IE 3265 Production &
Operations Management
Slide Series 2
Topics for discussion
• Product Mix and Product Lifecycle – as
they affect the Capacity Planning Problem
• The Make or Buy Decision
– Its more than $ and ¢!
– Break Even Analysis, how we filter in costs
• Capacity Planning
– When, where and How Much
Product Issues related to capacity
planning
• Typical Product Lifecycle help many
companies make planning decisions
• Facility can be designed for Product
Families and the organization tries to
match lifecycle demands to keep capacitiy
utilized
The Product Life-Cycle Curve
The Product/Process Matrix
Product Mix (Families) Typically
Demand Different Production Capacity
Design
• Is product Typically “One-Off”
– These systems have little standardization and require
high marketing investment per product
– Typically ‘whatever can be made in house’ will be
made ‘in house’
– Most designs are highly private and guarded as
competitive advantages
• Multiple Products in Low Volume
– Standard components are made in volume or
purchased
– Shops use a mixture of flow and fixed site
manufacturing layouts
Product Mix (Families) Typically
Demand Different Production Capacity
Design
• Few Major (discrete) Products in Higher Volume
– Purchase most components (its worth standardizing
nearly all components)
– Make what is highly specialized or provides a
competitive advantage
– Make decisions are highly dependent of capacity
issues
• High Volume & Standardized “Commodity”
Products
– Flow processing all feed products purchased
– Manufacturing practices are carefully guarded ‘Trade
Secrets’
Make-Buy Decisions
• A difficult problem address by the M-B
matrix
• Typically requires an analysis of the issues
related to People, Processes, and
Capacity
• Ultimately the problem is addressed
economically
Make – Buy Decision Process
Secondary Questions
1.
2.
3.
4.
Is the Item Available?
Will our Union Allow
us to buy?
Is outside Quality
Acceptable?
Are Reliable Sources
Available?
Primary Question
Can Item be
Purchased?
Decision
NO
NO = MAKE
(if yes continue
down)
YES
1.
2.
3.
4.
Is Manufacturing
Consistent with our
objectives?
Do we have Technical
Expertise?
Is L & MFG capacity
available?
Must we MFG to
utilize existing
capacity?
Can Item be
Made?
YES
NO
NO = Buy
(if yes continue
down)
Make – Buy Decision Process
Secondary Questions
1.
2.
3.
4.
1.
2.
3.
What Alternatives are
available to MFG?
What is future
demand?
What are MFG costs?
What are Reliability
issues that influence
purchase or MFG?
What other
opportunities are
avail. For Capital?
What are the future
investment
implications if item is
MFG?
What are costs of
receiving external
Financing?
Primary Question
Is it cheaper
to make than
buy?
Decision
NO
NO = Buy
(if yes continue
down)
YES
Is Capital
Available To
Made?
YES
NO
NO = Buy
YES = MAKE
Break-even Curves for the
Make or Buy Problem
Cost to Buy = c1x
Cost to make=K+c2x
K
Break-even quantity
Example M-B Analysis
• Fixed Costs to Purchase consist of:
– Vendor Service Costs:
• Purchasing Agents Time
• Quality/QA Testing Equipment
• Overhead/Inventory Set Asides
• Fixed Costs to Make (Manufacture)
– Machine Overhead
• Invested $’s
• Machine Depreciation
• Maintenance Costs
– Order Related Costs (for materials purchase and
storage issues)
Example M-B Analysis
• BUY Variable Costs:
– Simply the purchase price
• Make Variable Costs
– Labor/Machine time
– Material Consumed
– Tooling Costs (consumed)
Example M-B Analysis
• Make or Buy a Machined Component
• Purchase:
• Fixed Costs for Component: $4000 annually ($20000 over 5
years)
• Purchase Price: $38.00 each
• Make Using MFG Process A
• Fixed Costs: $145,750 machine system
• Variable cost of labor/overhead is 4 minutes @ $36.50/hr:
$2.43
• Material Costs: $5.05/piece
• Total Variable costs: $7.48/each
Example M-B Analysis
• Make on MFG. Process B:
• Fixed Cost of Machine System: $312,500
• Variable Labor/overhead cost is 36sec @ 45.00/hr:
$0.45
• Material Costs: $5.05
• Formula for Breakeven:
Fa + VaX = Fb + VbX
X is Break even quantity
Fi is Fixed cost of Option i
Vi is Variable cost of Option i
Example M-B Analysis
F1  V1 X  F2  V2 X
Break Even is X that satisfies this equation or:
F 2  F1
X
V 1 V 2
• Buy vs MFG1: BE is {(145750-20000)/(38-7.48)} =
4120 units
• Buy vs MFG2: BE is {(312500-20000)/(38-5.5)} = 9000
units
• MFG1 vs MFG2: BE is {(312500-145750)/(7.48-5.50)}
= 68620 units
Capacity Strategy
Fundamental issues:
– Amount. When adding capacity, what is the optimal
amount to add?
• Too little means that more capacity will have to be added
shortly afterwards.
• Too much means that capital will be wasted.
– Timing. What is the optimal time between adding
new capacity?
– Type. Level of flexibility, automation, layout,
process, level of customization, outsourcing, etc.
Three Approaches to Capacity
Strategy
• Policy A: Try not to run short. Here capacity must
lead demand, so on average there will be
excess capacity.
• Policy B: Build to forecast. Capacity additions
should be timed so that the firm has excess
capacity half the time and is short half the time.
• Policy C: Maximize capacity utilization. Capacity
additions lag demand, so that average demand
is never met.
Capacity Leading and Lagging
Demand
Determinants of Capacity
Strategy
• Highly competitive industries (commodities,
large number of suppliers, limited functional
difference in products, time sensitive customers)
– here shortages are very costly. Use Type A
Policy.
• Monopolistic environment where manufacturer
has power over the industry: Use Type C Policy.
(Intel, Lockheed/Martin).
• Products that obsolete quickly, such as
computer products. Want type C policy, but in
competitive industry, such as computers, you will
be gone if you cannot meet customer demand.
Need best of both worlds: Dell Computer.
Mathematical Model for Timing
of Capacity Additions
Let D = Annual Increase in Demand
x = Time interval between adding capacity
r = annual discount rate (compounded continuously)
f(y) = Cost of operating a plant of capacity y
Let C(x) be the total discounted cost of all capacity
additions over an infinite horizon if new plants are built
every x units of time. Then
C ( x)  f ( xD )  e  rx f ( xD )  e 2 rx f ( xD ) 
 f ( xD )(1  e  rx  (e  rx ) 2  (e  rx )3 
f ( xD )

1  e  rx
Mathematical Model (continued
• A typical form for the cost function f(y) is:
f ( y)  ky
a
Where k is a constant of proportionality, and a measures
the ratio of incremental to average cost of a unit of plant
capacity. A typical value is a=0.6. Note that a<1 implies
economies of scale in plant construction, since
f (2 y) k (2 y) a
a


2
( 1.516 for a=.6)
a
f ( y)
k ( y)
Mathematical Model (continued)
Hence,
k ( xD)a
C ( x) 
 rx
1

e
It can be shown that this function is minimized at x
that satisfies the equation:
rx
a
rx
e

1
This is known as a transcendental equation, and
has no algebraic solution. However, using the
graph on the next slide, one can find the optimal
value of x or any value of a (0 < a < 1)
The Function f (u)  u /(e  1)
u
To Use: Locate the value of a
on the y axis and the corresponding value
of x on the x axis.
Issues in Plant Location
•
•
•
•
•
•
•
•
Size of the facility.
Product lines.
Process technology.
Labor requirements.
Utilities requirements
Environmental issues.
International considerations
Tax Incentives.