P2 1-oscar lazaro

© SMEs in the Future Internet (FI) Task Force - 2012

Industrial Experiences in Sensing Enterprise Use Case Deployments

FInES Workshop – Panel 2 – The Sensing Enterprise

Aalborg, 09 May 2012

Dr Oscar Lazaro – Innovalia Association

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Agenda

The FASyS Experience.

Lessons Learned.

SMEs pathway towards a Sensing Enterprise Ecosystem.


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THE FASYS EXPERIENCE DEPLOYMENT OF INTEGRATED AND PERSONALISED RISK MANAGEMENT SOLUTIONS IN A SENSING ENTERPRISE


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Background

FASyS – the Spanish acronym for Absolutely Safe and Healthy Factory

FASyS is a 40 month duration project, started in September 2009 with a budget of 23.3 M€.

FASyS involves 13 companies and 11 research centres and universities.

FASyS aims at improving business competitiveness in “human-centric” manufacturing processes through new levels of industrial safety and workplace comfort facilitated by a strong IoT foundation.


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The FASyS concept back in 2009

The knowledge worker and human-centric manufacturing are pillars of new European production models.

But…..

Workforce is aging fast.

Human error is the source of 90% of accidents and incidents in industry.

The impact of error on workers is more severe.

Competitiveness of new industrial models could be compromised from the start.

Technology & prevention models lack the right scope to protect the worker as an strategic asset.


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The Business Challenge

IoT & Sensing Enterprise could be instrumental to achieve the right balance


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The Operational Challenge

There is a need for continuous, proactive, absolute management of security

and health – “factory worker first”.


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The Operational Challenge

Can well-known and emerging hazards be completely managed in an integrated, proactive and continuous manner?


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FASyS – A “caring” manufacturing enterprise


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FASyS – A “caring” manufacturing enterprise A

dvan

ced

Co

mm

mu

nicatio

n

Man

agem

en

t

Acquisition

Location Sensors

Artificial Vision Systems

Sensorised Textiles

Sensorised Machine Tools

Environmental Sensors

Communication

Short-range hybrid sensor networks

Heterogeneous communication

networks

1

Inte

grat

ed

Str

ate

gie

s fo

r R

isk

Pre

ven

tio

n

Risk Management

RR

Personal Health Services

Proactive Risk Management &

Visualisation

Risk Analysis & Identificacion

Decision Support Systems

Tools for Risk Prediction

(Simulation)

DeDe

3

Inte

lige

nt

FASy

S Se

rvic

e

Man

age

me

nt

ºº

2

Risk Characterisation Information Management

Work environment monitoring

Machine Tool Monitoring

Worker activity monitoring

Location services

Health Monitoring

Higine

Ergonomics & Psico-Sociology

Security

Risk A

ctuatio

n Syste

ms

4

Risk Information & Training

Advanced Human Machine Interfaces

Machine Tool – Active Security

Training Systems


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LESSONS LEARNED


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Testing sites – Large Enterprises & SMEs


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Lessons Learned

Technical

Data reliability. Sensor data + acquisition method description.

Data openness. Data is both open and close based on trusted networks and usage context.

Data stream scalability. Data processing should be flexible and distributed.

Reasoning resilience. Resilience to data unavailability, ambiguity, imprecision and error for real system deployment.

Linked knowledge. Knowledge searches for smart objects.

Smart object autonomy. Smart object exhibit “glocal” intelligence.

Smart object morphing. Smart objects may serve purposes beyond those that they were intended for.

Messaging performance. Secure QoS-aware service messaging.


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Lessons Learned

Economic

Business impact assessment methods should focus on effect quantification not technology.

Traditional business processes were initially revisited to exploit sensing enterprise solutions.

New business models could not be pushed. At latter stages new business opportunities naturally emerged from the adoption of new business processes.

Non-technical

Legal framework analysis focused on governance, accountability and liability.

Social framework focused on privacy empowerment and transparency vs. vigilance and scrutiny.


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Lessons Learned – Knowledge dynamics and intelligence

Knowledge should not be an static asset to be searched or found.

Searching for knowledge is a painful and slow experience. Less value

Knowledge is the sensing enterprise “protein”. The enterprise genome.

Knowledge “proteins” in traditional and “new coded” forms must actively attach and modify the behaviour of relevant enterprise objects – smart objects.

Knowledge in continuous and fit motion through the enterprise torrent equals to increased business value generation.


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Lessons Learned – Knowledge dynamics and intelligence


AN

AL

ISIS

D

EC

ISIO

N

AC

TIO

N

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THE ROLE OF SMES IN A SENSING ENTERPRISE ECOSYSTEM


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SME Context

SME activity focus is on medium-term survival.

Business case evaluation for advanced IT solutions is difficult in the SME context.

Lack of control over business environment + limited market share.

SMEs take the dual role of PROSUMER in the FI context

SMEs are trapped in a resource crossroad towards (Future) Internet technology embracement

SMEs are “organic”, responsive, flexible and adaptive and require different managerial approaches for predominantly flat structures


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SME Context

SME as a technology consumer

Sensing enterprise promise increased business opportunities.

Interesting framework to capitalise on SME agility.

Self-x support key to SME adoption

Evolutionary adoption paths preferred to disruptive ones.

SME as s technology & service developer

Sensing enterprise solid framework.

Standardisation on interfaces and description languages required.

Reference technology platforms cannot cover all. Need for customisation.

Niche enablers and advanced services (data managament, data fusion, intelligence services..).


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Acknowledgements

FASyS – Absolutely Safe & Healthy Factory http://www.fasys.es/en/index.php

ComVantage – Collaborative Manufacturing Network for Competitive Advantage http://www.comvantage.eu/

SMEs in the Future Internet Task Force http://www.fines-cluster.eu/fines/jm/FInES-Task-Forces/smes-in-the-future-internet-task-force.html


http://www.fasys.es/en/index.php

http://www.fasys.es/en/index.php

http://www.comvantage.eu/

http://www.comvantage.eu/

http://www.fines-cluster.eu/fines/jm/FInES-Task-Forces/smes-in-the-future-internet-task-force.html




















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Questions

Thank you

Dr Oscar Lazaro

[email protected]

www.innovalia.org


mailto:[email protected]