Asset Management Decision Making with DST & The SALVO …saama.org.za/wp...Huggett.Asset-Management-decision-making.SALVO_.pdf · © Decision Support Tools Ltd 2014© Decision Support

© Decision Support Tools Ltd 2014© Decision Support Tools Ltd 2014

Asset Management

Decision Making with DST &

The SALVO Process

Jack Huggett, Principal Consultant

The Woodhouse Partnership Ltd – DST & SALVO

SAAMA Conference Workshop

12 May 2014

Cape Town, South Africa


Your workshop leader

Summary CV:• Principal Consultant, The Woodhouse Partnership Ltd (TWPL) &

• DSTL Decision Support Tools Ltd.

• Maintenance & Asset Management facilitator, trainer, mentor and coach

• 34 years of international experience

• 43 countries in all the continents

• Industries, mainly

• Oil and gas (upstream and downstream)

• Electrical generation, transmission and distribution

• Rail

• Chemical

• Brewing

• General Industry.

Jack Huggett BSc Eng. MBL


This session

• Introductions

• Asset Management processes & decision-making

• SALVO project and the 6-steps ‘Smiley’

• Evaluating what to do, when & why

– Optimization concepts: getting the jargon sorted

– Decisions with lousy data

– Structured processes: getting a bit of discipline in place

• Case studies & examples

– Justifying planned maintenance & asset life extension

– Asset replacements: optimal timing & justification


Who is DST?

Decision Support Tools Ltd

• “Technical products” division of The Woodhouse Partnership Ltd (TWPL)

• Some of the top modelling, maths & software experts in the UK

• Acquired Operational Reliability Manager (ORM) toolkit from Shell in 2007

• Acquired APT Ltd (& APT toolkit) in 2008

• Prime contractor for the SALVO project

• Strategic partnership with Cambridge University


“Normal”Operation &

Maintenance cycles

Asset health &utilisation benefits

Different Decision Environments

AcquisitionCAPEX

OPEX, Risks &Minor Changes CAPEX

Bus

ines

s im

pact

Design/project

phase decisions

Operational

optimizations

Degradation, technologyovertake, obsolescence,

demand changes

Aging assets

decisions


Aging Assets: Scale of the Challenge

• Aging infrastructure: >$1 Trillion in USA and >£200 Billion in UK

• Technology change rate: more automation, higher

obsolescence rates

• New developments are more easy to justify than existing asset

replacements.

• Very little guidance, consistency or evaluation methods for the

different options


Existing “Solutions” & “Methodologies”

Asset history &data analytics

TOFDTOFDTOFDTOFD

InsulationTesting

RCA

Oil AnalysisOil AnalysisOil AnalysisOil Analysis

Network/system performance

simulation

LEANLEANLEANLEAN

…but none of them really provide the business case for what to do, when


European MACRO

project EU1488

Best practices in

asset management

decision-making

November 1995 - May 2000

Primary sponsors:The Woodhouse Partnership (Project Managers)Asset Performance Tools (Software Development)Anglesey Aluminium UK Government (DTI)Brown & Root Det Norske VeritasNational Power Institute of Asset MgmtNational Grid RailtrackShell Norway ICI EutechPDVSA Yorkshire Electricity

Capital investmentsEquipment purchase (life cycle cost)Renewal timingUpgrades & modificationsOpportunities & shutdown ‘bundles’

O&M decisionsMaintenance intervalsInspection/condition monitoring intervalsCondition reaction pointsFunctional testing strategies

Purchasing & materials decisionsPurchase quantities & thresholds etcStrategic spares

Decision types:


Project Summary

R&D project to produce:• Best practice definition• Process & methods guidance• Decision-support tools• Case studies & templates

Scope: identification of optimal strategies for managing assets, their degradation, obsolescence, renewal, refurbishments and changing inspection & maintenance requirements.







The SALVO Process:

6 steps,

Step by Step


Which assets are worthy of attention, and how can we

group them for common needs, urgency etc?

SALVO identified c.40 possible ‘grouping criteria’ including:

• Asset types, modularity, reparability, replace-ability

• Asset ages, usage, performance history (including trends & forecasts)

• Asset ‘health’ (current condition & performance)

• Demand and utilization forecasts

• Asset criticality/value

• Technology overtake/obsolescence

• Legislation & standards changes

Step 1: Identify & prioritise problems/opportunities


274 transformer population:


34 240kV transformers of various ages

and health indices:


240kV transformers are most critical in

transmission network:



Grouping assets for shared strategy

• Clear-cut ‘digital’ differences

– Asset types, designs, models

– Indoor/outdoor

– Spared, un-spared locations

• Continuous variables need segmentation

– Ages (or installation dates)

– Usage levels/rates

– Asset criticality, performance,

condition, reliability etc.


Grouping assets for shared strategy - criteria

Age versusPredicted Life

External and/orfuture threatsSupply chainCustomer demands

Asset FunctionalCriticality

Capital Value

Asset ‘Health ’

Condition Performance

Need to convertinto ‘residual life’implications

refinement ofassumptionsa) Current state

b) Rates of change

Urgency of attentionIm

port

ance

of a

ttent

ion Chosen assets or groups of

assets that need priority study

refinement ofassumptions


‘Improveability’ is the real basis for prioritized

attention

0100200300400500600700800900

1000

Opportunity to improve

Improvement

Residual risk

Biggest improvementopportunity may not be

the biggest current ‘headache’

But we don’t know yet how much

improvement we will get for our money…


Step 2: Define the Problem

• Problem statement: context, facts and questions to

answer

• Root Cause Analysis: understand and focus on the

underlying problem, not just the symptoms

– RCA ahead of the event, not just ‘post mortem’

• Other assets suffering the same underlying problem

(revise grouping)?


Step 3: Identifying potential solutions

• FMEA, RCM & RBI valuable but focus on technical intervention options (e.g. inspection or maintenance method)

• Need to encourage wider consideration of options and possible solutions

• Best solution is not always an asset/engineering one(e.g. take out insurance or change operator behaviours)


1 Acquire/ Create

1.1 Acquire/create new asset (replace existing)1.2 Acquire/create new asset (in addition to existing)1.3 Change technical specification for acquiring/creati ng1.4 Change supplier/constructor

2 Utilize 2.1 Change operational parameters2.2 Change operation (duty, loading)2.3 Change operational procedures2.4 Improve operator competence2.5 Improve operator motivation/recognition’ 2.6 Increase buffer stock/capacity2.7 Change outsourcing/insourcing of asset operation2.8 Outsource asset function

3 Maintain 3.1 1-off asset health assessment3.2 Periodic non-intrusive inspections3.3 Periodic intrusive inspections3.4 Continuous condition/performance monitoring3.5 Periodic functional testing3.6 1-off maintenance/refurbishment3.7 Periodic preventive maintenance3.8 Planned corrective maintenance3.9 Run To Failure corrective maintenance3.10 Change spares holding3.11 Improve maintainer competence3.12 Improve maintainer motivation/recognition3.13 Change maintenance procedures3.14 Change outsource/insource of maintenance

4 Change/ improve

4.1 Modify asset (change level of cost/risk/perf)4.2 Refurbish asset (change degradation rate & extend l ife)4.3 Change asset configuration4.4 Change asset functional location/usage4.5 Change outsourcing/insource of changes/improvements

5 Renew/ dispose

5.1 Replace existing asset (like-for-like)5.2 Replace existing asset (incl upgrade/downgrade)5.3 Change outsourcing/insourcing of asset renewals5.4 Decommission and mothball5.5 Decommission and salvage spares5.6 Decommission and dispose

6 Contingency planning

6.1 Manage stakeholder expectations (e.g. risk appetite )6.2 Acquire asset technical data 6.3 Create Emergency/Business Continuity plans6.4 Take out insurance6.5 Adjust asset valuation/criticality6.6 Diversify supply chain

Acquire/create new asset (replace existing)Acquire/create new asset (in addition to existing)Change technical specification for acquiring/creati ngChange supplier/constructorChange operational parametersChange operation (duty, loading)Change operational proceduresImprove operator competenceImprove operator motivation/recognition’ Increase buffer stock/capacityChange outsourcing/insourcing of asset operationOutsource asset function1-off asset health assessmentPeriodic non -intrusive inspectionsPeriodic intrusive inspectionsContinuous condition/performance monitoringPeriodic functional testing1-off maintenance/refurbishmentPeriodic preventive maintenancePlanned corrective maintenanceRun To Failure corrective maintenanceChange spares holdingImprove maintainer competenceImprove maintainer motivation/recognitionChange maintenance proceduresChange outsource/insource of maintenanceModify asset (change level of cost/risk/perf)Refurbish asset (change degradation rate & extend l ife)Change asset configurationChange asset functional location/usageChange outsourcing/insource of changes/improvementsReplace existing asset (like -for-like)Replace existing asset (incl upgrade/downgrade)Change outsourcing/insourcing of asset renewalsDecommission and mothballDecommission and salvage sparesDecommission and disposeManage stakeholder expectations (e.g. risk appetite )Acquire asset technical data Create Emergency/Business Continuity plansTake out insuranceAdjust asset valuation/criticalityDiversify supply chain

• Asset (e.g. maintenance, modification, renewal) and • Non-asset (e.g. process, mitigation, insurance) options

There areMANY potential solutions


Step 4: Evaluating an option

� LCC & trade-off calculations to evaluate cost/benefit & optimal timings

� Must cope with uncertainty in assumptions

� Must handle risk (incl. deterioration & risks that affect each other)

� Must handle intangibles such as reputation, ambience, morale etc.

� Value-for-money criterion (not “gold plated” or “cheapest/quickest”)

� Results must be explainable to financial & non-technical staff




Acknowledge the conflicting objectivesShamrock diagram from European MACRO project EU1488 www.MACROproject.org


“Optimization”

• Greatly over-used and mis-used term!

• At the heart of good asset management decision-

making

• Formal requirement within PAS 55 standard for

“optimal management of physical assets”

• Major education gap: what is ‘optimal’ and how can

we demonstrate it?



Exercise: Asset efficiency that deteriorates over time

5% performance loss after 6 months of operation. Deterioration is linear.

5% loss = £5/hour extra energy costs.

Total cost of cleaning = £1500 to ‘reset the clock’.

100%

95%

2000 4000 Hourssince last cleaning

6000

£5/Hour

HOW OFTEN SHOULD YOU CLEAN?



1000 1.50 0.625 2.13

2000 0.75 1.25 2.00

3000 0.50 1.88 2.38

4000 0.38 2.5 2.88

Total

$/hour

$/hour

$1500

cleaning

cost $/hour

Energy

loss

$/hourHours

Results

Costs of different

cleaning strategies:


“Get better data first” usually fails: what data, when available & what is ‘good enough’?

Sophisticated analysis with weak data: Garbage In -Garbage Out

Better

Decisions

SALVO method :: Iterative, “what if?” analysis: find out which assumptions matter & what data is therefore worthcollecting

Problems in making optimal decisions

Quality & Quantity of Data

SubjectiveInterpretation& confusion

An

aly

tica

l rig

ou

r &

eff

ort

CorrectCost, Risk& BenefitCalculation

Partial

knowledge &

‘Guesstimates’

Bad

Decisions


Better

Decisions

Disciplined Process


An

aly

tica

l rig

ou

r &

eff

ort

Bad

Decisions

1: checklist/storyboard to force

the right questions to be asked

(pre-consider how answers would be used)


Better

Decisions

Probing ahead


An

aly

tica

l rig

ou

r &

eff

ort

Bad

Decisions

2: capture knowledge as

range-estimates across

limits of credibility (e.g. min/max)



Sherlock Holmes method

“Eliminate the impossible: “Eliminate the impossible: “Eliminate the impossible: “Eliminate the impossible:

what what what what you are left with you are left with you are left with you are left with

MUST include the MUST include the MUST include the MUST include the truth!”truth!”truth!”truth!”

Actually the original was “When you have eliminated the impossible, then what you are left with, no matter how seemingly improbable, must include the truth.”



Better

Decisions

Probing ahead


An

aly

tica

l rig

ou

r &

eff

ort

Bad

Decisions

3: evaluate sensitivities to identify which

uncertain assumptions

affect the decision


Better

Decisions

Probing ahead


An

aly

tica

l rig

ou

r &

eff

ort

Bad

Decisions

4: only seek better data if cost of uncertainty

exceeds cost of getting the extra data

(typically <10% of assumptions)


Better

Decisions

Probing ahead


An

aly

tica

l rig

ou

r &

eff

ort

Bad

Decisions

5: Does better data yield

robust conclusion? If not, repeat….


Robust decision from uncertain data

Maintenance Interval (months)

Tota

l cos

ts &

ris

ks (

£k/d

ay)




“Storyboards” to capture info

Clear definition of the problem, the asset(s)

& the action to be evaluated

Scenario-based capture of assumptions:

“what if?” style

Hard data if we have it -

otherwise range-estimating

Instant view of reliability/risk

implications (survival, failure

density, hazard rates)


Life cycle cost & risk patterns interact

The math is ‘non-trivial’

Asset Age

Maintenance Tasks, Shutdowns, Modifications etc.

Maintenance-inducedrisks Increasing risk

Fail

ure

pro

ba

bil

ity

?


Typical results: $$ impact of different

intervention timings

Lowest total impact =

optimum replacement

point

Design life or

‘obsolescent’ point

Total business impact

of all costs, risks etc.

Consequences of

delaying renewal

beyond optimum


Extracting useful observations & conclusions

Consequences of delay (= timing criticality for renewal)

‘Premium paid for

Shine’ (if wechoose to

replace now) Biggest influences on timing decision

Auto-generated

observations


Sensitivity testing to uncertain data

Uncertainty range for optimal timing

Recommended timing (safest, given

data uncertainty)


SALVO Step 5: Activity Bundling

• Searching for cost, access or resource sharing opportunities:

– Downtime (shutdowns, turnarounds, outages, possessions)

– Remote site visits & logistics costs

• Re-mixing minor and major work packages & work alignments

• Evaluating discrete alignment opportunities for work

implementation

• DST Schedule Optimizer searches for best combined

programme:


Example: optimized work bundles

Bundle Optimized

Individually optimized

Typically 25-50% reduction in shared costs & planne d downtime



The SALVO licensee ‘Playbook’

Context, organisation, planning,

leadership, administration,

workshops, communications etc.


SALVO Processes in detail

Step-by-step process guide,

flow diagrams, examples and

templates


The SALVO Guidebook

• Step-by-step explanation of the SALVO process for determining the optimal management strategies for aging assets.

• Extensive use of case studies and real-world examples.

• Building better decision-making skills in the organisation

• Core principles and practical applications to over 40 common decision types, ranging from inspection, maintenance and operating strategies to process changes, plant modifications, refurbishments and optimal timing for replacement or decommissioning.

The public domain guidebook




Asset decisions involve trade-off and real

optimization


We can and must work with mixed quality

information


SALVO field trial results

• All studies so far (>30) have revealed over £700k/year potential improvements typically within 1-3 weeks. e.g.– Water industry: filter life cycles, treatment works refurbishments– Rail sector: track grinding, steelwork painting– Process sector: control systems obsolescence, motor renewals– Manufacturing: shutdown intervals

• DCS control system replacements (obsolescence management) revealed over $25 Million benefits

• Generic approach works: asset- and industry-specific differences exist only at the ‘cosmetic’ level (language, values, mix of decision drivers etc.)

• Existing tacit knowledge is usually enough to make fully robust, transparent & auditable LCC decisions

• Teaching technical people how to make a clear commercial business case changes the game!


Thank you!

www.SALVOproject.org

www.decisionsupportools.com

Jack Huggett, Principal Consultant

The Woodhouse Partnership Ltd

Documents

Asset Management Decision Making with DST & The SALVO …saama.org.za/wp...Huggett.Asset-Management-decision-making.SALVO_.pdf · © Decision Support Tools Ltd 2014© Decision Support