Multi-mitigation scenarios of maritime

disruptions in a wheat supply chain

AMC SEMINAR SERIES, 8th APRIL 2010

SAUT GURNING

What is maritime disruption ?

Supply-Chain Risks

Uncertainties Disturbances

Delay Deviation Disruption Disaster

Related to risks as Disruption Risks

Clausen et al.(2001a,

p. 41)

“A state during the execution of the current

operation, where the deviation from plan is

sufficiently large that the plan has to be

changed substantially”.

Yu and Gi (2004)

“Various unanticipated events caused by

internal and external factors which significantly

deviate original plans of a system and

consequently affect its performance severely”

Events in Supply Chain as Supply Chain Disruption

Craighead et al. (2007,

p.132)

“Unplanned and unanticipated events that

disrupt the normal flow of goods and materials

within a supply chain and, as a consequence,

expose firms within the supply chain to

operational and financial risks”.

Disruptions in Maritime

Bearing-Point &

Hewlett-Packard

(2005, p.2)

“The maritime industry is directly

impacted by a variety of disruptions

to the flow of legitimate trade and

travel. These range from minor

weather disruptions to hurricanes

and typhoons, from workforce

shortages to work stoppages and

from security breaches to potential

Terrorist attacks”.

ImpactFrequency

DirectIndirect

MajorMinor

Summary of factors identified in major studies as causes of maritime disruptions

Ak

aha

198

6

Rose

et

al.

199

7

Chan

g 2

000

Ram

age

200

1

Wata

nabe

200

2

Conn

olly

200

4

Ale

xan

der

and I

rwin

2005

Bea

rin

gP

oin

t 2

005

Chu a

nd

Hans

en 2

005

Coy

et

al.

200

5

Davi

s e

t al

200

5

Earl

y-W

arn

ing 2

00

5

Fritt

elli

200

5

Kle

indorf

er

and

Saa

d 2

005

Arn

old

et

al.

2006

CS

A 2

00

6

Shu

ltz 2

00

6

Auc

klan

d 2

007

Bu

sine

ss L

ine 2

007

CB

C 2

00

7

Con

rad e

t al 2

007

Dru

m 2

007

Hege

r 200

7

Mahb

ub 2

007

Pe

ttit

200

7

Reute

rs 2

00

7

Yan

k 2

007

Bro

wn

200

8

Gurn

ing 2

008

Horl

ock

200

8

Robe

rt 2

00

8

Said

i 200

8

Seb

a 2

00

8

Str

atfor

200

8

Todd

200

8

Tsu

kim

ori

and

Juk

wey

200

8

Wrig

ht

200

8

Nig

hti

ngale

, 20

08

NO Disruptive Events

1 Security issues • • • •

2 Political events • • •

3 Rail related operation • •

4 Port strikes • • • • • • • •

5 Customs & administration • • •

6 Severe weather condition • • • • • • • • • • • •

7 Earthquakes • • • •

8 Electrical outages • •

9 Equipment down / shortage • •

10 Empty containers •

11 Ship accidents in port areas • • •

12 Shipping-Port disputes •

13 Port congestion • • • •

14 Ship shortages • • •

15 Fuel and bunkering Costs •

16 Inland accesibilty problems • •

17 Telecomunication system •

18 Shortage of service demand •

Researchers and Factors Identified / Discussed

Maritime Disruptions and its impacts

TYPE OF MARITIME DISRUPTION RISKS

DIRECT INDIRECTSecurity and safety Market

- Ship accidents - Shortage of Demand

- Ship pollution - Shortage of ships

- Political events - Financial Crisis

- Terrorist attack - Trade imbalance

Service related factors Organisation and relationship

- Operational and equipment - Employment / Port Workers

- Competition - Legal and policy

- Fuel and bunkering - Resource

- Electrical shortage - Customs process

- Congestion - Ships inspection

- Infrastructure related factors Environmental

- Communication facility - Severe weather

- Lack of development - Earthquakes

- Inland transport connections - Flood

Security and safety

- Ship accidents- Security and safety- Political events

Environment

- Severe weather- Earthquake- Tsunami- Pollution

Infrastructure

- Lack of rail facilities- Lack of inland access- Communication facility- Equipment breakdown- Electrical outages

Market

- Uncertain bunkering

- Shortage of dry bulk ships

- Imbalance traffic / Insufficient empty containers

Organisation

- Port strikes- Slow customs and quarantine- Shipping port disputes- Shipment contract

Access to loaders

- Competition - Terminal selection- Service preference

Collective risk

- Propagating risk- Supply chain

performance- Limited coordination

Leadership risk

- Risk perception and experiences- Information on supply chain flows- Risk culture and practices- Lack of collaborations with community

and supply chain entities

Delay Deviation Stoppage Destruction

Instigating factors

Inte

rdep

end

ent

fact

ors

Progressive factors

Maritime disruption risk

Impact of maritime disruptionsin the Australian-Indonesian

wheat supply chain

WHEAT SUPPLY CHAIN IN AUSTRALIA AND INDONESIA

Farmers Handlers Processors Distributors

Sub

Wholesalers Retailers Consumers

Farm Scale

Southern-Belt

Wheat Area

High Rain Fall

Special Area

AWB Limited

Grain Pool

Agra-Corp

Premium

Grain

Brooks Grain

ABB

Mortons

Aus-Wheat

Millers For

Animal

Feeds

Millers For

Human

Foods

Processors

For

Beverage

Processors

For Ethanol /

Bio-Fuel

Industrial

Consumers

Big Industry

Small

Medium

Enterprise

Household

End

Consumer

Export

Markets

Domestic

Markets

Agents

Marketers

Freight

Forwarders

Storage and

Handling

Global Supply Chain Networking

National and Local Wholesalers and

Retailers Chains

Food Retail Services and Small Shops

Wholesalers

Third Party Suppliers

AUSTRALIAN-INDONESIAN WHEAT SUPPLY-CHAIN AS A CASE

Global and common wheat chain as

research perspective and objective

Farmers Handlers Processors

Maritime Distributors

& Handling

Wholesalers Retailers Consumers

Shipping

Ports

Forwarders

Shippers

Consignees

Tim

e, costs

, volu

mes

Tim

e, costs

, volu

mes

Tim

e, costs

, volu

mes

Tim

e, costs

, volu

mes

Tim

e, costs

, volu

mes

Tim

e, costs

, volu

mes

Effecting Factors / Affecting issues on three layers of upstream chain

Focal PointFocal Point

Effecting Factors / Affecting issues on three layers of downstream

Disruption MitigationOther trade chain Maritime Disruption Model

Maritime disruptions in the Australia-Indonesia wheat supply chain

In Australia

Drought

Insufficient

Rail-linkage

Queuing and

Congestion

at ports

Limited draught

at ports

Shortage of

Containers

Imbalance market

of global dry bulk

fleet over the

demand

Temporary change

from dry-bulk to

containerised

Inland Congestion

Port Congestion

Problems with Inter-Island networks

Lack of inland

accessibility

Higher costs and

longer time

Lack of terminal storages, limited draught of

berth, higher terminal charge, exhausted

customs’ procedures

Severe wave and wind in

ocean environment

Stoppage of ferry /

domestic services to

Inter-island points

Contribute to

Higher price 38-76

per cent of 250-

260 percent of

total selling price

Longer lead time

maximum 30 days

In Indonesia

T rend of F OB and C &F P ric e of Wheat from Aus tralia to Indones ia

227 235 224212 219

231

264

341 345 349

384

422

464

434460

474500

530552

170

350

325

302

288273251243

212

0

100

200

300

400

500

600

1/1/200

6

2/1/200

6

3/1/200

6

4/1/200

6

5/1/200

6

6/1/200

6

7/1/200

6

8/1/200

6

9/1/200

6

10/1/2

006

11/1/2

006

12/1/2

006

1/1/200

7

2/1/200

7

3/1/200

7

4/1/200

7

5/1/200

7

6/1/200

7

7/1/200

7

8/1/200

7

9/1/200

7

10/1/2

007

11/1/2

007

12/1/2

007

1/1/200

8

2/1/200

8

US

Do

lla

r P

er t

on

F OB

C NF

Natural problems

Demand Factor

+ diversificationSea transport gap

Maritime

Disruptions

More Findings in The Australian-Indonesian Wheat Supply Chain

MARITIME DISRUPTION STUDY 2009 BY TELEPHONE SURVEY

Wheat Supply Chain Risks

21.4%

5.4%

8.9%10.7%

33.9%

14.3%

1.8%

Market Legal Technical Environmental Operational Financial Security

Which of the following risks best describe any severe disruptions in the

international supply chain of your wheat trade in the last two years?

Perceptions on Maritime Disruption

24.6%

22.8%

10.5%

24.6%

10.5%

7.0%

Interruptions Disturbances Stoppages Delays Deviations Disruptions

In general, a disruption may relate to a service in your supply chain being

unavailable. What terminology does your organisation use to refer to this type

of risk?

POSSIBLE CAUSES OF PORT CONGESTION

4

5

8

3

7

6

1

3

8

9

4

5

2

6

7

1

2

3

4

6

1

2

3

5

Ships High Wind Power failure

Accidents

Lack of pilotage Heavy snow

Service & tug-boat and rain

Clearance of

Medical &

Quarantine Checks

Port Strikes / Immigration

Labor shortage

Downstream

intermodal

problems

Ships shortage Cranes Disabled

Hazardous Spill Straddle Carriers

In shops

Low tide level Shortage of chassis Cargo verified Customs

to work vessel By customs Clearance

Severe WaveShip’s Fire Accident Lack of

Roads,

bridges &

Access lanesEarthquake

Shortage of handling Overloaded

equipments Container area

Disruption before Disruption Disruption at Disruption

at Port platform

Disruption

to port SCM

networkPort Channel in waterways Port Berth

Problems in

nearby port

Coast guard

delaying

boarding and

clearance

II (PORT CHANNEL) III (BERTHING AREA) IV (PORT YARD)

2

4

5

8

3

7

6

1

3

8

9

4

5

2

6

7

1

2

3Process

4Terminal & port

Computer system

Crash / down

5

1

4

Flooding

I (PORT

Disruption

at Port inland

access

V (ADM PROCESS) VI (INLAND)

Subjective Risk Profile

CONSEQUENCES

DISRUPTION RISK PROFILE

HIGH DISRUPTION RISK EVENTS

EA Earthquake

PC Port congestion

EB Equipment breakdown

MEDIUM DISRUPTION RISK EVENTS

EC Empty containers

IA Inland accessibility

CQ Customs and quarantine

SD Shortage of dry bulk ships

SDP Shipping disputes

SW Severe weather

CLN Cleanliness

RF Rail facilities

LOW DISRUPTION RISK EVENTS

BS Bunkering supplies

CF Communication failure

EO Electrical outages

PE Political events

PS Port strikes

SA Ship accidents

SS Shortage of shipping services

ST Security threats

TS Tsunami

Makassar

Banjarmasin

Surabaya

Jakarta

Singapore/Malaysia

Medan

Brisbane

Sydney

MelbourneAdelaide

Perth

Main shipping route

Feeder route to Indonesia

Banjarmasin

Semarang

Singapore/Malaysia

Medan

Brisbane

MelbourneAdelaide

Perth

Main shipping route

Feeder route to Indonesia

MacKay

Gladstone

Newcastle

Kembla

Thevenard Gile

s

Portlan

d

Geelon

g

Albany

Kwinana

Geraldton

Esperance

Less than 10%

10% - 25%

25% < x < 50%

More than 50%

Subjective port risk

index

Disruption cycles from the case

Finding of Disruption Stages(Blackhurst et al. 2004; Zsidisin et.al 2006; Yu and Qi 2008)

Time

Ser

vice

var

iab

el

det

erio

rati

on

Delay Deviation Disruption Disaster

Flat zonal rate

Sacrificing Phase

D2

D1

D3

D5

A PORT CONGESTION CASE DUE TO EQUIPMENT

BREAKDOWN (Port Manager, Respondent #0901)

Handling

Equipment

Breakdown

Delay discovery

Period

in days

Deviation of

handling

availability level

Unavailability of dominant

handling services

Initial recovery

01 5 19 36

Full recovery

90

Reparations

Parts ordering

Dominant (70%)

available

equipments failed

22

Ordering & transporting

back up equipment

Back up equipment

started operating

38 60

Retrofitting and replacement process of

handling equipment

Intermediate recovery, 70% of equipment ready

62

Collaboration with port users and partners

A CASE OF PORT STOPPAGE DUE TO SEVERE

WEATHER (Port Manager, Respondent #0925)

Severe weather

in navigational

area

Delay discovery

Period

in hours

Deviation of

services for ships

Initial recovery

30% of port

facilities ready

0 6 12 24 36

Full recovery

90

Limit the clearance of ships

Received Navigational Warnings

Port stoppage

27

Normal weather

confirmation

48

Intermediate recovery, 60% of facility ready

60

Coordination with stevedores, ships’ operators, unloading operators , and truck drivers

PORT DISRUPTION DUE TO EARTHQUAKE,

(Port General Manager, respondent #0929)

Earthquake

Discovery

Period in Days

Unavailability of

port facilities

Initial recovery

30% facilities ready

01 15 22 55

Full recovery (100%)

907

60% damage of port facilities

Finding back-up supports

8

Dominant ships’ re-routing

Provide temporary facilities

62

Provide new

Operational

procedures

Port facility restorations

Coordination and collaboration among

port authorities and port communities

DISRUPTION DUE TO SHORTAGE OF DRY BULK SHIPS,

Shipping Manager, Respondent# 0912

Shortage

of dry bulk

ships

Discovery

reported by partners

Period in Days

Additional shipment

delay to loading port

Initial recovery

Intermediate recovery

0 7 14 22 50

Full recovery

Higher freightTop up inventory

at loading ports

Rerouting to other

Unloading ports

30

Revise shipment contract

with third / four party logistics

Fix the shipment process

either by dry bulk or containerised

75

Return to unloading ports

assigned by buyers

80

Process to be considered

Time

Delay Deviation

Disruption

Disaster

Discovery

Point

Response

Point

Recovery

Point

Reposition

Point

Impacts

How to prepare responses and preparedness

as mitigation process

RESPONSE ON MARITIME DISRUPTIONSGRAIN CONTAINERISED, Early 2008

Container (TEU)

Bulk (20 tons)

0

500

1000

1500

2000

2500

3000

3500

4000

Bela

wan

Pri

ok

Pera

k

Tj E

mas

Bari

to

Makassar

Cost (US$)

Container (TEU)

Bulk (20 tons)

Farmers Collectors/polls/millers Millers Consumers

3P/L as maritime Distributors and handling(Shipping, ports, freight

forwarders)

FourthParty logistics /

4PL

Upstream Entities

Downstream Entities

3P/L as maritime Distributors and handling(Shipping, ports, freight

forwarders)

RESPONSE ON MARITIME DISRUPTIONSRELYING ON 3P/L OR 4/PL ON LOADING ACCESSIBILITY

Supply flexibility

ReservesRoutes

Implicationmonitoring

DevelopWarningsystem

Network & procedures

redesign

CriticalNodes

Mapping

Formal Assessment

MaximumAllowable

Interruptions

ChangesTo working

practices

Inventory polling at

ports

Apply other Chain links

Postponementdelays

Applying Recovering

actions

Risks Based

Budgeting

Insurancearrangement

OptimumOrdering

policy

Utilisingagencyservice

BY LITERATURES

UtiliseChain

coordination

ContingencyPlans

PRE-DISRUPTIONS ON-DISRUPTIONS POST-DISRUPTIONS

Supply flexibility

ReservesRoutes

Implicationmonitoring

Re-evaluatingContingency

plansContingencyPlans

ChangesTo working

practices

Inventory polling at

ports

Applying Recovering

actions

Insurancearrangement

OptimumOrdering

policy

Utilisingagencyservice

Control access to

load

BY SURVEY

PRE-DISRUPTIONS ON-DISRUPTIONS POST-DISRUPTIONS

MITIGATION IN RESPONSES

Always Often Sometimes Never UnsureNot

applicableAverage

(45%) 9 (19%) 6 39% (12) (13%) 4 (0%) 0 (0%) 0 5

(16%) 5 (45%) 14 (45%) 9 (10%) 3 (0%) 0 (0%) 0 5

(6%) 2 (26%) 8 (39%) 12 (23%) 7 (6%) 2 (0%) 0 4

(16%) 5 (19%) 6 (23%) 7 (32%) 10 (10%) 3 (0%) 0 4

(13%) 4 (19%) 6 (23%) 7 (39%) 12 (6%) 2 (0%) 0 4

(13%) 4 (45%) 9 (32%) 10 (16%) 5 (10%) 3 (0%) 0 4

(13%) 4 (16%) 5 (42%) 13 (16%) 5 (13%) 4 (0%) 0 4

(13%) 4 (10%) 3 (35%) 11 (39%) 12 (3%) 1 (0%) 0 4

(10%) 3 (16%) 5 (23%) 7 (35%) 11 (13%) 4 (0%) 0 4

(13%) 4 (26%) 8 (23%) 7 (32%) 10 (6%) 2 (0%) 0 4

(16%) 5 (23%) 7 (35%) 11 (13%) 4 (13%) 4 (0%) 0 4

General mitigation responses

Rescheduling the shipment process

Increase some inventories at loading/unloading ports

Utilise supply alliance networks in order to have a flexible

Employing economic supply incentives

Apply flexible rerouting to other ports

Real-time decision support

A redundancy system which includes risk detection and

Controlling product exposure to customers

An effective and strong coordination with other players

Business continuity plan in operation/services

Bottom up approach to set up the mitigation plan

FACTORS IN MANAGING DISRUPTIONS

t Stat ρ two tail Mean

-1.372 0.242* 4.9 / Agree

-1.647 0.175* 4.7 / Agree

-1.719 0.161* 4.6 / Agree

-1.324 0.256* 4.6 / Agree

-2.201 0.093* 4.4 / Agree

-3.096 0.036 4.3 / Agree

-3.068 0.037 4.3 / Agree

-2.202 0.092* 4.1 / Agree

-1.744 0.156* 4.1 / Agree

-3.508 0.025 3.6 / Unsure

-1.909 0.129* 2.9 / Disgaree

-3.068 0.037 2.9 / Disagree

ISPS code reduces maritime security threats

Your organisation always uses a contingency plan

Rail service supports your service appropriately

Labour strikes have occurred in your organisation

Customs and quarantine agencies are inactive in

reducing longer and costly processess

Applying a good repositioning plan for empty containers

A flexible transport arrangement in wheat supply chain

Your organisation is employing a back up system for bunkering supplies

Your organisation is adopting a reliable maintenance and repair system

Improving port capacity is the best way to deal with port congestion

Your organisation is implementing a risk sharing plan

with your business partners when disruptive events occur

Your organisation prepared a pre-disaster plan

for natural disasters that may impact on your facilties

Factor in managing maritime disruptions

THE RELEVANCE OF STRATEGIES

Cf SD Cf SD Cf SD Cf SD Cf SD Cf SD Cf SD

0.50 0.5 0.05 0.5 0.05 0.4 0.07 0.5 0.04 0.5 0.09 0.6 0.08 0.6 0.05

0.40 0.4 0.03 0.4 0.03 0.5 0.03 0.4 0.03 0.5 0.03 0.3 0.03 0.3 0.07

0.40 0.4 0.06 0.5 0.06 0.5 0.06 0.5 0.06 0.5 0.06 0.3 0.04 0.3 0.06

0.90 0.9 0.07 0.9 0.07 0.9 0.06 0.9 0.05 0.9 0.05 0.9 0.07 0.9 0.08

0.90 0.9 0.07 0.9 0.07 0.9 0.05 0.9 0.07 0.9 0.07 0.9 0.08 0.9 0.07

0.80 0.7 0.05 0.7 0.05 0.9 0.05 0.8 0.05 0.9 0.05 0.8 0.05 0.8 0.05

0.80 0.7 0.04 0.8 0.04 0.9 0.04 0.9 0.04 0.8 0.06 0.8 0.04 0.8 0.04

0.80 0.8 0.03 0.7 0.03 0.7 0.02 0.7 0.03 0.8 0.03 0.9 0.06 0.9 0.06

0.80 0.7 0.03 0.7 0.03 0.8 0.03 0.7 0.03 0.8 0.05 0.9 0.03 0.9 0.06

0.60 N/A - 0.6 - 0.6 - 0.7 - 0.6 - 0.7 - 0.7 -

0.50 0.6 0.05 0.5 0.05 0.5 0.05 0.7 0.05 0.5 0.05 0.5 0.05 0.5 0.05

0.30 0.4 0.05 0.3 0.05 0.3 0.04 0.5 0.05 0.3 0.02 0.3 0.04 0.3 0.04

0.20 0.3 0.06 0.2 0.06 0.2 0.06 0.3 0.06 0.2 0.06 0.2 0.06 0.2 0.06

0.20 0.3 0.06 0.2 0.06 0.2 0.05 0.3 0.06 0.2 0.04 0.2 0.07 0.2 0.08

0.90 0.9 0.06 0.8 0.06 0.9 0.06 0.8 0.06 0.9 0.05 0.9 0.06 0.9 0.08

0.90 0.9 0.07 0.9 0.07 0.9 0.05 0.8 0.07 0.9 0.07 0.9 0.07 0.9 0.07

0.90 0.7 0.05 0.9 0.05 0.9 0.06 0.9 0.05 0.9 0.08 0.9 0.08 0.9 0.06

0.80 0.8 0.04 0.8 0.04 0.9 0.04 0.9 0.04 0.8 0.04 0.8 0.04 0.8 0.04

0.80 0.9 0.06 0.8 0.06 0.8 0.07 0.8 0.06 0.9 0.05 0.7 0.05 0.7 0.06

0.50 0.5 0.07 0.5 0.07 0.6 0.07 0.6 0.07 0.5 0.07 0.5 0.07 0.5 0.07

Active response of custom and quarantine agency

Reposition plan for empty containers

Farmers Handlers

Correlation factors

Processors

All stages along the chain have an equal risk probability to probability suffer from maritime disruptions

ConsumersWholesalers RetailersMarOpr

A flexible transport arrangement in supply chain

Better human resource management

Back up system for bunkering supplies

Maintenance and repair system

Rail services

All stages along the chain have an equal risk probability create maritime disruptions

Stages prior to maritime service (such as handlers)

Contribution of stages to maritime disruptions

Contingency plan

Improving port capacity and facility

Pre-disaster / emergency plan

Risk sharing plan

Select the shipping companies

Substitute additional shipping costs

Arrrange the selection of loading/unloading terminals

Reactions General

Factor in managing maritime disruptions

Strategies to deal with third or fourth party logistics

Negotiate the wheat selling prices

Arrange the shipping contract including its risks

Arrange the inland transport arrangements

Role of 3P/L & 4P/L andCommercial impacts

t Stat ρ two tail Average rating

-2.331 0.08* 5.1 / Strongly Agree

-1.759 0.153* 4.6 / Agree

-3.559 0.024 4.3 / Agree

-2.484 0.068* 4.3/Agree

-2.449 0.07* 4.2 / Agree

-2.915 0.004 4.1 / Agree

-3.302 0.030 3.9 / UnsureDecide the freight level of shipping arrangements

Arrange the shipping contract including its risks

Decide the selling prices of raw wheat

Consider and collaborate with the export agency

Select the shipping companies

Arrange the inland transport arrangements

Arrange the selection of loading/unloading

The role of third and fourth party logistics

N Correlation Standard

factors Deviation

34 0.99 0.06

34 0.98 0.08

34 0.96 0.05

34 0.95 0.07

34 0.80 0.07

34 0.78 0.04

34 0.72 0.06

34 0.27 0.06

The commercial impacts of maritime disruptions

Business uncertainty due to discrepancies in maritime transport costs

Higher wheat retailers’ prices

Supply chain performances

Market

Operational processes / services

Revenue losses (from buyers to sellers) due to the decreasing of traffic

Poor business reputation due to unreliable services

Supply guarantee (buyers deciding to explore other sources)

Higher emergency costs due to immediate responses taken

Lower tariff and higher costs in order to attract customers back

Risk of permanent stoppages of cargo delivery processes

Recommendations

Logical Process of Maritime Disruptions on Wheat-Trade

Natural Hazard

Operational

Maritime Disruption

Management

Model

Discovery

Basic drivers Stages

Goals

Industry

Characteristics

Disparities

between trade

Pre-Disruptions

Environment

Wheat Chain

Structure

Maritime

Operations

Existing Practices

Of SC operators

Market / Economics

Development

Initial reactions

Response group/

Chain responses

Options available

Decision made

Recovery

Performance

Wheat-Chain

Redesign

Readiness /

Mitigation

MARKOV CHAIN APPROACH

Uncertainties

Contingency Planning

Stochastic Models

Robust Optimisation

Pure Rescheduling

Disruption Management

Real-time Responses

Deviation Costs

Multi-criteria (states) decision

making

Returning to Original Plan

Multiple Solutions

Partial Solutions

Markov Chain Approach

• Risk-state definition

• Disruption-state

transition matrix

• Initial mitigation scenario

• Expected frequencies

and probabilities

Body of Knowledge Methodology Approach

41

Markov Decision Processes (MDPs)for estimating probabilities

• MDPs is a decision-theoretic planning and learning problems.

• An MDP is a model M = < S, A, T, R > consisting

a set of environment states S,

a set of actions A,

a transition function T: S A S [0,1]

T(s,a,s’) = Pr (s’| s,a),

a reward function R: S A R .

• A policy is a function : S A.

• Expected cumulative reward -- value function V: S R .

The Bellman Eq.: V(s) = R(s, (s)) + s’T(s, (s),s’) V(s’)

Transition matrix of wheat supply chain and maritime operations

Note:

Far : farmers; Ashp: Shipping operations in AustraliaIndonesiaan: handlers; Iprt : Ports in Indonesia; Proc: processor; Ifwr : forwarders in Indonesia, Aspr: shippers; Cos : Consignees; Afwr: Forwarders in Australia; Whl : Wholesalers; Aprt: Ports in Australia; Rtl : Retailers; Ashp: Shipping operations in Australia, Fcon : Final consumers

Transition the probabilities matrix of the disruptions wheat supply chain networks

Detailed process of wheat chain

and Its risk interactions

Layer of Disruptions and Consequences

Stimulators

Consequences

1st Layer

Disruptions

2nd Layer

Disruptions

• Security threats

• Political riots or/and

war

• Lack of port facilities

• Lack of HRD

management

• Long customs

process

• Quarantine process

• Severe weather

states

• Tsunami

• Earthquakes

• Electrical outages

• Lack of maintenance

• Shortage of ships

• Unreliable service

level

• Lack of navigation

equipment

• Insufficient of empty

containers

• Uncertain fuel costs

• Communication

failure

• Lack of inland

accessibility

• Congestion

• Shortage of

port services

• Slow and

cancellation of

service

deliveries

• Limited

shipping

services

• Disputes

between port

operators and

shipping

companies

• Lower

handling

capacity

• Ship’s

accident

• Port strikes

• Recurrent

interruptions

• Delays

• Deviations

• Unavailability

of services

such as port

and/or

shipping

services

• Higher

transport costs

• Longer

delivery time

• Cargo rerouting

• Poor reputation

• Higher logistics

costs

• Loss of business

profit

• Higher commodity

price

• Loss of trade

competition

• Loss of economic

benefit

Using enumerative

approach to

structure maritime

disruptive

propagation units

PROPAGATION EFFECTS CLASSIFICATION

CLASSIFICATION CHARACTER DEFINITION OF THE TYPE

TYPE I Internal Occurring within the boundaries of maritime entities

(Scope) where the disruptive risks propagate

External Occurring outside the maritime boundaries where

the disruptive events propagate as a direct

or indirect result

TYPE II Direct Occurring as a direct impact of the previous

(Consequences) disruptive event

Indirect Occurring as an indirect impact of a preceding

disruptive event

TYPE III Delay Occurring with a delay effect from its operational targets

(Character) Deviation Occurring with a deviation effect from original plans

Disruption Occurring with unavailability of dominant services

TYPE IV Serial Occurring as one of several simultaneous impact links

(Process) of interruptive chain caused by preceding events

Parallel Occurring as one of several simultaneous impact links

of interruptive chain caused by preceding events

NormalState

μ0

Event 1

Event 2

Internalstages

.

.

.

Event n

- Single mitigation , λ1- Multi-mitigations:

λ1 + λ2+… λn

Possible Disruptiveevents

- Single mitigation , λ2- Multi-mitigations:

λ1 + λ2+… λn

- Single mitigation , λ3- Multi-mitigations:

λ1 + λ2+… λn

Transition Matrix of Disruption States

Disruption-states: S → 2T, a function mapping each state S

1414143142141

314333231

214232221

114131211

...

............

....

...

...

PPPP

P

PPPP

PPPP

PPPP

ij

P =

where , ,…, . That is, , i =1,2,…n

n

j

jP1

1 1

n

j

jP1

2 1

n

j

njP1

1

n

j

ijP1

1

Initial Probabilities ( π Vector of Mitigating Plans)

Initial Probability vector

P ( S1 S2 … Sk …. Sn ) = P

Disruption occurence

F =

Where α, β, γ, and δ represent the number of disruption occurrence for each state S1, S2, Sk, and Sn respectively

)............(FFFF

......1

ifn

i

1)(1

n

i

iSP

Prediction of Disruptions

P (S1 S2 … Sk …. Sn ) = P ( S1 S2 …Sk ...Sn )

1414143142141

314333231

214232221

114131211

...

............

....

...

...

PPPP

P

PPPP

PPPP

PPPP

ij

Probability Disruption Occurence

Expected Frequencies

)()..(1

i

n

i

i SMSP

EF =

The future probability and frequency can be estimated by using using the

transition matrix created and the initial probability vector below.

The Expected Frequency (EF) of threat-occurrence can be estimated using the

probability of disruption-occurrence and the median for each disruption-state

MARKOV CHAIN APPROACH

Uncertainties

Contingency Planning

Stochastic Models

Robust Optimisation

Pure Rescheduling

Disruption Management

Real-time Responses

Deviation Costs

Multi-criteria (states) decision

making

Returning to Original Plan

Multiple Solutions

Partial Solutions

Markov Chain Approach

• Risk-state definition

• Disruption-state

transition matrix

• Initial mitigation scenario

• Expected frequencies

and probabilities

Body of Knowledge Methodology Approach