under uncertainty conditions

CELS

CENTRO DI RICERCA CENTRO DI RICERCA

SULLA LOGISTICA E SUI SERVIZI POST-VENDITA

Managing Supply Chain

Managing Supply Chain

under uncertainty conditions

Sergio Cavalieri Sergio Cavalieri

Università degli Studi di Bergamo

CELS – Research Center on Logistics and After Sales Services

Factors of uncertainty

The case of steel industry

Demand

Global Crude Steel Production: Quarter 1 2009 production of 264

Global Crude Steel Production: Quarter 1 2009 production of 264 million tonnes is 23% below same period 2008. China, with production up 1%, accounts for 48% of output. March 2009 saw highest global output since October 2008.

Trade Levels Tumble: 7 of the top 10 steel exporters have released data to February 2009 Combined January February 2009 exports million tonnes is 23% below same period 2008. China, with production up 1%, accounts for 48% of output. March 2009 saw highest global output since October 2008.

Trade Levels Tumble: 7 of the top 10 steel exporters have released data to February 2009 Combined January February 2009 exports data to February 2009. Combined January-February 2009 exports are down 33% at 19.5 million tonnes compared with same period 2008.

US Imports Sink to 13 Year Low: February 2009 imports of 1.4 million tonnes are the lowest since October 1995. January-February data to February 2009. Combined January-February 2009 exports are down 33% at 19.5 million tonnes compared with same period 2008.

US Imports Sink to 13 Year Low: February 2009 imports of 1.4 million tonnes are the lowest since October 1995. January-February

Prices

Supply

y y

2009 imports at 3.5 million tonnes down 23% on 2008 equivalent

y y

2009 imports at 3.5 million tonnes down 23% on 2008 equivalent

The Bullwhip effect– in theory..

Units/month Customer’s orders

Retailer’s orders +10% +35% Wholesaler’s orders Production +10% -10% -52% 3 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

d i

ti

.. and in practice

T t l B i I t t S l R ti (US C ) Total Business Inventory to Sales Ratio (US Census)

2009

M i

f BWE

Main causes of BWE

Th

i k

d i

The main key drivers

•Requests from the market

•Product customisation

•Uasge of production factors

•Rilocation of production

•Postponement

•Mix policies

Flexibility Reactivity

•Cross-industry perspective

•Partnership and trust with suppliers/customers Visibility Collaborati on •Sell-out vs. sell-in •CPFR practices •Risk sharing •Event co-management •Shared KPIs 6

CELS

RESEARCH CENTER ON LOGISTICS AND AFTER SALES SERVICE

AND AFTER SALES SERVICE

The Experiences of CELS

Sergio Cavalieri

Università degli Studi di Bergamo

CELS – Research Center on Logistics and After

Sales Services

L

ti

Location

CELS is a Research Center operating at the University of Bergamo

Department of Industrial Engineering Department of Industrial Engineering

located in Dalmine

Department of Industrial Engineering

Via Guglielmo Marconi, 5 I-24044 – Dalmine (BG)( )

From Logistics to Supply Chain

From Logistics to Supply Chain

Warehouse Management Warehouse Management Materials Handling Materials Handling Enterprise Integration Enterprise Integration Di ib i & Di ib i & Enterprise Integration Enterprise Integration Distribution & Distribution & Transportation Planning Transportation Planning 9

Supply Chain Integration Supply Chain Integration

& Collaboration & Collaboration

Th V l

Ch i

ti

The Value Chain perspective

- Financing Product

Product--S i

S i P

Financing

- Warranties

- Maintenance

- Spare parts & accessories

Service Service R O D - Technical Assistance - Value-added services - End-of-lifemanagement “ “CoreCore” ” Product Product U C T C C H A II N Supply Chain

Supply Chain Service ChainService Chain

10

Supply Chain

R

h St

Research Streams

Supply Chain

Management

Service Chain

Management

Industrial Asset

Management

Management

• Demand planning • Capacity planning • Demand planning • Capacity planning

Management

• Service Engineering • Service Engineering

Management

• Maintenance strategies • Maintenance strategies • Capacity planning • Risk management in supply chains • Business • Capacity planning • Risk management in supply chains • Business Engineering • Service Logistics • Sustainability issues Engineering • Service Logistics • Sustainability issues strategies • Maintenance Engineering • Prognostics strategies • Maintenance Engineering • Prognostics • Business reference models & PMS for SCs • Role of IT & • Business reference models & PMS for SCs • Role of IT & issues • Business reference models & PMS for service issues

• Business

reference models & PMS for service

Prognostics • Maintenance related services Prognostics • Maintenance related services Role of IT & Embedded technologies in SCs Role of IT & Embedded technologies in SCs

& PMS for service chains

& PMS for service chains

R l

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Roles and responsibilities

Director

Sergio Cavalieri Communication and Secretariat

Francesca Sandionigi

Supply Chain Management

Roberto Pinto

Service Chain Management

Paolo Gaiardelli

Industrial Asset Management

Sergio Cavalieri

Elena Legnani Giuditta Pezzotta Stefano Ierace

Fabiana Pirola Barbara Resta

12

S

l Ch i M

t

Supply Chain Management

Supply Chain

Management

Service Chain

Management

Industrial Asset

Management

Management

• Demand planning • Capacity planning • Demand planning • Capacity planning

Management

• Service Engineering

Management

• Maintenance strategies • Capacity planning • Risk management in supply chains • Business • Capacity planning • Risk management in supply chains • Business Engineering • Service Logistics • Sustainability issues strategies • Maintenance Engineering • Prognostics • Business reference models & PMS for SCs • Role of IT & • Business reference models & PMS for SCs • Role of IT & issues • Business reference models & PMS for service

Prognostics • Maintenance related services Role of IT & Embedded technologies in SCs Role of IT & Embedded technologies in SCs

& PMS for service chains

SCM Area

Main relevant topics

Network

PMS

Network planning

PMS

Demand planning Capacity planning & planning Supply

Chain Risk planning & scheduilng Chain Risk

D

d Pl

i

Demand Planning

Ind strial Research

Ind strial Research

Industrial Research

Industrial Research

• Defining the forecasting process for aftermarket

Defining the forecasting process for aftermarket

products

(in collaboration with Brembo)

• Evaluate spare parts forecast accuracy in the

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(i

ll b

ti

ith

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ti

automotive sector

(in collaboration with automotive

companies)

Academic Research

Academic Research

• Application of ANNs to time series forecasting

• Business intelligence approaches to forecasting and

demand planning

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i

d S h d li

Capacity Planning and Scheduling

Industrial Research

Industrial Research

• Capacity management and scheduling in a manufacturing

company with partial information about orders

(in

company with partial information about orders

(in

collaboration with SAME Deutz-Fahr)

• Capacity management and allocation through critical path

p

y

g

g

p

identification

(in collaboration with Brembo Moto)

• Production order management support system in a

foundry

(in collaboration with Tenaris)

foundry

(in collaboration with Tenaris)

Academic Research

Academic Research

• Use of simulation and constraint-based reasoning in order

promising and scheduling

N t

k Pl

i

Network Planning

Industrial Research

• Production-distribution matrix definition for aftermarket

products

(in collaboration with Brembo)

Fi d th b

t

d

li i

f

di

hi

• Find the best order policies for a vending machine

provider (in collaboration with IVS Group)

Academic Research

• Parts allocation in a network with and without lateral

transshipment

• Distribution network design and planning determinants

• Distribution network design and planning determinants

S

l Ch i Ri k M

t

Supply Chain Risk Management

Industrial Research

• Development of a Portal for the collection promotion

• Development of a Portal for the collection, promotion

and diffusion of news, resources, initiatives and

activities related to the operating risk management of

S

l Ch i

Supply Chains

Academic Research

Academic Research

Q

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i k

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• Quantitative model for risk management (Monte Carlo

simulation, Decision tree, bayesian networks…)

• AHP-based decision support system for supply chain

AHP based decision support system for supply chain

risk assessment and management

SCM Area

Other Projects & Initiatives

BenchLOG

TEXLOG Lab

TEXLOG Lab

B

hLOG

BenchLOG



Benchmarking of logistics and service performance of

industrial supply chains

CELS

h

tl

i

l

d

i

th



CELS

researchers

are

currently

involved

in

the

development

of

the

XCOR

reference

models,

in

collaboration with the Supply Chain Council

pp y

BENCH-LOG

Simulating SC processes

Tipi di processo Tipi di processo Categorie di processo Livello 1 Categorie di processo Livello 1 Livello 2 Livello 2 Livello 3 Livello 3 Decomposizione Processi Livello 4 Decomposizione Processi Livello 4 Decomposizione Elementi di Processo Decomposizione Elementi di Processo 21

BENCH-LOG

Assessing SC performances

The Dasboard The Dasboard Processes and metrics 22

TEXLOG L b

TEXLOG Lab

A Lab for promoting and A Lab for promoting and disseminating innovative practices and technologies in

the textile supply chain

23

pp y industry

Oth

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i

Other past experiences



Multi agent models for coordinated distribution chain



Multi-agent models for coordinated distribution chain

planning



Hybrid Genetic Algorithms for a Multiple-Objective



Hybrid Genetic Algorithms for a Multiple Objective

Scheduling Problem



Coordinated planning models for managing spare parts

Coordinated planning models for managing spare parts

inventory in after sales service



Distributed simulation for Supply Chain Co-ordination

pp y



Development of a performance measurement system for

S

i

Ch i M

t

Service Chain Management

Supply Chain

Management

Service Chain

Management

Industrial Asset

Management

Management

• Demand planning • Capacity planning

Management

• Service Engineering • Service Engineering

Management

• Maintenance strategies • Maintenance strategies • Capacity planning • Risk management in supply chains • Business Engineering • Service Logistics • Sustainability issues Engineering • Service Logistics • Sustainability issues strategies • Maintenance Engineering • Prognostics strategies • Maintenance Engineering • Prognostics • Business reference models & PMS for SCs • Role of IT & issues • Business reference models & PMS for service issues

• Business

reference models & PMS for service

Prognostics • Maintenance related services Prognostics • Maintenance related services Role of IT & Embedded technologies in SCs

& PMS for service chains

& PMS for service chains

The ASAP (After Sales Advanced Planning)

Service Management Forum

Research • Fundamental research • Observatories • Scientific publications Promoting  service culture  and the  excellence in  excellence in  service  management Competence  / Solution  Transfer Training Transfer •Transfer projects •National conferences •Association •Newsletter •Research reports •Technical publications •Website •Workshops 26

ASAP SMF Activities (2003

2005)

ASAP SMF - Activities (2003 – 2005)

SOTA

SOTA -- Strategic assetStrategic asset INDUSTRIAL REPORTSINDUSTRIAL REPORTS

-- SOTASOTA

-- Case studiesCase studies -- Best practicesBest practices

-- Strategic assetStrategic asset

-- Organisation / ProcessesOrganisation / Processes

-- SCMSCM

-- Control SystemsControl Systems

INDUSTRIAL REPORTS INDUSTRIAL REPORTS

–

–AutomotiveAutomotive

–

–White goodsWhite goods Cons mer Electr Cons mer Electr

-- ITIT INDUSTRIAL INDUSTRIAL CONTEXT CONTEXT –

–Consumer Electr.Consumer Electr.

– –IT HWIT HW INDUSTRIAL INDUSTRIAL CASE CASE STUDIES STUDIES CONTEXT CONTEXT ANALSYSIS ANALSYSIS -- SurveySurvey -- ContactsContacts -- BPMBPM

-- Survey toolsSurvey tools

-- questionnairesquestionnaires

CROSS INDUSTRY CROSS INDUSTRY

REPORT REPORT

-- Quantitative AnalysisQuantitative Analysis

-- Cross FertilisationCross Fertilisation

-- Industial dataIndustial data

questionnaires questionnaires -- interviewinterview

-- data gatheringdata gathering

-- Cross FertilisationCross Fertilisation

ASAP SMF – The Industry sections

Academic Board Academic Board Industrial Board Communication & Industrial Board Dissemination Digital Systems

Auto, Moto & Industrial Vehicle

White Goods and Consumer Electronics

Università di Bergamo _{Università di Brescia Università di Firenze}

Machinery

Università di Bergamo

Università Bocconi Università di Brescia Università di Firenze

Politecnico di Milano

ASAP SMF – The Industrial Board

R

h fi ld

Research fields

Service Engineering

-The AS-DfX matrix

Source: Gaiardelli et al. (2008)

31

S

i

E

i

i

Service Engineering

Product Service life cycle Product-Service life cycle

Performance Management Systems

Performance Management Systems

n an ci al R es ult s n an ci al R es ult s ial ts ial ts Ma rk et Cost Fi n _R Ma rk et Cost Fi n _R BUSINESS ERM TIVE k et _st Finan ci Re su lt k et _st Finan ci Re su lt stom er sfa cti o n xi b il it y d uc tivit y stom er sfa cti o n xi b il it y d uc tivit y SHOR T T E PERSPEC T Ma rk Co s Ma rk Co s r _on ty ty r _on ty ty ess

FRONT OFFICE BACK OFFICE

Cu s Sa ti s Fle Pr o d ess

FRONT OFFICE BACK OFFICE

Cu s Sa ti s Fle Pr o d PROCESS S P

FRONT OFFICE BACK OFFICE

Custome r Sa ti sf ac ti o Fl ex ib il it Productivi t

FRONT OFFICE BACK OFFICE

Custome r Sa ti sf ac ti o Fl ex ib il it Productivi t Rel iab il it y Re spo n sive n e In te rn al Le a d T im e Wa st e & Co sts Assets Ut il is at io n Rel iab il it y Re spo n sive n e In te rn al Le a d T im e Wa st e & Co sts Assets Ut il is at io n ACTIVITY

FRONT OFFICE BACK OFFICE FRONT OFFICE BACK OFFICE

R el iab il it y sponsiveness In te rn al L ea d T im e W as te & Costs _Assets U til is at io n R el iab il it y sponsiveness In te rn al L ea d T im e W as te & Costs _Assets U til is at io n

Research & Service Portfolio Human Resources IT & Service Capacity Research & Service Portfolio Human Resources IT & Service Capacity

DEVELOPMENT G TERM PECTIVE

R Re s _L W _U R Re s _L W _U 33 DEVELOPMENT & INNOVATION _LON G PERS P (Gaiardelli et al. 2006)

Aligning AS Service strategic profiles

with performances

(a) Business Generator (b) Cash Generator (c) Brand Fostering

Mapping After Sales Processes

The CCOR project

Supplier My company Customer

Product/Portfolio Management

Product/Portfolio Management Product/Portfolio Management

Supplier My company Customer

Product/Service  Development DCOR™ Sales &  Support CCOR™ Product/Service  Development DCOR™ Sales &  Support CCOR™ Product/Service  Development DCOR™ Sales &  Support CCOR™

Supply Chain SCOR™

Supply Chain SCOR™ Supply Chain SCOR™

cPlan cAssist Contract cContract cSell cRelate 35

The ASSIST Processes

LEVEL 1 ASSISTANCE PROCESS

LEVEL 2 Passive Assist Collaborative Assist ‘Turn Key’ Assist LEVEL 2 Passive-Assist Collaborative-Assist Turn-Key -Assist

Define business model requirements

Receive inquiry/request Receive inquiry/request Receive inquiry/request Authorize request Authorize request Authorize request Route request Route request

R id if Id if l i S h d li

LEVEL 3 ACTIVITIES

Route request to identify solution

Identify solution Scheduling Propose solution Propose solution Identify solution Relea se solution to

customer

Distribute solution Propose solution

Cl R l l i h Ob i i l

Close request Relea se solution to the customer

Obta in ma teria ls or feedba ck

Close request Repa ir product or obta in customer a greement Dispose ma teria ls Cl

' Turn-Key' Assist process :"Repair product or obtain customer agreement"

The process of prepa ring, decomposing the product, repla cing the pa rt a nd re-a ssembling the product. The product is fully opera tiona l upon completion In ca se the request is a re-negotia tion of the a ssist contra ct it

PROCESS PROCESS NAME

Close request

completion. In ca se the request is a re-negotia tion of the a ssist contra ct, it is necessa ry to refine the counter offer within constra ints a nd obta in a greements with the customer

• Annua lized Service Event Rate: n°of service ca lls pe r system per yea r

• Customer Commit Resolution Time met: % of time a customer problem/question is resolved within the a greed upon time

• First Time Fix Ra te: % of time the problem wa s fixed during the first

RELATED METRICS DEFINITION

36

p g

conta ct with the customer

• Repa ir Product Tota l Cost: Process costs. It includes direct a nd indirect cost

An application in a company producing

pp

p

y p

g

heating and cooling systems

I d

t i l A

t M

t

Industrial Asset Management

Supply Chain

Management

Service Chain

Management

Industrial Asset

Management

Management

• Demand planning • Capacity planning

Management

• Service Engineering

Management

• Maintenance strategies • Maintenance strategies • Capacity planning • Risk management in supply chains • Business Engineering • Service Logistics • Sustainability issues strategies • Maintenance Engineering • Prognostics strategies • Maintenance Engineering • Prognostics • Business reference models & PMS for SCs • Role of IT & issues • Business reference models & PMS for service

Prognostics • Maintenance related services Prognostics • Maintenance related services Role of IT & Embedded technologies in SCs

& PMS for service chains

The INTELLIMECH Consortium

INTELLIMECH is one of the first entirely

The INTELLIMECH Consortium

private-held research consortium which aims at representing a benchmark for

innovative – led enterprises, science institutes advanced research and institutes, advanced research and development organizations in the Italian

panorama

It counts 26 enterprises and promotes

pre-competitive projects in the mechatronics field.

The Consortium converts R&D and interdisciplinary experimental activities

i t titi t h l i l

into pre-competitive technological platforms and pre-production prototypes in innovative cross-industry applications,

involving directly the Consortium’s

39

involving directly the Consortium s partners

L

ti

Intellimech is located at KilometroRosso Science & Technology Park

Location

which plays host to companies, research centers, laboratories and

hi-tech manufacturing operations.

The Prophet Project – Aims and Scope

Design of a prognostic platform using methodologies, techniques and innovative instruments related to:

instruments related to:

•capturing of parameters revealing the degradation condition using smart

sensors;

•data storage and processing using specific software tools;g p g g p

•diagnosis of degradation conditions and functional performance forecasting

by means of statistical-mathematical techniques such as soft computing;

•maintenance logistic planning, using decision support tools able to estimate

remaining useful life and perform economical evaluations remaining useful life and perform economical evaluations.

The Prophet Project – Pilot Cases

Development of a Service Portfolio

Starting from historical data, the case study demonstrates

h i i i f h i i i l

the optimization of the preventive maintenance interval, based on reliability analysis and cost evaluation.

Predictive Maintenance

The case study provides techniques for determining the plant / machine health state by electrical signature analysis

f th i t l li ith i t ft

of the equipment supply line, with appropriate software.

Wireless Sensors Network

The case study deals with the use of Wireless Sensors Networks, mainly focusing on Zigbee® _{technology, for} monitoring plant / machine parameters

Development of a Service Portfolio

Development of a Service Portfolio

Fault tree analysis

Identification of optimum preventive maintenance interval, based on reliability analysis and cost evaluation 100%

cost evaluation.

Spare parts optimization in order to guarantee a certain Service Level and spare parts

75,05% 92,69% 98,34% 99,69% 99,95% 99,99% 100,00% 60% 70% 80% 90% 100% 95%

Service Level and spare parts availability 38,29% _36,76% 17,64% 38,29% 20% 30% 40% 50% 5,65% 1,36% 0,26% 0,04% 0,01% 0% 10% 0 1 2 3 4 5 6 7

Predictive maintenance

Predictive maintenance

Actual absorption A in t* Power absorption A Amax absorption A_min A_med Id tifi ti f d e t* Identification of Remaining Useful Life

Power signal shape Active power (kW)

Power (kW) _{Water pressure (MPa)}

Instantaneous power (kVA) Power signal shape Active power (kW)

Power (kW) _{Water pressure (MPa)}

Instantaneous power (kVA) Am

plitu d [VA] P i i d Strokes’ durations Strokes energies

Pressure signal (MPa)

Left stroke Right stroke _{P i i d}

Strokes’ durations Strokes energies

Pressure signal (MPa)

Left stroke Right stroke

Diagnostics based on electrical i t l i

Pumping period Time (s)

Left stroke Right stroke _{Pumping period}

Time (s)

Left stroke Right stroke

Wireless Sensors Net ork

Wireless Sensors Network

Wireless sensors network implementation

Deploy monitoring networks

Recent publications

Recent publications

C

t

t

Contacts

Università degli Studi di Bergamo

Viale Marconi, 5

24044 Dalmine (BG)

Tel. 035-2052384

e-mail:

[email protected]

g

@

g

www.unibg.it/cels

www.progettoasap.org

p g

p

g

www.riskcentral.org