TEMONAS A Technology Strategy& Management Tool TEMONAS Workshop - 22... · Judgments allow to calculate new numerical values ... (Technology Readiness Level, NASA) – MRLn (Manufacturing

TEMONAS

A Technology Strategy & Management Tool

P. Claassen, H. Wancura, F. Montignac, J. Lourenco

Final Workshop, FCH-JU Office, Brussels

May22, 2013

Agenda

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TEMONAS Presentation final Workshop

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Time Title Presenter

09:45 Welcome by the FCH-JU G. Leduc

10:00 Project Introduction by Co-ordinator P. Claassen

10:15 Background & Main Functions H. Wancura

10:45 Coffee Break

11:00 Monitoring & Benchmarking, Data Presentation H. Wancura/A. Nowak

12:15 MCDA F. Montignac/ J Lourenco/ A. Nowak

13:00 Lunch Snack

13:45 Expert Judgment Mapping H. Wancura/A. Nowak

14:30 Data Input H. Wancura/A. Nowak

15:15 Final Discussion & Recommendations All

16:00 End

Project Information

• Project Reference 278.862• Call for Proposals: 2010• Application Area: Cross Cutting• Project Type: Coordination & Support Action• Topic: SP1-JTI-FCH.2010.5.1• Start Date: 01/09/2011• Duration: 18 Months, extended by 3 Months• Project Total Costs: € 1,800,602.00• FCH-JU Funding: € 1,132.046.00• Co-ordinator Details:

Claassen Industrie Management Trading GmbH (CLIMT)A-8054 Graz/Austria, Weizbachweg 33, [email protected]

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Consortium Information

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Partner No. Full Organsisation Name Organisation

Short Name

Country

1

(Coordinator)

Claassen Industrie Management

Trading GmbH

CLIMT AT

2 Planungsgruppe Energie und Technik

GbR

PLANET DE

3 European Fuel Cell Forum AG EFCF CH

4 Commissariat á l‘Energie Atommique

et aux Energies Alternatives

CEA FR

5 Janina Agnieska Swiech-Skiba CSMS PL

6 Bana Consulting Lda. Bana PT

7 synergesis consult.ing Herbert

Wancura

SYN-HW AT

Presentation Structure

• Background• Solutions & Examples• Summary

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• General• Definitions

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Background

Local Zero

Emission Mobility

Renewable

Energy Storage

„Limitless“

mobile Energy

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Decentral

Electricity and

Heat

Next Generation

Power Plants(Ultra High Efficiency)

Urban

Quality of Life

Climate Change

Mitigation

Innovation

Enabling

Regional

Development

Background

General (2)

Background

General (3)

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Background

General (1)

• Management of new technologies is often faced with hype

• Typical for radical new approaches in stable large markets

• Generation of hype is almost „intrinsically powered“

• Need to have a solid analysis and monitoring of new entrants

• So far no commercial tool

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„Gartner Hype Cycle“Based on Fenn and Raskino, 2008

Cit at Bakker and Budde, 2012

Background

Definitions (1)

• Technology Roadmap

– Time dependent

performance expectation

– Includes

• Extrapolation of

performance based on

past/documented RTD

results

• Expert inputs

• Assumptions about

resources

– HYPE Risk !

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Kn

ow

nP

erf

orm

an

ce

Time @

Road map creation

Forecast

Background

Definitions (2)

• Assessment

– Evaluation based on

achieved performance

• Benchmarking

– Evaluation against other

performances

• Targets

• Best in Class (BiC)

• Best Available Technology

(BAT)

• Monitoring

– Time dependent

performance evaluation

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• Basic Concept• IT-Solution• Research Object Definition• Data Quality Workflow• Data Precision/Consistency• Evaluation „Escalation“• Multi Parameter Comparison• Expert Judgment Mapping

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Solutions

Solutions

Basic Concept

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Solution

• Database

• Metholodology

• Functionalities

SolutionsIT-Solution

• Object oriented database

• Client-Server Solution

• Customizable Middleware

• Based on existing solution

already developed by

partner CSMS

• Secure multi-user system

• Database flexible

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Solutions

Research Object Definition

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Program Object Project ObjectCall Object Source Object

Tech

no

log

y

De

scri

pti

on

Ob

ject

Sp

eci

fica

tio

n

Ev

alu

ati

on

Bo

un

da

rie

s TargetPerformance• Technical Metrics

• Economical Metrics

• Environmental Metrics

• Social Metrics

• Safety & Regulation MetricsTarg

et

Ob

ject

Tech

no

log

y

De

scri

pti

on

Ob

ject

Sp

eci

fica

tio

n

Eva

lua

tio

n

Bo

un

da

rie

sObject Performance

• Technical Metrics

• Parameter Group (Attribute)

• Performance Parameter 1

• Performance Parameter 2

• Economical Metrics

• Environmental Metrics

• Social Metrics

• Safety & Regulation Metrics

Re

sea

rch

Ob

ject

Ag

gre

ga

ted

Re

sea

rch

Ob

ject

SolutionsEvaluation Escalation

• Single physical parameter

performance

• Target based (linear)

normalised performance

• Multiple parameter

performance

• Categorized multiple

parameter performance

• Non-linear normalisation

• Multi-criteria assessment

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ExamplesPivot Tables

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ExamplesGraphical Analysis Output

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SolutionsWhy MCDA?• Multiple-criteria decision analysis (MCDA) aims to help

decision making processes in an environment of complexity when several conflicting criteria are to be used to compare two or more alternatives.

• Addressing such problems takes both social and technical approaches:– Social, because at the end of the day a person or a group of

persons are the main actors to whom both the problem and the solution belong,

– Technical because MCDA will rely on procedures and mathematical techniques to solve the problems.

• In order to compare one alternative with another, there is the need to split the main problem into several smaller problems, i.e. there is the need to create a set of criteria that decision makers found to correctly describe the global problem.

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SolutionsMACBETHMACBETH = Measuring Attractiveness by a Categorical Based Evaluation Technique

• MACBETH is a multiple criteria decision analysis method to evaluate options on several criteria based on qualitative comparisons with differences of attractiveness

• Developers of the method : Bana e Costa, C.A., Vansnick, J.C., De Corte, J.M.

• MCDA Software: M-MACBETH

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SolutionsMCDA with MACBETH• 2 Important Functionalities

– Normalisation• Function modeled based on performance

– Qualitative– Quantitative

• Uses minimum 2 „anchoring points“– Acceptable (Higher AP)– Satisfactory/Neutral (Lower AP)

• Model building based on relative ranking and qualitative difference between 2 ranks

– No difference / very weak / weak / moderate / strong / very strong / extreme

– Aggregation• Priorisation via ranking• Weight determination via difference in attractiveness

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ExampleMCDA using MACBETH� Based on a reliable Performance Table, possibility to build a multicriteria model with Macbeth

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• Choice of relevant technical criteria and collection of raw performance data:

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How to compare the technologies based on such multi-

parameter performance table?

ExampleMACBETH (Project StorHy)

Source : Montignac F et al., Multi-criteria

evaluation of on-board hydrogen storage

technologies using the MACBETH approach,

International Journal of Hydrogen Energy

34 (2009) 4561-4568

From raw performances…

….to criteria modelling

• Need to transform technical performances into “value”: use of “reference levels”

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25

• Need to transform technical performances into “value”: implementation

of users’ judgments

Judgments allow to calculate new numerical values


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Performance profiles Global technologies ranking

• Example of results


SolutionsExpert Judgment Mapping• Standardise Expert Input• Use ranking or Likert scales• Evaluate Maturity and or non-technical barriers• Multi-dimensional

– TRL (Technology Readiness Level, NASA)– MRLn (Manufacturing Readiness Level new, modified NASA)– FRL (Framework Readiness Level)

• RCS Status, Know-how Accessibility, Market Access, Fiscal/Taxation Barriers, Financial Accessibility, Industry Coordination)

– DDS (Demand Development Status)• 9 Step Ranking of Product Life Cycle with „Zoom“ of Early Market Phase

– PCL (Policy Congruence Level)• Energy, Environment, Resources, Health/Safety, Industrial

Competitiveness, Transport– MA (Market Attractiveness)

• Market Size, Growth, Interdependency, Price sensitivity, Competitive Intensity

– RCA (Relative Competitive Advantage)• Manufacturer Margin, User TCO, Productivity Access Benefit, Marketing

benefits

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ExamplesExpert Judgment Mapping

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Examples

Expert Judgment Mapping

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RCA

MA

B

C

AC

TRL

PC

L

A

B

C

TRLF

RL

AB

C

TRL

DD

S

A

B

C

TRL

MR

Ln

A

B

C

n

n

Technology „n“

@ Time X

Technology „n“

@ Time X - 3

B B

B

B

A

A A

A

ExamplesData Entry

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SolutionsData Precision/Consistency

• Precision Solution

– Exact value

– Imprecise numbers need a MIN/MAX range from RA

• Consistency

– Ontological concept of attributes

• Implementation via “parameter groups”

• One attribute may have a number of parameters

• Normalisation relative to respective target enables comparison as “achievement level”

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SolutionsData Quality Workflow• Every Data record has a „Responsible Analyst“ (RA,

data owner)• New data entry requires authorisation by the RA

– Process is fully IT supported (e-mail, sms, etc.)– As all records also contain the source file

• backchecking is simple

– RA may initiate an external verification/validation with workflow support from the system

– RA may also initiate an up/downgrading of data quality rating (necessitates protocol)

• All data entries/changes etc. are logged and a history file is available

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• Summary

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Summary

Summary & OutlookSummary

• TEMONAS is a output oriented planning and controlling tool for technology management

• A set of methodologies for technology monitoring and analysis was developed/selected addressing the issues of early stage technology.

• The methodology is implemented in an integrated IT tool.

• The tool is currently being launched with the FCH-JU and ready to be adapted/ applied to other client needs.

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Acknowledgements

This project was funded by the European Union using FP7 funds via the Fuel Cell and Hydrogen Joint Undertaking (FCH-JU), Grant Agreement 278.862. The support of the FCH-JU is gratefully acknowledged.

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Herbert Wancurasynergesis consult.ingA-8053 Graz / Austria, Puschweg [email protected]

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Contact

More information: www.temonas.eu

Documents

TEMONAS A Technology Strategy& Management Tool TEMONAS Workshop - 22... · Judgments allow to calculate new numerical values ... (Technology Readiness Level, NASA) – MRLn (Manufacturing