Principles for risk and uncertainty analysis and management, in a production assurance setting Roger Flage PhD student on the RAMONA project (research.

Principles for risk and uncertainty analysis and management, in a production assurance setting

Roger Flage

PhD student on the RAMONA project(research tasks 1 and 4)

2

Basis for this presentation

Aven, T. & Flage, R.Use of decision criteria based on expected values to support decision-making in a production assurance and safety setting.Reliability Engineering and System Safety, to appear.

Flage, R. & Aven, T.On treatment of uncertainty in system planning.Reliability Engieering and System Safety, to appear.

3

Expected value decision criteria

How should we use the E[NPV] approach, with adjustments, in the decision-making process?

NPV Net Present Value

4

The E[NPV]

T

tt

t

t

r

YENPVE

0 )1(

][][

Expected cash flow at year t

= E[Bt] – E[Ct]

Analysis period

Discount rate at year t

Bt benefits (revenues) at year tCt costs at year t

5

Uncertainty reduction in system planning

Should we use predefined uncertainty interval categories to direct uncertainty reduction processes?

6

Uncertainty reduction structure Prediction interval categories

Feasibility phase Concept development phase

Engineering phase

E1[Y] ± 40%

Y

± 30%± 20%

E2[Y]E3[Y]

Y Performance measure (e.g production downtime)

1%100qEYYP

7



Engineering phase

E1[Y] ± 40%

Y

± 30%± 20%

E2[Y]E3[Y]


1%100qEYYP

Use with care

8

Some E[NPV] adjustments

TSNPVE S ,][ 0

][1.1][9.0][ ttt CEBEYE

0][ vNPVE

)][(][ fmifi rrErrE

6][ BCE

• Risk-adjusted discount rate

• Downward revision of benefits,upward revision of costs

• Safety margin

• Negative safety margin

• Cut-off periods

9

Some E[NPV] adjustments

TSNPVE S ,][ 0

][1.1][9.0][ ttt CEBEYE

0][ vNPVE

)][(][ fmifi rrErrE

6][ BCE

• Risk-adjusted discount rate

• Downward revision of benefits,upward revision of costs

• Safety margin

• Negative safety margin

• Cut-off periods

Considerable arbitrariness

10

Wrong assumptions

• All aspects of risk and uncertainty have been taken into account in the formulae

• There is no need for seeing beyond the formulae

11

The main problem

Risk and uncertainties are represented by probabilities, but probabilities are not perfect tools for expressing risks and uncertainties.

12

Decision situations

1. Known, “objective” probability distributions can be established

2. More or less complete ignorance

3. A situation between the two extremes 1) and 2)

13

Approaches to arriving at a good decision

Decision criterion Decision

Analyses Managerial reviewand judgement

Decision

Basis for the analysesOther concerns

Analyses

14

Uncertainty reduction in system planning

Should we use predefined uncertainty interval categories to direct uncertainty reduction processes?

15



Engineering phase

E1[Y] ± 40%

Y

± 30%± 20%

E2[Y]E3[Y]


1%100qEYYP

16



Engineering phase

E1[Y] ± 40%

Y

± 30%± 20%

E2[Y]E3[Y]


1%100qEYYP

Use with care

17

Structural levels and planning guidance

Structural level

Plant or system

System

Subsystem, equipment and component

18


Structural level Form of planning guidance

Plant or system Overall ideal goals

System Requirements related to expected performance

Requirements related to uncertainty about performance

Specifications related to design or operation


Requirements related to expected performance



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Structural level Form of planning guidance Specific examples and examples of attributes

Plant or system Overall ideal goals “No production losses”


Throughput availabilityDemand availability


Prediction interval limitsLimit for variance of lost throughput


CapacitySize and weightOperating temperature rangeMaintenance- Spare part needs- Manpower needs



Mean time to failure (MTTF)Mean time to repair (MTTR)


Reliability/availability at a specified time


CapacitySize and weight…

20


Structural level Form of planning guidance Specific examples and examples of attributes

Plant or system Overall ideal goals “No production losses”


Throughput availabilityDemand availability


Prediction interval limitsLimit for variance of lost throughput


CapacitySize and weightOperating temperature rangeMaintenance- Spare part needs- Manpower needs



Mean time to failure (MTTF)Mean time to repair (MTTR)


Reliability/availability at a specified time


CapacitySize and weight…

21


Structural level Form of planning guidance Specific examples and examples of attributes“No production losses”Throughput availabilityDemand availabilityPrediction interval limitsLimit for variance of lost throughputCapacitySize and weightOperating temperature rangeMaintenance- Spare part needs- Manpower needsMean time to failure (MTTF)Mean time to repair (MTTR)Reliability/availability at a specified timeCapacitySize and weight…

Plant or system Overall ideal goals








Avoid unless a rationalecan be given

May be stated whenlevel of detail inplanning becomes high

Do not treat asabsolute limits

“Optimisation”(in a broad sense)

Feasib

ility a

nd

con

cep

td

evelo

pm

en

t ph

ase

sEn

gin

eerin

gp

hase

22

Conclusions

• Be careful in using adjustments of expected values to reflect risk and uncertainties

• Use predefined uncertainty interval categories with care

23

Situation 1Known, “objective” probability distributions can be established

Net benefit 0 1 10

Probability 0.90 0.09 0.1 E[NPV] = 0.09

Net benefit -1000 0 1 10

Probability 0.00001 0.90 0.09 0.1E[NPV] = 0.09

+ safety concerns

+ environmental issues

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Situation 2More or less complete ignorance

Net benefit -108 0 100 108

Probability 0.25 0.25 0.25 0.25E[NPV] = 25

1. E[NPV] poor prediction consider distribution

2. Poor basis for probabilities (knowledge based)

3. Even more extreme outcomes could occur

4. Uncertainties related to non-economic outcome dimensions• e.g. health problems for workers in 20-30 years

Little is gained by introducing a specific formulareflecting uncertainty and risk aversion

25

Situation 3A situation between the two extremes (1) and (2)

How much weight to give to risk and uncertainties?

• The company’s attitude towards risk and uncertainty• The frame conditions, for example defined through taxes, regulations etc.• Compensation schemes (monetary or in kind)• Insurance and liability• Sustainability. Does the project assist in sustaining vital ecological functions,

economic prosperity and social cohesion?• Ethical concerns, for example related to equity and fairness• Political concerns…

A balanced perspective is required

Principles for risk and uncertainty analysis and management, in a production assurance setting Roger Flage PhD student on the RAMONA project (research.

Documents

y y performance measure

care slide

component slide

g production downtime

uncertainty analysis

treatment of uncertainty

system safety

system planning