1) Go for preventive maintenance!

2) Eliminate process problems

3) Segment your spare parts portfolio

4) Evaluate spare parts criticality

5) Spare parts management starts with good forecasting

6) Use special methods for intermittent demand items

7) Consider the whole life cycle of your equipment

8) Computers and technologies will help you

Eight rules for efficient SPM

Go for preventive maintenance!

STANDARD

PLANNED

PLANNED

MAINTENANCE

CORRECTIVE

(REPAIRS)

UNPLANNED

PREDICTIVE

PROACTIVE

DEFFERED

CORRECTIVE

PLANNED PROCUREMENTINVENTORY

MANAGEMENT

Go for preventive maintenance!

Eliminate process problems

SPARE PARTS PROCESS

Who is responsiblefor spares stock?

Who/how oftenapproves?

Procurementspecification missing

Insufficient sparesidentification

Are returns to warehouse allowed?

Spare parts process – benchmarking

Internal best practice

PLANT 1 PLANT 2 PLANT 3 PLANT 4

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

1 2 3 4

Comparison of inventory turnover

Eliminate process problems

SP NEED

IDENTIFICATION

No direct responsibility of maintenance engineers/technicians for

“their” items and spare parts levels.

REQUEST

FOR ORDER

RFO created by someone else, not the technician who requested part.

The step of RFO may not be necessary in the process.

APPROVAL

How often are orders approved? Who approves?

Approving in IS workflow or by signing a paper copy? Or both?

Approving both RFO and then issued order again?

Too many approvers, complicated procedure and hierarchy.

Approving on high levels of management.

PROCUREMENT

Insufficient information available to procurement, poor spare parts

identification – the buyer hardly knows what should be bought,

additional communication with maintenance technician is needed.

Missing or incomplete procurement specification in the IS.

EOQ

MAX

Ordering systems

s|Q

s|S

Fixed period

Fixe

dq

uan

tity

Var

iab

leq

uan

tity

B|Q

B|S

Variable period

Ideal world: inventory management modelConstant demand and lead time

STOCK

400

200

0Days 10 20 30 40 50 60

Order sent Order sentAverage

stock

Goods deliveredGoods delivered

Order more often!

STOCK

400

200

0DAYS 10 20 30 40 50 60

Order sent Order sentAverage

stock

Goods deliveredGoods delivered

No impactto risk!!

Real example: Material 210015: from order quantity 200 000 pcs down to 80 000 pcs: reduction of average stock by 60 000 pcs = 265 546 Kč

Optimal order size – EOQEconomic Order Quantity

Ordering cost(transportation)

Inventory holding cost

(warehousing)

Total cost

No impactto risk!!

Orderingdaily

Ordering oncea year

Order size [pcs]

Eliminate process problems

CONSUMPTIONSlow spare part issues in case of sudden need.

Issued spare parts are not consumed in fact. What happens then?

Consumption of external material even in case the part is on stock.

WAREHOUSE

RETURNS AND

REFURBISHED

SPARE PARTS

Refurbished parts return to warehouse while new are bought.

Accounting price of refurbished items is much higher (or lower) than

the non-realistic value of items on stock.

Problematic or impossible returns of parts issued but not consumed.

Insufficient control of parts dismantled from the maintained object

(the information system has no information about these).

RECEPTIONProblems with missing (undelivered) documentation for the received

material (certificates, declarations).

Lost spare parts documentation – only “paper-based” archiving.

WAREHOUSING

Insufficient identification of spare parts in the warehouse.

Problems to find items stored.

Inventory count discrepancies, physical stock different from

information system data.

Non-real value of stock in the information system.

Out-of-system stocks.

How are your bearings doing?

How are your bearings doing?

How are your bearings doing?

Segment your spare parts portfolio

Service level x locked-in capital

Inventoryvalue

90 % 95 % 98 % 99 % 100 %?

Service level / availability

What items are really important?

What items are really important?

Dominant categoriesC and D are typical forspares parts

On-hand inventory value

Consumed quantity

ABC analysis – on hand inventory value

Value of available inventory

ABC analysis – consumed quantity

In spare parts, C and D categories typically prevail

Quantity

Spare parts inventories segmentation – consumption frequency(in quantity)

Spare parts inventories segmentation – consumption frequency (in value)

WHEN?

HOW MANY?

WHEN?

HOW MANY?

Strategic segmentation of spare parts

CONSIDER CONSIGNATION

CONSIDER CONSIGNATION

CONSIDER CONSIGNATION

CONSIDER CONSIGNATION

BUY

BUY

BUY

BUY

CONSIDER CONSIGNATION

CONSIGNATION

BUY BACK

BUY

TYP

E O

F FO

REC

AST

CONSUMPTION FREQUENCY

Example of buyback application

20 pieces were purchased for turnaround in 2010 for 41.2 M CZK, but these spare parts

were not used during the turnaround and will be stored until the next turnaround in 2014.

Buy-back in this case can save 9 M CZK (360k EUR) on storage and locked-in capital cost

Between shutdowns

Evaluate spare parts criticality

Effects of failure

Production losses

Links to asset register, critical assets (RCM)

Delivery time

Repairability

Number of items in use

Maintenance planning

Part lifespan

Failure probability

Failure characteristics

Failure anticipation

Price

% cost of capital

Cost ofinventory

holdingFailureprobability

Impacts ofspare part unavailability

Leadtime andother

parameters

Spare parts criticality – 4 bits of information

𝐶𝑖𝑛𝑣 = 𝐶𝑢𝑛 ∗ 𝐿𝑇 ∗ 𝑓

10 000 EUR x 10% 100 EUR / day 100 days 1 per 2 years

1 000 EUR 5 000 EUR

KEEP ON STOCK

<

Criticality calculation

INVENTORY HOLDING UNAVAILABILITY LEAD TIME FAILURE RATE

CMMS spare partsmaster data

RCM dataSpare parts

consumptionforecasts

Preliminarysegmentationof spare parts

Quantitativeevaluation of

criticality

Qualitativeevaluation of

criticality

PreviousSP criticalityassessments

(if available)

Cost ofunavailability

(from RCM or other sources)

Planning Wizarddata analysis

CMMS spare partstransactions

data

Assessment by maintenance engineers and

technicians

Potentiallycritical items

Critical items (criticality score)

Non-criticalitems

Non-criticalitems

1

2

2-levelevaluation of criticality

Criticality evaluation

Critical SP Non-critical SP

Intermittentconsumption

Regular consumption

Stock level set byBootstrapping

Longleadtime

Standard modelsof stock

management+ Safety stock

Standard modelsof stock

management

Shortleadtime

Stock level is set based on level of

criticality and quantity of

installed pieces

Stock level is validated by maintenance

technician

Criticality

Consumption frequency

Lead time

Potentially critical SP Non-critical SPPreliminary identification

of potentially criticalitems

Recommended method of stock control (stock level

calculation)

All active spare parts (SP) Spare parts segmentation

For items under Framework contractswith vendors, automated MRP ordering

in ERP can be applied

Qualitative criticality assessment: online app

Login

Login = Příjmení

Heslo = Jméno

Příklad:

tokac miroslav

Selection of items to evaluate

Answering few simple questions

Answering few simple questions, send

Done – items evaluated

Spare parts criticality analysis result

Criticality score

Spare parts items

Simple segmentation: FSN, VED and SDE

39 http://www.yourarticlelibrary.com/business-management/marketing-management-business-management/ved-analysis-sde-analysis-and-fsn-analysis/69363

V

E

D

F

S

N

Fast-moving

Slow-moving

Non-moving

Vital

Essential

Desirable

S

D

E

Scarce

Difficult

Easy

Consumption CriticalityAvailability

on themarket

http://www.yourarticlelibrary.com/business-management/marketing-management-business-management/ved-analysis-sde-analysis-and-fsn-analysis/69363

Spare parts management starts with good forecasting

Quantitative methods x Common sense

Quantitativemethods

Commonsense

MAKE EFFICIENT!MAXIMIZE!

Quantitative methods x Common sense

Quantitative methods

Common sense

Unexplained / Random

Uncertaintyof future

consumption

Maximize

Make efficient

Minimize

Forecasting step-by-step

Visualisation of time seriesFor better understanding of the time series

Calculation of accuracyAbsolute and relative errors, evaluation on testing season

Calculation of forecasts using all available methods

Selection of the best methodBest accuracy and reliability

1

3

2

4

What forecast method is best for spare parts?

1% 1%2%

3%5%

9%

79%

Konstantní model

Regresní model

Holtovo exp. vyrovnání

Jednoduché exp.vyrovnáníKlouzavý průměr

Winters

Forecasting není možný

Constant model

Regression model

Holt’s exp. smoothing

Simple exp. smoothing

Moving average

Winters

Forecasting impossible?

???

Use special forecasting methods for intermittent demand items

Týd

enn

í sp

otř

eby

ND

Historie týdenních spotřeb (týdny)

4 13 17 300

1

2

3

4

81 18 25 2726

32

Spare parts – intermittent demand

Monthly consumption history (months)

Mo

nth

lysp

are

par

tsco

nsu

mp

tio

n (

pie

ces)

QUESTION: What reorder level should be set in order to ensure required availability of a spare part?

Týd

enn

í sp

otř

eby

ND

Historie týdenních spotřeb (týdny)

4 13 17 300

1

2

3

4

81 18 25 2726

32

BootstrappingBootstrapping = random sampling from history of consumptions.

SP consumption for lead-time period is sampled from history

Sample 1: Consumption in

6 months = 5 pcs

Example: SP lead time is

6 months

Monthly consumption history (months)

Mo

nth

lysp

are

par

tsco

nsu

mp

tio

n (

pie

ces)

Týd

enn

í sp

otř

eby

ND

Historie týdenních spotřeb (týdny)

4 13 17 300

1

2

3

4

81 18 25 2726

32

Bootstrapping

Vzorek 2: Spotřeba za

6 týdnů = 0 ks

Sample 2: Consumption in

6 months = 0 pcs

Weekly consumption history (weeks)

Spar

e p

art

con

sum

pti

on

(p

iece

s)

Monthly consumption history (months)

Mo

nth

lysp

are

par

tsco

nsu

mp

tio

n (

pie

ces)

Bootstrapping

Vzorek 3: Spotřeba za

6 týdnů = 12 ks

Týd

enn

í sp

otř

eby

ND

Historie týdenních spotřeb (týdny)

4 13 17 300

1

2

3

4

81 18 25 2726

32

Sample 3: Consumption in

6 months = 12 pcs

Weekly consumption history (weeks)

Wee

kly

SP c

on

sum

pti

on

Monthly consumption history (months)

Mo

nth

lysp

are

par

tsco

nsu

mp

tio

n (

pie

ces)

Bootstrapping

Vzorek 4: Spotřeba za

6 týdnů = 2 ks

Týd

enn

í sp

otř

eby

ND

Historie týdenních spotřeb (týdny)

4 13 17 300

1

2

3

4

81 18 25 2726

32

Sample 4: Consumption in6 months = 2 pcs

Weekly consumption history (weeks)

Wee

kly

SP c

on

sum

pit

on

Monthly consumption history (months)

Mo

nth

lysp

are

par

tsco

nsu

mp

tio

n (

pie

ces)

Če

tno

sti s

po

tře

b v

jed

no

tliv

ých

inte

rva

lech

(z

e s

imu

lace

)

Spotřeba během LT – intervaly (ks)

0 5 10 15

60 000

0

30 000

Ku

mu

lati

vní p

ravd

ěp

od

ob

no

st s

po

tře

by

100 %

Example of 100 000 simulations of SP consumption

Target: SP availability (Service level) = 99%

OPTIMUM INVENTORY = 9 PCS

Consumption during leadtime (pcs)

Cu

mm

ula

tive

pro

bab

ility

of

con

sum

pti

on

Freq

uen

cies

of

con

sum

pti

on

(fro

m s

imu

lati

on

)

Bootstrapping application – a case study

Original inventory: 17 000 EUR(49 pcs)

Spare part lead-time: 32 days

Recommended inventory

29 pcs

10 000 EUR

Savings

7 000 EUR

99.9% availability

Intermittent demand

Minimum level 2 pcs

Life cycle thinking:Consider the whole life cycle of your assets

PROCUREMENT

MAINTENANCE

RENOVATION

COST

PROFIT?PROFIT

MAINTENANCE CREATES VALUE!

ASSET LIFE CYCLE

Asset life cycle (Kari Komonen, EFNMS EAMC)

INVESTMENT UTILIZATION

$$

PROCUREMENT

MAINTENANCE

RENOVATION

COST

PROFIT?PROFIT

MAINTENANCE CREATES VALUE!

ASSET LIFE CYCLE

PROFIT

Efficient spare parts management:

Computers, information systems and technologies will help you!

Efficient spare parts management – 8 rules

Preventive maintenance Smooth SP processes

Segment your SP portfolio Assess criticality

Good forecastingSpecial methods for

intermittent demand items

Life cycle thinkingGood information system

and smart tools

Good information system for spare parts management

Quantitative methods

Common sense

Uncertainty

Maximize!

Make efficient!

Minimize!

ForecastingInventory levels

Ordering

Input of technicians and procurement

Criticality analysis

Forecast accuracyand reliability

Identification of spare parts in smartphone

Even you can have an app in your phone that solves your process or problem.Today it is easy. And cheap.

Forecasting of spare parts consumption with neural networksAI and advanced statistics work for us.

Artificial intelligence is working for us:Diagnostics from acoustic emission using neural networks

Analysis ofdata in place

of origin

Remotediagnostics

https://www.youtube.com/watch?v=yuZtnEZEOxw

Prevention, inspectionand cleaning:Jettyrobot

Even more preventive

maintenance

3D PRINTING OF SPARE PARTS IS REALITY

Today, blades for gasturbines can be printed

Keepspares on printer!

Culture Eats Strategy

For Breakfast,

Innovation For Lunch,

And Transformation

For Dinner

CULTURE STRATEGY

Efficient Spare Parts Management

MAINTENANCE VOLUME

SPARE PARTS INVENTORY

MAINTENANCE VOLUME

SPARE PARTS INVENTORY

Thank youLogio, s.r.o.Evropská 37160 41 Praha 6

Tel +420 731 151 276Email hladik@logio.czLinkedIn: https://www.linkedin.com/in/tomashladik/

www.logio.cz

https://www.linkedin.com/in/tomashladik/