Digital Factoy in a Cloud and Grid Environment

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1 Digital Factory in a Cloud and Grid Environment MANUFUTURE, ICT and e-manufacturing, Wroclaw, October 24, 2011 Dr.-Ing. Carmen Constantinescu MBA October 24, 2011

2 Overview»Digital Factory«at Fraunhofer IPA Guiding Idea Fields of Research Grid Engineering for Manufacturing Approach and Realization Ways of Implementation and Migration at the Fraunhofer IPA From Grid to Cloud Engineering for Manufacturing Definition, Relevance and Potentials The Digital Factory in the Cloud The Way to Cloud Engineering for Manufacturing Slide 2

3 »Digital Factory«Fraunhofer IPA / IFF University of Stuttgart / GSaME Leading position in the field of»digital Production«through excellent research and the appliance of digital methods and tools through the whole factory life cycle Digital Factory Industry Higher Education Research Development Implementation Application Experience from industry Slide 3

4 Today s Approach: Grid Engineering for Manufacturing Continuously integrated product design, factory and process planning as well as factory operation and maintenance: Modelling, simulation, optimization and visualization of products, factories and processes Networking and distribution of data, models, tools and computer resources with the support of grid technologies Benefits: Reduction of time Lowering of costs Increase of throughput and quality of planning and optimization activities Slide 4

5 Fields of Research Grid Engineering for Manufacturing Factory Lifecycle Management Factory Data Management Digital Engineering Tools Integration of Heterogeneous und Autonomous Factory Information Systems Slide 5

6 Factory Life Cycle Management Objective Integrated and holistic planning and continuous optimisation of»factories as Products«How Systematisation and harmonisation of the planning phases and the corresponding planning steps Result Reference Model of Factory Life Cycle Factory Data Management Benefit Improved planning process with reduced planning and optimisation time Positive effects on produced products and planned and optimised factory Support for standardisation: Guidelines (e. g. VDI) and norms (e. g. DIN) Slide 6

7 Factory Data Management Ziel: Objective Verwaltung Management und of factory Bereitstellung data along von Daten factory der life Fabrik- cycle and und over Prozessplanung all factory entlang scales des Fabriklebenszyklus und über alle Skalen einer Fabrik How Identification, collection and Resource structuring of all relevant data Factory Product Definition and representation of corresponding dependencies Semantic-based data description Result Factory Data Reference Model: knowledge-driven, generic, modular, scalable, open Process Basis for the analysis and selection of factory data management systems Benefit Data actuality, integrity and minimal redundancy Support for data change propagation and systems integration Sharing and (re-)use of manufacturing knowledge Factory Data Fabrikdatenmanagement Management Slide 7

8 Digital Engineering Tools (I) Objective Support for planning, optimization and operation of continuously integrated product design, factory and process planning as well as factory operation and maintenance s How Use of suitable engineering tools Development of own tools Economics of digital tools Digital Factory Result Holistic engineering tool portfolio Benefit Reduction of planning time Lowering of planning costs Increase of throughput and quality Slide 8

9 Digital Engineering Tools (II) Implementation NX², Pro/Engineer 1 Windchill 1 FLIP 3 vpronet 3 Failure Management System 5 Cooperative Planning Table 3 ProVis.Visu 7 ProVis.APS 7 Teamcenter Manufacturing 2 GEMFlow GEM Factory Immersion 3 Factory CAD/Flow 2 Total Energy Efficiency Management TEEM 3 GEMFlow 3 GRIDGlobus (OGSA) 6 Plant Simulation 2 Coating Simulation 3 Process Simulate 2 Process Designer 2 1) Parametric Technology Corporation (PTC) 2) Siemens Industry Software 3) Fraunhofer IPA 4) IFF - University of Stuttgart 5) Sikom, Solvtec 6) GlobusAlliance 7) Fraunhofer IOSB Order Management System 3,4 Factory Cockpit 3,4 DataEngine 3,4 Slide 9

10 Digital Engineering Tools (III) GEMLab 2.0 Hardware 1. GEMLab 1 Stereoskopic 3D-Projection Wall 8 12 dedicated PC Workstations 12 High-End-PCs for 3D-Cube System 14 further PCs as additional Workstations Cooperative Planning Table Input devices for VR: SpaceMouse Nintendo Wii Control and Balance Board 2. Smart Factory 2 Ubisense, mobile terminals, RFID readers 3. Parts of Learning Factory 2 Physical Learning Factory and coupled Digital Learning Island 1) Fraunhofer IPA 2) IFF University of Stuttgart 3) Siemens Industry Software 4) Parametric Technology Corporation (PTC) 5) Sikom, Solvtec 6) Globus Alliance 7) Fraunhofer IOSB 8) Eyevis 9) University of Malta 10) Autodesk Software Planning Phase Digital Tools Product Development NX 3, Pro/Engineer 4, Autocad 10, Inventor 10 Product Lifecycle Management Windchill 4 Factory Performance and Investment Planning FLIP 1 Side and Network Planning vpronet 1 Process, Equipment and Workplace Planning Process Simulation Plant Simulation 3 Layout Planning Internal Logistics Process Designer / Process Simulate 3 Cooperative Planning Table 1, Process Designer 3, FactoryCAD 3, SBFP 9 FactoryCAD 3, FactoryFlow 3, Plant Simulation 3, Order Management System 1,2 3D Visualization GEM Factory Immersion 1 Factory Operation Failure Management System 1,5 Order Management System 1,2 Factory Cockpit 1,2, DataEngine 1,2 ProVis.Agent 7 : ProVis.APS 7, ProVis.Visu 7 Total Energy Efficiency Management 1 Factory Life Cycle Management Teamcenter Manufacturing 3 Planning Workflow System Integration Product-, Process-, Factory Modelling GEMFlow (Workflow System) 1 Globus Toolkit 6 UML-, BPMN-, OWL-Modelling Fraunhofer Tools IPA Slide 10

11 Integration of Heterogeneous and Autonomous Factory Information Systems (I) Objective Implementation of continuously integrated planning and optimization of factories How Conception of IT environments for networked and multi-scale factories Usage of standard based communication, integration and data exchange technologies Coupling of different static and dynamic models Result Grid Engineering for Manufacturing Laboratory 2.0»GEMLab 2.0«Benefit Standardized system interfaces Data transparency between systems Data security Lossless data communication Slide 11

12 Implementation: Grid Engineering for Manufacturing Laboratory 2.0 Investment and performance planning Site and network planning Buildings, Prozess- infrastructure and simulation media planning Internal Prozess- logistics simulation and layout planning Process, equipment and workplace planning Ramp-up and projectmanagement 1 Planning Product workflows development 8 Factory operation and manufacturing execution PLM Product data GRID technologies Specialized application, FEM Product functionality simulation Simulation techniques Factory performance simulation System simulation Process simulation FLM Factory data PLM: Product Lifecycle Management Product System Process FLM: Factory Lifecycle Management Slide 12

13 Integration of Heterogeneous and Autonomous Factory Information Systems (III) Implementation Data server DB Data server DB Data server Data server DB Data server DB Process Designer Import/ Export API FactoryCAD/ FactoryFlow Import/ Export API Plant Simulation ODBC API Planning table Import/ Export API Surface simulation Import/ Export API Failure Management System ODBC Gridadaptor Gridadaptor Gridadaptor Gridadaptor Gridadaptor Gridadaptor Open Grid Service Architecture (OGSA) Workflow Management System - GEMFlow Gridadaptor Import/ Export API Gridadaptor Web service API Gridadaptor Caption: PLM: Produkt Lifecycle Management FLM: Factory Lifecycle Management PLM Windchill FLM Teamcenter DB Data base: Data of Product, Process und Factory structure Data system DB Data system DB Processor pool for distributed processing Data system Data System: Large CAD data, documentations, simulation models Slide 13

14 Integration of Heterogeneous and Autonomous Factory Information Systems (IV) Implementation 1 Workflow system triggers Gridadaptor to start a new planning process Workflow System 4 Transfer of planning results to the planning workflow Gridadaptor starts planning process by displaying an operating procedure for the planner and transfers new planning data to the digital tool Gridadaptor 2 3 Access to digital planning tool (API, ODBC, Web service, Import/Export) Digital planning tool Gridadaptor reads change data as soon as the planning process is completed Slide 14

15 From Grid to Cloud Engineering for Manufacturing»Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.«[nist, 2011] Slide 15

16 From Grid to Cloud Engineering for Manufacturing»Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.«[nist, 2011] Concepts Rules Paradigms Slide 16

17 From Grid to Cloud Engineering for Manufacturing»Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.«[nist, 2011] Concepts Rules Paradigms Adapting Learning Customizing Cloud Engineering for Manufacturing Slide 17

18 From Grid to Cloud Engineering for Manufacturing Overview of Cloud Computing Services current in use or planned to be employed Already in use Possible Planned Non of this Collaborative and E- Mail Solutions Storage und BackUp Archiving Testing Environment Security Solutions Server Capacities Software Development Environment Ratio of polled companies in percent, n = Pierre Audoin Consultants (PAC): User Survey Outsourcing, Cloud & Managed Services 2011, Slide 18

19 From Grid to Cloud Engineering for Manufacturing Embedded Systeme Virtualization Grid Computing Service Orientied Architecture (SOA) Internet of Things The Semantic Web Utility Computing Apps for Mobile Devices Cloud Computing Grid Engineering for Manufacturing (GEM) Cloud Engineering for Manufacturing FACTORY OF THE FUTURE time Slide 19

20 Maturity of the Technology From Grid to Cloud Engineering for Manufacturing Enhancement of product lifecycle oriented distribution and integration of resources with help of Grid Engineering for Manufacturing with: Scaleable application, Internet of Things, Flexible und automatic performance adaption, Virtualization and thus, worldwide reachability of physical resources, Business process management, Knowledge integration and Cloud Computing Cloud Engineering for Manufacturing Grid Engineering for Manufacturing to Cloud Engineering for Manufacturing today time Slide 20

21 From Grid to Cloud Engineering for Manufacturing Product lifecycle Distribution, Marketing Tendering Design, Planning Control Process execution System Integration Mock Up Operation and Maintenance Upgrading Reconfiguration Adaption Desktop and Mobile Devices IT-Network Communication Secure, intelligent, scaleable and flexible collaboration environment Apps for Engineers Technicians Experts Resources Machines Systems Factories Digital Products Digital Factories Processes Resources IT-Services for all stakeholders (PLM centered, federative, workflow based, secure, cooperative, intelligent) Slide 21

22 Factory abilities The Way to Cloud Engineering for Manufacturing Service orientation Context awareness Distribution and integration Life cycle orientation PHASE IV Cloud Engineering for Manufacturing PHASE III Smart Factory PHASE II Grid Engineering for Manufacturing PHASE I Learning Factory Integration technologies Grid Computing Federation Ubiquitous Cloud Computing time Key technologies Slide 22

23 The Way to Cloud Engineering for Manufacturing Challenges on the way to Cloud Engineering for Manufacturing Confidence Organization Technology Confidence Guaranteed performance in spite of virtualized processing capacity und data security in spite of a removal of physical separation of data Technology Integration, realization and implementation of Cloud Computing, workflow management systems, knowledge management systems and reference models for the manufacturing industry Organization Analysis und adaption of suitable business models und app concepts Slide 23

24 »Information and Communication Technologies as the Enabler for Future Production«Humans Technologies Organisation Slide 24

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