Ideal for all hippies, jocks, nerds, geeks, hepcats, dramats, zealots, and beauty queens. Hoods, jun

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HTM 302 Course Review
Ideal for all hippies, jocks, nerds, geeks,
hepcats, dramats, zealots, and beauty queens.
Hoods, junkies, or derelicts need not
apply.Dennis Guseman, Dean of the Business
School Theres something wonderfully jarring
about a bunch of students sitting under the
stars, gushing about operations management,
philosophy, and their first date. Vicki
Golich, Dean of College of Arts and Sciences
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Fall 2005 HTM 302 Course Review
A delightfully refreshing review Paula Thomas,
Los Angeles Times Will make hundreds of viewers
happy for a very long timeMichael Scott, The
New York Times HTM 302 is Superb! Breathtaking!
Almost cinematic!Bill Stein, San Francisco
Chronicle Thumbs up! Splendidly charming, you
must see it!Wade Foundas, Variety Magazine
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• Operations Management
• ... concerned with the design, planning,
  operation, and control of systems for the
  creation of goods and services.

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• Operations Management
• Many seemingly simple everyday tasks are very
  complex in nature, but repetitiveness and
  familiarity hide their complexity
• Making dinner
• Tying your shoes
• Driving to airport
• Videotaping a TV show
• Staying awake in this class
• Most real world problems demand sophisticated
  methods at first exposure

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Making Dinner
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HTM 302 Review

• In this review, we are going to apply some of the
  techniques that youve learned to a Demonstration
  Business. Well cover many, but not all of the
  course materials.

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Our Demonstration Business
Pizza Optimal Methodologies
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Sample Strategies Competing on...

• Cost
• Quality
• Flexibility
• Speed

• Process selection Make or Buy?
• Reliability of delivery
• Forecasting demand
• Supply chain

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Decision Analysis

• Quantitative decision-making techniques
• for situations where uncertainty exists

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Decision Making

• States of nature
• Events that may occur in the future
• Will it rain during tonights delivery?
• Decision maker is uncertain which state of nature
  will occur
• Decision maker has no control over the states of
  nature

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Payoff Table

• A method of organizing illustrating the payoffs
  from different decisions given various states of
  nature
• A payoff is the outcome of the decision

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Payoff Table

• States Of Nature
• Decision clear rain
• 1 driver on time late
• 2 drivers faster on time

Two states clear and rain One decision
choose 1 or 2 drivers Four possible outcomes
on time, late, faster, on time
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Decision Making with Probabilities

• Risk involves assigning probabilities to states
  of nature
• Expected value is a weighted average of decision
  outcomes in which each future state of nature is
  assigned a probability of occurrence

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Expected Value
where
xi outcome i p(xi) probability of outcome i
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Payoff Table

• Probability of rain 5
• Cost of one driver 50/night
• Cost of two drivers 100/night
• Do nothing (hire one driver) delivery cost
  50
• Hire two drivers delivery cost 100
• If we have the ability to hire one or two drivers
  as the
• need arises, and we want to plan for our delivery
  costs....
• What is our expected delivery cost?
• Expected cost 0.05(100) 0.95(50) 52.50

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Decision Making Criteria Under Uncertainty

• Maximax criterion
• Choose decision with the maximum of the maximum
  payoffs
• Maximin criterion
• Choose decision with the maximum of the minimum
  payoffs
• Minimax regret criterion
• Choose decision with the minimum of the maximum
  regrets for each alternative

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Payoff Table Tips

• States Of Nature
• Decision clear rain
• 1 driver 5 tip no tip
• 2 drivers 6 tip 5 tip

• Maximax criterion Choose decision with the
  maximum
• of the maximum payoffs (tips)
• Maximum tip (1 driver) 5
• Maximum tip (2 drivers) 6
• Which choice maximizes the maximum tip?
• Chose 2 drivers

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Payoff Table Tips

• States Of Nature
• Decision clear rain
• 1 driver 5 tip no tip
• 2 drivers 6 tip 5 tip

• Maximin criterion Choose decision with the
  maximum
• of the minimum payoffs (tips)
• Minimum tip (1 driver) 0
• Minimum tip (2 drivers) 5
• Which choice maximizes the minimum tip?
• Chose 2 drivers

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Payoff Table Tips

• States Of Nature
• Decision clear rain
• 1 driver 5 tip no tip
• 2 drivers 6 tip 5 tip

• Minimax regret criterion Choose decision with
  the
• minimum of the maximum regrets for each
  alternative
• Maximum regret (1 driver) no tip , loss of 5
• Maximum regret (2 drivers) 5 tip, loss of 1
• Which choice minimizes the maximum regret?
• Chose 2 drivers to minimize max regret

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Decision Analysis

• Weve dealt with states of nature, and
  probabilities of outcomes
• What about situations that are far more complex?
  Where there are more steps in a situation
  analysis?

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Sequential Decision Trees

• A graphical method for analyzing decision
  situations that require a sequence of decisions
  over time

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Simple Decision Tree
STATE or OUTCOME A
probability ofoutcome A
DECISION POINT
probability ofoutcome B
STATE or OUTCOME B
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Sequential Decision Tree
C
A
DECISION POINT
D
B
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Sequential Decision Tree
P(A) P(C)
C
probability ofoutcome C
DECISION 2
probability ofoutcome A
A
probability ofoutcome D
DECISION 1
D
probability ofoutcome B
P(A) P(D)
P(B)
B
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Situation Analysis

• As you deliver pizza on a clear night, you notice
  that your drivers left front tire is nearly
  bald.
• Should you call in the second driver, at a cost
  of 50?
• OR
• Should you continue with one driver, knowing that
  there
• is a 5 chance that hell get a flat and you will
• encounter a loss of 500 business and 1500 of
  good will
• (total loss of 2000)?

Draw the decision tree and calculate the expected
costs
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Decision Analysis 2nd delivery driver?
Cost 50
YES
second driver?
flat
Cost 2000
NO
0.05
0.95
no flat
Cost 0
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Decision Analysis 2nd delivery driver?
Cost 50
YES
Probabilities on any branch must sum to 1.0
second driver?
Cost 2000
flat
NO
0.05
0.95
no flat
Cost 0
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Decision Analysis 2nd delivery driver?
Cost 50
YES
second driver?
Cost 2000
flat
NO
0.05
Expected cost (0.05)(2000) (0.95)(0) 100
0.95
no flat
Cost 0
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Functional Design(How the Product Performs)

• Reliability
• Probability product performs intended function
  for specified length of time
• Maintainability
• Ease and/or cost or maintaining/repairing product

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Computing Reliability
R reliability, expressed as a fraction (0 lt R lt
1)
Components in series
R1
R2
Series the system fails if any one component
fails
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Computing Reliability
Components in series
R R1R2
R1
R2
Rs R1R2Rn
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Computing Reliability Delivering Good Pizza

• To deliver good pizza, we must use good
  ingredients, and bake properly, and deliver on
  time. If any one element fails, the system
  fails. Therefore we use the series equation
• Rs Ringredients x Rbaking x Rdelivery

example Rs (0.9) (0.9) (0.9) 0.72
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Computing Reliability
Components in parallel
R2
R1
Parallel the system works if component1 or 2 work
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Computing Reliability
Components in parallel
car1
car2
Parallel the delivery system works if car1 or
car 2 work
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Computing Reliability
Components in parallel
R2
R 1 (1-R1)(1-0.R2)
R1
Parallel the delivery system works if car1 or
car 2 work
Example if R1 R2 0.9 R 1 - (1-0.9)(1-0.9)
0.99
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Computing Reliability
Rn
n components in parallel
R2
R1
Parallel the system works if 1 or 2 or 3 or n
work
n
Rp 1 - ? (1-Ri)
I 1
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Other Reliability Measures

• MTBF
• Mean Time Between Failure
• MTTR
• Mean Time to Repair
• Both are statistical estimates gathered
• from large numbers of measurements

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System Availability
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Car Availability
If we assume car MTBF 2 years (730 days) MTTR
1 day then
730 1 730
Car Availability
99.8
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• Wake up!
• Were halfway through

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Process Selection with Break-Even Analysis
Total cost fixed cost total variable
cost Total revenue volume x price Profit
total revenue - total cost
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Solving for Break-Even Volume Buy Resell
Pizza revenue Npizzas x 15 Pizza cost 100
Npizzas x 10 What is the break-even point
for number of pizza sold???
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Solving for Break-Even Volume Buy Resell
Pizza revenue Npizzas x 15 Pizza cost 100
Npizzas x 10 To find the break-even, set the
Total Revenue equal to the Total Cost and solve
for Npizzas Npizzas x 15 100 Npizzas x
10 Npizzas 20
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Break-Even Analysis
Process A (Buy) cost line (100 10/pizza)
Revenue line (15/pizza)
300 200 100
pizzas
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Break-Even Analysis
Process A cost line (100 10/pizza)
Revenue line (15/pizza)
300 200 100
Process B (Make) cost line (200 5/pizza)
pizzas
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Break-Even Analysis
Process A (Buy) cost line (100 10/pizza)
Revenue line (15/pizza)
300 200 100
Process B (Make) cost line (200 5/pizza)
Choose process A
pizzas
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Break-Even Analysis
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A Gantt Chart

• Popular tool for project scheduling
• Graph with bar for representing the time for each
  task
• Provides visual display of project schedule
• Also shows slack for activities
• Amount of time activity can be delayed without
  delaying project

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A Simplified Gantt Chart
Minutes
0 2 4 6 8 10

Activity Receive order Throw dough Schedule
driver Add toppings Prep oven Fold
box Bake
RED lines indicate mandatory order of events
1 3 5 7 9
Month
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A Simplified Gantt Chart
Minutes
0 2 4 6 8 10

Activity Receive order Throw dough Schedule
driver Add toppings Prep oven Fold
box Bake
Possible slack time of one min
or as late as min 4
Could start as early as min 3
1 3 5 7 9
Month
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A Simplified Gantt Chart
Minutes
0 2 4 6 8 10

Activity Receive order Throw dough Schedule
driver Add toppings Prep oven Fold
box Bake
RED lines indicate mandatory order of events
Items that could be done earlier
1 3 5 7 9
Month
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Project Network for a Pizza
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Project Network for a Pizza
3
Schedule driver
Dummy
Bake
Addtoppings
Take order
Throwdough
Prepoven
Dummy
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Foldbox
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Completing items earlier
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Project Network for a Pizza
3
Schedule driver
Dummy
Bake
Addtoppings
Take order
Throwdough
Prepoven
Dummy
7
Foldbox
8
Completing items even earlier
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Critical Path

• A path is a sequence of connected activities
  running from start to end node in network
• The critical path is the path with the longest
  duration in the network
• Project cannot be completed in less than the
  time of the critical path

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What is the Critical Path?
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Schedule driver
Dummy
Bake
Addtoppings
Take order
Throwdough
Prepoven
Foldbox
5
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Critical Path
3
Schedule driver
Dummy
Bake
Addtoppings
Take order
Throwdough
Prepoven
Foldbox
5
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Early Times

• ES - earliest time activity can (reliably) start
• EF ES activity time
• Work left-to-right to determine ES EF

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Late Times

• LS - latest time activity can start not delay
  project
• LF LS activity time
• Work right-to-left to determine LS LF

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Activity Slack

• Activities on critical path have ES LS EF
  LF
• Activities not on critical path have slack

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Project Crashing

• Crashing is reducing project time by expending
  additional resources
• Crash time is an amount of time an activity is
  reduced
• Crash cost is the cost of reducing the activity
  time
• Goal is to reduce project duration at minimum cost

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Supply Chain

• All activities associated with the flow and
  transformation of goods and services from raw
  materials to the end user, the customer
• A sequence of business activities from suppliers
  through customers that provide the products,
  services, and information to achieve customer
  satisfaction

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The Pizza Supply Chain Process 1 Buy
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The Pizza Supply Chain Process 2 Make
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Supply Chain Management

• Synchronization of activities required to achieve
  maximum competitive benefits
• Coordination, cooperation, and communication
• Rapid flow of information

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Supply Chain Uncertainty

• Forecasting, lead times, batch ordering, price
  fluctuations, and inflated orders contribute to
  variability
• Inventory is a form of insurance
• Distorted information is one of the main causes
  of uncertainty

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Vendor-Managed Inventory

• Manufacturers generate orders, not distributors
• Stocking information is accessed electronically
• Increased speed, reduced errors, and improved
  service

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Components of Forecasting Demand

• Time Frames
• Short-range
• medium-range
• long-range
• Demand Behavior
• Trends, cycles, seasonal patterns, random

• Pizza Business
• today
• this week
• 2-5 yrs
• Weekends, local events, etc.

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Moving Average

• Average several periods of data
• Dampen, smooth out changes
• Use when demand is stable with no trend or
  seasonal pattern

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Pizza Demand
60 50 40 30 20 10 0
Orders
Mon Tues Weds Thu Fri Sat
Sun Mon Tue Wed
Day
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Quality

• Three categories of satisfaction
• Basic or expected attributes
• Performance attributes
• Surprise and delight attributes

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Who owns Quality

• Order taker
• Cook
• Driver/delivery person
• Suppliers

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Cost of Quality

• What are the costs of poor quality?

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• Are we there yet?

Ok, time to wake up, weve got one more film
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Final Exam

• Next Tuesday at.
• 1130 AM - 120 PM