You Squeeze,
Inc. with the US Trade and Patents Office. It was filed on August 5th, 2003 by the law firm of
Panos, Y & Papalambros with USPTO reference number 6.873.424.
2.) Bench Marking
Please refer to the technical analysis section of this report for the bench marking report.
32