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1
LSM733-PRODUCTION OPERATIONS MANAGEMENT
By: OSMAN BIN SAIF
LECTURE 26
2
JIT Schedulling Kanban Toyota Production System Lean Operations
Summary of last Session
3
Summary of last Session(Contd.)
CHAPTER : Maintenance and Reliability Operations
Global Company Profile: Orlando Utilities Commission
The Strategic Importance of Maintenance and Reliability
Reliability Improving Individual Components Providing Redundancy
4
Summary of last Session(Contd.)
Maintenance Implementing Preventive Maintenance Increasing Repair Capabilities
5
Agenda for this Session
Total Productive Maintenance Techniques for Enhancing
Maintenance
6
CHAPTER : Decision Modeling Decision Making & Models. Decision Tables.– Decision making under uncertainty.– Decision making under risk.– Expected value of perfect information (EVPI).
Agenda for this Session (Contd.)
7
Maintenance Costs
The traditional view attempted to balance preventive and breakdown maintenance costs
Typically this approach failed to consider the true total cost of breakdowns Inventory Employee morale Schedule unreliability
8
Maintenance Costs
Figure 17.4 (a)
Total costs
Breakdown maintenance costs
Cost
s
Maintenance commitment
Traditional View
Preventive maintenance costs
Optimal point (lowestcost maintenance policy)
9
Maintenance Costs
Figure 17.4 (b)
Cost
s
Maintenance commitment
Full Cost View
Optimal point (lowestcost maintenance policy)
Total costs
Full cost of breakdowns
Preventive maintenance costs
10
Maintenance Cost ExampleShould the firm contract for maintenance on their printers?
Number of Breakdowns
Number of Months That Breakdowns Occurred
0 2
1 8
2 6
3 4
Total: 20
Average cost of breakdown = $300
11
Maintenance Cost Example1. Compute the expected number of breakdowns
Number of Breakdowns
Frequency Number of Breakdowns
Frequency
0 2/20 = .1 2 6/20 = .3
1 8/20 = .4 3 4/20 = .2
∑ Number of breakdowns
Expected number of breakdowns
Corresponding frequency= x
= (0)(.1) + (1)(.4) + (2)(.3) + (3)(.2)= 1.6 breakdowns per month
12
Maintenance Cost Example2. Compute the expected breakdown cost per month with no preventive
maintenance
Expected breakdown cost
Expected number of breakdowns
Cost per breakdown= x
= (1.6)($300)= $480 per month
13
Maintenance Cost Example3. Compute the cost of preventive maintenance
Preventive maintenance cost
Cost of expected breakdowns if service contract signed
Cost of service contract
=+
= (1 breakdown/month)($300) + $150/month= $450 per month
Hire the service firm; it is less expensive
14
Increasing Repair Capabilities
1. Well-trained personnel2. Adequate resources3. Ability to establish repair plan and priorities4. Ability and authority to do material planning5. Ability to identify the cause of breakdowns6. Ability to design ways to extend MTBF
15
How Maintenance is Performed
Figure 17.5
Operator Maintenance department
Manufacturer’s field service
Depot service(return equipment)
Preventive maintenance costs less and is faster the more we move to the left
Competence is higher as we move to the right
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Total Productive Maintenance (TPM)
Designing machines that are reliable, easy to operate, and easy to maintain
Emphasizing total cost of ownership when purchasing machines, so that service and maintenance are included in the cost
Developing preventive maintenance plans that utilize the best practices of operators, maintenance departments, and depot service
Training workers to operate and maintain their own machines
17
Establishing Maintenance Policies
Simulation Computer analysis of complex situations Model maintenance programs before they are implemented Physical models can also be used
Expert systems Computers help users identify problems and select course of action
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CHAPTER : Decision Modeling
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The Decision-Making Process
Problem Decision
Quantitative Analysis
LogicHistorical DataMarketing ResearchScientific AnalysisModeling
Qualitative Analysis
EmotionsIntuitionPersonal Experience and MotivationRumors
20
Models and Scientific Management
• Can Help Managers to:
– Gain deeper insights into the business.
–Make better decisions!• Better assess alternative plans and actions.
– Quantify, reduce and understand the uncertainty surrounding business plans and actions.
21
Steps to Good Decisions• Define problem and influencing factors.• Establish decision criteria.• Select decision-making tool (model).• Identify and evaluate alternatives using
decision-making tool (model).• Select best alternative.• Implement decision.• Evaluate the outcome.
22
Benefits of Models• Allow better and faster decisions.
• Less expensive and disruptive than experimenting with the real world system.
• Allow managers to ask “What if…?” questions.
• Force a consistent and systematic approach to the analysis of problems.– Require managers to be specific about constraints and
goals.
23
Limitations of Models• May be expensive and time-consuming to
develop and test.• May be unused, misused or misunderstood (and
feared!).– Due to mathematical and logical complexity.
• May downplay the value of qualitative information.
• May use assumptions that oversimplify the real world.
24
Decision Theory
Terms:
Alternative: Course of action or choice.Decision-maker chooses among alternatives.
State of nature: An occurrence over which the decision maker has no control.
Decision Table
States of Nature
State 1 State 2
Alternative 1 Outcome 1 Outcome 2
Alternative 2 Outcome 3 Outcome 4
A-25
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A firm has two options for expanding production of a product: (1) construct a large plant; or (2) construct a small plant. Whether or not the firm expands, the future market for the product will be either favorable or unfavorable.
If a large plant is constructed and the market is favorable, then the result is a profit of $200,000. If a large plant is constructed and the market is unfavorable, then the result is a loss of $180,000.
If a small plant is constructed and the market is favorable, then the result is a profit of $100,000. If a small plant is constructed and the market is unfavorable, then the result is a loss of $20,000. Of course, the firm may also choose to “do nothing”, which produces no profit or loss.
Example - Decision Making Under Uncertainty
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Example - Decision Making Under Uncertainty
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
28
Decision Making Under Uncertainty - Criteria
• Maximax - Choose alternative that maximizes the maximum outcome for every alternative (Optimistic criterion).
• Maximin - Choose alternative that maximizes the minimum outcome for every alternative (Pessimistic criterion).
• Expected Value - Choose alternative with the highest expected value.
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Example - Maximax
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
Maximax decision is to construct large plant.
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Example - Maximin
Minimumin Row
-$180,000
-$20,000
$0
Maximin decision is to do nothing.
(Maximum of minimums for each alternative)
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
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• Probabilistic decision situation.
• States of nature have probabilities of occurrence.
• Select alternative with largest expected value (EV).– EV = Average return for alternative if decision
were repeated many times.
Decision Making Under Risk
32
Expected Value Equation
Probability of payoffEV A V P V
V P V V P V V P V
i ii
i
N N
( ( )
( ) ( ) ( )
) == *
= * + * + + *
1
1 1 2 2
Number of states of nature
Value of Payoff
Alternative i
...
N
33
Example - Expected ValueSuppose: Probability of favorable market = 0.5 Probability of unfavorable market = 0.5
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
Expected Value
$10,000
$40,000
$0
Decision is to “Construct small plant”.
34
Example - Expected ValueSuppose: Probability of favorable market = 0.7 Probability of unfavorable market = 0.3
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
Expected Value
$86,000
$64,000
$0
Now, decision is to “Construct large plant”.
35
Example - Expected ValueOver what range of values for probability of favorable market is “Construct large plant” preferred?
Solve for x: 380000x-180000 > 120000x-20000
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
Expected Value
380,000x - 180,000
120,000x - 20,000
36
Solve for x: 380000x - 180000 > 120000x - 20000
x > 0.6154
So, as long as probability of a favorable market exceeds 0.6154, then “Construct large plant”.
Example - Expected ValueOver what range of values for probability of favorable market is “Construct large plant” preferred?
37
Expected Value of Perfect Information (EVPI)
• EVPI places an upper bound on what one would pay for additional information.– EVPI is the maximum you should pay to learn
the future.
• EVPI is the expected value under certainty (EVUC) minus the maximum EV.
EVPI = EVUC - maximum EV
38
Expected Value Under Certainty (EVUC)
)P(S*jå=
=EVUC
n
j 1
where:
P(Sj ) = The probability of state of nature j.
n = Number of states of nature.
(Best outcome for the state of nature j)
39
Example - EVUC
Best outcome for Favorable Market = $200,000
Best outcome for Unfavorable Market = $0
States of NatureAlternatives Favorable
MarketUnfavorable
MarketConstructlarge plant
$200,000 -$180,000
Constructsmall plant
$100,000 -$20,000
$0 $0Do nothing
40
Expected Value of Perfect Information
EVPI = EVUC - max(EV) = ($200,000*0.50 + 0*0.50) - $40,000 = $60,000
Thus, you should be willing to pay up to $60,000 to learn whether the market will be favorable or not.
Suppose: Probability of favorable market = 0.5 Probability of unfavorable market = 0.5
41
Expected Value of Perfect Information
EVPI = EVUC - max(EV) = ($200,000*0.70 + 0*0.30) - $86,000 = $54,000
Now, you should be willing to pay up to $54,000 to learn whether the market will be favorable or not.
Now suppose: Probability of favorable market = 0.7 Probability of unfavorable market = 0.3
42
Summary of the Session
Total Productive Maintenance Techniques for Enhancing
Maintenance
43
CHAPTER : Decision Modeling Decision Making & Models. Decision Tables.– Decision making under uncertainty.– Decision making under risk.– Expected value of perfect information (EVPI).
Summary of the Session (Contd.)
44
THANK YOU