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LSM733-PRODUCTION OPERATIONS MANAGEMENT

By: OSMAN BIN SAIF

LECTURE 26

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JIT Schedulling Kanban Toyota Production System Lean Operations

Summary of last Session

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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

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Summary of last Session(Contd.)

Maintenance Implementing Preventive Maintenance Increasing Repair Capabilities

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Agenda for this Session

Total Productive Maintenance Techniques for Enhancing

Maintenance

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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.)

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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

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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)

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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

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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

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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

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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

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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

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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

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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

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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

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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.

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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.

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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.

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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.

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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

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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

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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

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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”.

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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”.

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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

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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?

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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

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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)

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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

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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

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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

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Summary of the Session

Total Productive Maintenance Techniques for Enhancing

Maintenance

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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.)

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THANK YOU