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PROMISE

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PROMISE Product Lifecycle Management and Information Tracking using Smart Embedded Systems EU FP6 IP 507100 IMS 01008 – PowerPoint PPT presentation

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Title: PROMISE


1
PROMISE
Product Lifecycle Managementand Information
Trackingusing Smart Embedded SystemsEU FP6 IP
507100IMS 01008
2
Product Systemflows
3
PROMISEClosing the information loops
4
PROMISE enabling technologiestomorrow (2005
2010)
  • A possible feasible approach
  • Applications based on PLM systems enabled via
    PEID and wireless Internet

Reader
PEID
PLM system
Internet
5
Ideas in a nutshell
Initial product info is written in the product
embedded device
Product delivery
Producers PDKM
Producers PDKM
Producers PDKM
Embedded device
Wireless Internet connection between mobile
device and producers PDKM
Wireless connection between mobile device and
product embedded device
A certified agent for service or End-Of-Life
operations
Update information in the embedded device and in
the producers PDKM
Service maintenance
End-Of-Life
6
The PROMISE approach
  • - PLM agent
  • Knowledge agent
  • DFX agent

- Data
- Sensors - Tags - Memory - Data
Producers PDKM
- PLM system - KB repositories
Embedded device
Producers PDKM
Producers PDKM
- Info - Advice
- Info
- Info
Internet (long distance)
- Data
Wireless comm. (short distance)
- Info request
- Semantics - Ubiquitous computing
- Diagnosis - Decision making
e-transformation of information to knowledge
7
PROMISEVision
  • To develop a new generation of PLM system that
  • uses smart embedded IT systems,
  • allows the seamless flow and transformation of
    data and information to knowledge.
  • To allow all actors in a products lifecycle to
    manage and control product information
  • at any moment of its lifecycle,
  • at any place in the world.

8
PROMISEMission
  • to allow information flow management to go beyond
    the customer
  • to close the product lifecycle information loops
  • to enable the seamless e-Transformation of
    Product Lifecycle Information to Knowledge

9
Product IDsome questions
  • In general, a smart product should be able to
    answer questions like
  • Who are you?
  • Who created you?
  • Who owns you now?
  • What kind of a product are you?
  • Do you contain hazardous materials?
  • Who repaired you?
  • What has been happening to you?
  • When are you going to expire?
  • What is your destination?
  • When should you arrive at your destination?
  • Are you on the right route?

10
Product IDmore questions
  • Products, or product components must be able to
    communicate their relationships to other
    "things".
  • This enables a smart product to answer questions
    like
  • To which order do you belong?
  • To what shipment do you belong?
  • To what sub-assembly do you belong?
  • What service procedure was carried out on you?

11
Product informationavailable anywhere at any time
  • Product-centric information management
  • Concentrating information around product instead
    of around companies
  • Enabling information sharing, easier access and
    management of the data
  • Product information updates performed in
    real-time
  • Product life cycle management becomes easier

12
PEID Research
  • High class PEID tags with ID and other sensing
    functionalities
  • PEID system protocols for maximum robustness and
    performance
  • PEID longevity and reliability

13
PEID Related Software Research
  • Data filtering, collection and event triggering
    models
  • Aggregation strategies (i.e. how do we check if a
    PEID is linked to the product, to a product
    component, etc)
  • Distributed information services for managing
    product data
  • Extended Product Data specifications to include
    product instructions/recipes
  • Distributed decision making/decision support
    strategies based on availability of real time
    product data

14
Standardisationas an integration element
  • Standardisation is one of the key integration
    elements of the IMS PROMISE project
  • Standardisation issues will be the main part of
    the agenda of the planned IMS PROMISE workshops
  • Standardisation will be also an element of
    collaboration with the ATHENA IP on
    interoperability and other external projects.

15
Standardisation issues
  • Pre-normative and standardisation issues will be
    addressed in PROMISE at four levels
  • Hardware (PEID) ISO 18000
  • Firmware, D2D, D2B IMS Centre
  • Software (interoperability, security) - ATHENA
  • System (product policies, environmental issues,
    lifecycle management) ISO 14000

16
PEID Applications Research
  • Characterisation of the nature of product data
    generated/accessible from PEID tagged items
  • The role of PEID in real time response
  • EOL impact of product information on
    effectiveness of EOL processes (e.g. disassembly)
  • EOL/MOL impact of product information on the
    effectiveness and nature of reverse logistics
    processes
  • BOL impact of product information on guidelines
    for product design improvements

17
Truck predictive maintenance demonstratorat CR
Fiat
REMOTE DIAGNOSTIC LINK
MAINTENANCE
MISSION PROFILE ID.
Information and clustering of data
MAINTENANCE ON DEMAND
GPS
GSM/GPRS
PEID
Signals
MISSION ANALYSIS
COMUNICATION WITH CAN
(PEID Engine,PEID Transmission, )
REMOTE DIAGNOSTIC LINK (WIRELESS)
Engine usage profile
GROUND STATION
Consumption analysis
IDENTIFICATION OF INCOMING ANOMALIES
IDENTIFICATION OF MISSION PROFILES AND
CORRELATION WEAR / DRIVING STYLE
18
PREDICTIVE MAINTENANCEthe idea
PREVENTIVE MAINTENANCE Goal avoid
failure Example Engine Oil substitution High
Costs due to materials and manpower
CORRECTIVE MAINTENANCE Goal minimize maintenance
direct costs Example all unpredicted
/unpredictable failures High costs mainly due to
machine unavailability and repair time
THE IDEA BENEATH PREDICTIVE MAINTENANCE IS THE
IDENTIFICATION OF SLOW DEGRADATION TRENDS IN THE
PERFORMANCE OF SPECIFIC SYSTEMS IN ORDER TO
IDENTIFY WITH A REASONABLE ADVANCE THE NEED OF AN
INTERVENTION. THIS ALLOW THE OPTIMISATION OF
MAINTENANCE INTERVENTION WITH THE IMPLEMENTAION
OF A PERSONALISED MAINTENANCE POLICY
19
IMS-PROMISEwhy an IMS proposal ?
  • Products are global
  • Used locally
  • Production is global
  • Production units are local
  • Service maintenance is global
  • Performed by local agents
  • End-Of-Life is global
  • Performed by local agents

Global sustainabilty of product systems
20
PROMISE IMS structure
21
IMS PROMISEregions partners
European Union Research partners (BIBA, Cambridge
University, CIMRU, HUT, ITIA-CNR, SINTEF,
POLIMI) system modeling, knowledge management
and logistics and decision making. Solution
providers (SAP, Indyon, INFINEON, Stockway,
InMediasP, COGNIDATA) Indyon, Stockway and
INFINEON will develop e-integrated hardware and
software infrastructure of PROMISE. SAP,
COGNIDATA and InMediasP will be responsible for
the Product Data and Knowledge Management issues.
Industrial partners (Centro Ricerce FIAT,
Caterpillar, Merloni, WRAP, INTRACOM, FIDIA)
specifications and requirements tasks, scenario
specification and testing evaluation.
Switzerland Research partner (EPFL) DFX and
Product Data and Knowledge Management issues in
close collaboration with the respective CH EU
participants. Industrial partners (Bombardier
Transportation, ENOTRAC) are interested in the
information flow and management for design,
service and maintenance of railway systems. 
22
IMS PROMISEregions partners
Japan Research partners (University of Tokyo,
Waseda University, Chuo University) will develop
the product life cycle models, simulation
algorithms and tools for the validation of the
PROMISE developments. Industrial partners (Ricoh,
Toyoda Machine Tools, Toyota Motors) will
contribute as end-users mainly for testing the
results produced in Japan. All of the Japan
industrial partners are well known global players
in their respective sectors of activity.
USA Research partners (University of
Wisconsin-Milwuakee, Stanford University,
University of Michigan) will develop
e-Maintenance and e-Service web-enabled systems
used in the MOL phase of a products life
cycle. Industrial partners linked with the
Intelligent Maintenance Systems Center (IMS) run
by the above academic organisations will provide
the necessary input from the industrial point of
in the above activity.
AUSTRALIA Research partners (IRIS) will develop
EOL management systems. Industrial partners (MTI,
AEEMA) linked with IRIS will provide the
necessary input from the industrial point of in
the above activity.
23
IMS PROMISEregional collaboration
Requirements and Specifications
AUS
CH
EU
USA
Information Modeling, Architecture, Implementation
DFX
MOL
EOL
Logistics/ Decision making
PEID technology
Prototypes and Demonstrators
Japan Modeling and Simulation
24
PROMISEWorkplan architecture
25
PROMISEClusters Actions
  • Research Clusters
  • specifications, theoretical foundations and
    methodologies
  • Research Cluster RC-1 PROMISE system
    architecture and modelling
  • Action RC-1.1 PROMISE system architecture
  • Action RC-1.2 PROMISE lifecycle modelling
  • Action RC-1.3 Product information flow modelling
  • Action RC-1.4 Definition of application
    scenarios

26
PROMISEClusters Actions
  • Research Clusters
  • specifications, theoretical foundations and
    methodologies
  • Research Cluster RC-2 Product Embedded
    Information Devices
  • Action RC-2.1 PEID Core
  • Action RC-2.2 PEID Customisable application
    specific prototypes
  • Action RC-2.3 PEID pre-industrialisation

27
PROMISEClusters Actions
  • Research Cluster RC-3 IT Infrastructure, Models
    and Software
  • Action RC-3.1 Design and Architecture
  • Action RC-3.2 Security and Privacy
  • Action RC-3.3 Communication and Interoperability
  • Action RC-3.4 Data Management
  • Action RC-3.5 Deployment, Test and Evaluation

28
PROMISEClusters Actions
  • Research Cluster RC-4 Methodologies for
    Information and Knowledge Treatment Decision
    Making
  • Action RC-4.1 Concept and methods for
    transformation of information to knowledge
  • Action RC-4.2 Methodology to support PROMISE
    specific KM processes
  • Action RC-4.3 Requirements of decision making
    during BOL, MOL and EOL
  • Action RC-4.4 Development of decision making
    methods and algorithms
  • Action RC-4.5 Implementation of the PROMISE
    information management system
  • Action RC-4.6 Consolidation and integration of
    evaluation results from the application clusters

29
PROMISEClusters Actions
  • Application Clusters
  • development of application sectorial
    demonstrators
  • Application Cluster AC-1 EOL (End-of-Life)
  • Action AC-1.1 EOL information management for
    monitoring of End of Life Vehicles
  • Action AC-1.2 EOL information management for
    heavy load vehicle decommissioning
  • Action AC-1.3 EOL information management for
    tracking and tracing of products for recycling

30
PROMISEClusters Actions
  • Application Cluster AC-2 MOL (Middle-of-Life)
  • Action AC-2.1 MOL information management for
    predictive maintenance for trucks
  • Action AC-2.2 MOL information management for
    heavy vehicle lifespan estimation
  • Action AC-2.3 MOL information management for
    machine tools
  • Action AC-2.4 MOL information management for
    EEE-1 (brown goods)
  • Action AC-2.5 MOL information management for
    EEE-2 (white goods)
  • Action AC-2.6 MOL information management for
    Telecom equipment

31
PROMISEClusters Actions
  • Application Cluster AC-3 BOL (Beginning-of-Life)
  • Action AC-3.1 BOL Demonstrator 1 DfX in the
    railway sector
  • Action AC-3.2 BOL Demonstrator 2 adaptive
    production in the automotive sector

32
PROMISEClusters Actions
  • Innovation Clusters
  • Innovation Cluster IC-1 Integration and
    Standardisation
  • Action IC-1.1 Integration and harmonisation of
    efforts with external projects
  • Action IC-1.2 Standardisation
  • Innovation Cluster IC-2 Business development
  • Action IC-2.1 Consolidation of PROMISE results
    and solving of IPR issues
  • Action IC-2.2 New innovative business
    opportunities identification and modelling
  • Action IC-2.3 Exploration of potential market
    for new business opportunities
  • Action IC-2.4 Evaluation of the considered
    business opportunities

33
PROMISEClusters Actions
  • Training Cluster
  • Training Cluster TC-1 Training
  • Action TC-1.1 Develop training concept
  • Action TC-1.2 Develop training delivery
    mechanisms
  • Action TC-1.3 Develop a web facility for
    training and external relations

34
PROMISEIntegrating clusters
35
Legend
Concepts
PROMISE Roadmap to Results
More general result
Formalisation
Main Deliverables
Implementation
Adoption
Possible synergy with ATHENA and IMS PROMISE
partners
Activities
TC-1
IC-2
IC-1
AC-1toAC-3
RC-4
PROMISE InformationManagement
RC-3
inter-enterprise softwareinfrastructure
Fully FunctionalController
Software Infrastructurevalidation
RC-2
RC-1
Month 42
Month 36
Month 24
Month 12
Month 0
36
PROMISEContact Details
  • Asbjørn Rolstadås (Project Coordination)
  • Phone  47 73 59 37 85   Fax  47 73 59 7117
  • E-mail  Asbjorn.Rolstadas_at_ntnu.no
  • Bjørn Moseng  (Project Administration)
  • Phone  47 73 59 37 97   Fax  47 73 55 1326
  • E-mail  Bjorn.Moseng_at_sintef.no
  • SINTEF Technology and Society
  • S. P. Andersens veg 5
  • N - 7465 Trondheim, Norway
  • Phone 47 73 59 03 00
  • Fax 47 73 59 03 30

37
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