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SMS – Spares Management SMS – Spares Management SoftwareSoftware

Overview and Case StudiesOverview and Case Studies

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Interval StockReliability

Spares Management Software (SMS)Spares Management Software (SMS)

Optimal

Spares

Requirement

Optimization criteria

Instant. StockReliability

Availability

CostMinimization

Supportability

Stock

Remaining

Life

Non-Repairable Non-Repairable SparesSpares

Repairable Repairable SparesSpares

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Repairable Spares# items in service

Repairshop

repaired units

stock

time

Failures

failed units

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Criteria for Decision Making

1.Instant reliability

2.Interval reliability

3.Cost minimization

4.(Process) Availability

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Scenario

• Plant has 62 electric motors on their conveyor systems (Mining company)

• MTBReplacements of motors is 3000 days (8 years)

• Planning horizon is 1825 days (5 years)

• Cost of spare motor is 15,000 $

• Value of unused spare is 10,000 $

• Cost of emergency spare is 75,000 $

• MTTRepair a motor is 80 days

• Cost of plant downtime for a single motor is 1000 $ per day

• Holding cost of a spare is 4.11 $ per day (10% of value of part/annum)

QUESTION: HOW MANY SPARE PARTS TO STOCK?

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Results: Repairable Parts

Electric motors

• Interval reliability: 95% reliability requires 7 spares

• Instant reliability: 95% reliability requires 4 spares

• Cost minimization: requires 6 spares. Associated plant availability is 100.00%

• Availability of 95%: requires 0 spares. Associated electric motor availability is 97.4% [Note: If availability of 99% was required (rather than the specified 95%) then spares required would be 2]

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Reference Case

Population 100 transformers

Failure Rate 0.005 failures/transformer/yr

Repair Time 1 yr

Replacement Time

0.001yr

Interval 1 yr

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Repairable Instantaneous Reliability

Vary Spares

0.9

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

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1 2 3 4 5

Spares

Rel

iab

ility

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Case studies:

1. Fume fan shaft, blast furnace in a steel operation: non-repairable part, decision support

2. Power train component, haul trucks: repairable parts, multiple criteria

3. Frigate control system: supportability interval

Additional CasesAdditional Cases

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1. Fume fan shaft – steel mill1. Fume fan shaft – steel mill

Spares provisioning optimization project

• Part: fume fan shaft used in a Blast Furnace• Decision: should there be 0 or 1 spares?• Complication:

• Part has long lifespan (25-40 years).• Long lead time (22 weeks).• If part fails, results are catastrophic (loss of almost $6

million per week).• Inventories are trying to be minimized.

SMS was used to quantify the risk involved in not having a spare

Decision supportDecision support

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How many spares – Fume fan shaft?How many spares – Fume fan shaft?

MTBF Vs Reliability with 22 week LT

97

97.5

98

98.5

99

99.5

100

100.5

0 5 10 15 20 25 30 35 40 45

Mean time between failures

Rel

iabi

lity 0 spares

1 spare

2 spares

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2. Repairable components – haul 2. Repairable components – haul truckstrucks

Open pit mining operation in South America

Haul truck power train component: COMPONENT X

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6,600 operating hours per truck per year (average fleet utilization)

Preventive replacement policy at 9,000 operating hours in place

Repairable components - Data / 1Repairable components - Data / 1

GeneralGeneral

Two parameter Weibull distribution, fitted using Weibull++

• 171 events: 86 failures, 85 suspensions (preventive replacements)

• Beta = 0.8565

• Eta = 14,650 operating hours

• Mean time to replacement = 6,420.3 operating hours

Time to replacementTime to replacement

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Based on estimations provided by maintenance personnel

Estimated at MTTR = 452 operating hours

Repairable components - Data / 2Repairable components - Data / 2

Time to repairTime to repair

Downtime: estimated using operational indicators (value of lost production, $2,173.3 / op. hour)

Holding: 25% of the value of the part per annum ($1.51/ op. hour)

Cost of downtime and holding costsCost of downtime and holding costs

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Repairable components - Data SummaryRepairable components - Data Summary

SMS can perform the optimization based on four criteriaSMS can perform the optimization based on four criteria

Parameter Value

Number of components in operation 78

MTBReplacements (μ) 6420.3 (op. hours)

Planning horizon (T) 6600 (op. hours)

MTTRepair (μR) 452 (op. hours)

Holding cost for one spare $1.51 per op. hour (25% of value of part/annum)

Cost of plant downtime for a single component

$2173.3 per op. hour

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Repairable components - ResultsRepairable components - Results

Case & Optimization criteria Optimal Stock level

Associated Values

Interval Reliability(goal = 95%)

15 Reliability = 98.05%(for stock=14, Rel.=94.99%)

Instantaneous Reliability(goal = 95%)

10 Reliability = 97.53%(for stock=9, Rel.=94.75%)

Availability(goal = 99%)

6 Availability = 99.14 %

Cost minimization 14 Total cost per unit time = $23

Inst. Reliability = 99.94%

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4. Frigate control system – supportability 4. Frigate control system – supportability intervals (S.I.)intervals (S.I.)

Determination of supportability intervals

• Several electronic components – control system• Parts no longer available - discontinued• Decision: how long can we support the operation of

the system using only the current stock? (achieving the desired reliability of the stock)

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Case Study – Supportability Interval Case Study – Supportability Interval (S.I.)(S.I.)

Summary of Data

Part # Parts in Operation

(complete fleet)

Rate of Replacements yearpart

tsreplacemen

Stock Level

V 12 0.0556 6 W 12 0.4259 8 X 12 0.3241 16 Y 12 0.3796 19 Z 36 0.0432 11

Supportability interval (RUL of current stock) can be rapidly calculated using SMS – NEWLY ADDED FEATURE

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Case Study (S.I.) / 2Case Study (S.I.) / 2

Results

Supportability for the system is influenced by the (shortest) supportability for any of its critical parts

Supportability Interval T* (years) Part Stock Level Reliability=90% Reliability=95% Reliability=99%

V 6 5.84 4.92 3.49 W 8 1.06 0.92 0.69 X 16 3.08 2.79 2.28 Y 19 3.19 2.91 2.43 Z 11 5.03 4.45 3.49

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Case Study (S.I.) / 3Case Study (S.I.) / 3

Informed decisions for:

• Adequate timing for replacement of current system

• Placement of final orders for discontinued parts

• Maximum supportability interval for current stock – procurement planning

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