Presentation is loading. Please wait.

Presentation is loading. Please wait.

© November 2004 1 PROMISE Product Lifecycle Management and Information Tracking using Smart Embedded Systems EU FP6 IP 507100 IMS 01008.

Similar presentations


Presentation on theme: "© November 2004 1 PROMISE Product Lifecycle Management and Information Tracking using Smart Embedded Systems EU FP6 IP 507100 IMS 01008."— Presentation transcript:

1 © November PROMISE Product Lifecycle Management and Information Tracking using Smart Embedded Systems EU FP6 IP IMS 01008

2 © November End-of-UseUse & Service ProductionDesign The 4 phases of a product system life cycle Resources Process Product Processes are designed, resources used and products produced and treated in each phase DFE DFMA DFS Information flows, complete or incomplete Recycling Re-use Re-mfg Disposal Materials Service Material flows Product System flows

3 © November PROMISE: Closing the information loops MOL Process Resourc e Product DESIGN Proces s Resourc e Produc t PRODUCTION Process Resourc e Product EOL Process Resourc e Product Materials Disposal Recycling Re-mfg. ServiceRe-use

4 © November PROMISE enabling technologies tomorrow (2005 – 2010)  A possible & feasible approach: Applications based on PLM systems enabled via PEID and wireless Internet Internet Reader PEIDPLM system

5 © November Ideas in a nutshell Product delivery End-Of-Life Embedded device Producer’s PDKM Initial product info is written in the product embedded device A certified agent for service or End-Of-Life operations Update information in the embedded device and in the producer’s PDKM Wireless Internet connection between mobile device and producer’s PDKM Wireless connection between mobile device and product embedded device Service & maintenance Producer’s PDKM Producer’s PDKM

6 © November The PROMISE approach - Data Embedded device - Diagnosis - Decision making - Data - Info - Info request - Info - Advice - PLM system - KB repositories - Sensors - Tags - Memory - Data Wireless comm. (short distance) Internet (long distance) - Semantics - Ubiquitous computing - PLM agent - Knowledge agent - DFX agent e-transformation of information to knowledge Producer’s PDKM Producer’s PDKM Producer’s PDKM

7 © November PROMISE Vision 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 product’s lifecycle to manage and control product information  at any moment of its lifecycle,  at any place in the world.

8 © November PROMISE Mission 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 © November Product ID: some 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 © November Product ID: more 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 © November Product information available 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 © November 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 © November 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 © November Standardisation as 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 © November Standardisation issues  Pre-normative and standardisation issues will be addressed in PROMISE at four levels:  Hardware (PEID) – ISO  Firmware, D2D, D2B – IMS Centre  Software (interoperability, security) - ATHENA  System (product policies, environmental issues, lifecycle management) – ISO 14000

16 © November 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 © November MAINTENANCE ON DEMAND MISSION PROFILE ID. MISSION ANALYSIS REMOTE DIAGNOSTIC LINK (WIRELESS) GROUND STATION Information and clustering of data PEID GPS GSM/GPRS Signals COMUNICATION WITH CAN (PEID Engine,PEID Transmission, …) IDENTIFICATION OF INCOMING ANOMALIES IDENTIFICATION OF MISSION PROFILES AND CORRELATION WEAR / DRIVING STYLE MAINTENANCE REMOTE DIAGNOSTIC LINK Engine usage profile Consumption analysis Truck predictive maintenance demonstrator at CR Fiat

18 © November PREVENTIVE MAINTENANCE Goal: avoid failure Example: Engine Oil substitution High Costs due to materials and manpower PREDICTIVE MAINTENANCE the idea 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 © November IMS-PROMISE why 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 © November PROMISE IMS structure PROMISE IMS assembly All IMS partners PROMISE IMS board All regional coordinators PROMISE IMS coordinator BOMBARDIER - CH EU SINTEF Modeling Hw & Sw CH EPFL DFX USA U. Milwaukee e-Service e-Maintenance Japan Toyota Motors Product Life Cycle Modeling & Simulation Australia IRIS EOL

21 © November IMS PROMISE regions & 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 © November IMS PROMISE regions & 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 product’s 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 © November IMS PROMISE regional collaboration Logistics/ Decision making Information Modeling, Architecture, Implementation PEID technology Requirements and Specifications Japan Modeling and Simulation DFX MOL Prototypes and Demonstrators CHEUUSA AUS EOL

24 © November PROMISE Workplan architecture

25 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Clusters & 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 © November PROMISE Integrating clusters

35 © November Concepts Formalisation Implementation Adoption TC-1 IC-2 IC-1 AC-1 to AC-3 RC-3 RC-2 RC-4 RC-1 Legend PROMISE Roadmap to Results Main Deliverables More general result Possible synergy with ATHENA and IMS PROMISE partners Activities Month 42 Month 36Month 24Month 12Month 0 Application scenarios PROMISE Demonstrators Design & Roadmap System specifications and modeling PEID prototypes Requirements analysis PROMISE Information Management Fully Functional Controller PROMISE Demonstrators Implementation PROMISE Information Management Implementation intra-enterprise software infrastructure PEID prototypes Implementation Concepts for Knowledge Transformation Market Investigations Business Opportunities & Roadmap Training concepts PROMISE Information Management Validation inter-enterprise software infrastructure PEID Validation Standardization domains & Roadmap Standardization Initiatives & Activities Consolidated modeling PROMISE Demonstrators Evaluation TIPs & Business Plans Training Delivery Mechanisms Software Infrastructure validation

36 © November PROMISE Contact Details Asbjørn Rolstadås (Project Coordination) Phone: Fax: Bjørn Moseng (Project Administration) Phone: Fax: SINTEF Technology and Society S. P. Andersens veg 5 N Trondheim, Norway Phone: Fax:

37 © November Thank you !


Download ppt "© November 2004 1 PROMISE Product Lifecycle Management and Information Tracking using Smart Embedded Systems EU FP6 IP 507100 IMS 01008."

Similar presentations


Ads by Google