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Simulation Data Management

Simulation Data Management. How engineering enterprises can improve Productivity, Collaboration & Innovation. What is Simulation Data management. Challenges in SDM. What is Engineering SDM. What is the scope of improvement for enterprises.

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Simulation Data Management

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  1. Simulation Data Management How engineering enterprises can improve Productivity, Collaboration & Innovation.

  2. What is Simulation Data management. • Challenges in SDM. • What is Engineering SDM. • What is the scope of improvement for enterprises. • Technologies used for high performance computing and storage. • Some basic real life examples. • Benefits of SDM. Outline

  3. Simulation - imitation of the operation of a real-world process or system over time. • Data Management- Administrative process by which the required data is acquired, validated, stored, protected, and processed. Simulation + Data Management = SDM • Simulation Data Management provides a mechanism to streamline the execution of our simulation processes while offering a suitable way to manage data. Simulation Data Management?

  4. The Volume, Velocity and Variety of SD. • Managing distributed data securely and efficiently. • Maintaining Data Integrity. • Collaboration and Communication. • Improving Knowledge Management. • Engineer’s Productivity. Challenges?

  5. Engineering SDM

  6. Data from PDM/ERP/PLM, such as CAD. • Data within simulation such as boundary conditions, materials, processes etc. • Details on simulation type, simulation task Simulation Input

  7. Data in large files • Unstructured solution results • Output from simulation processes, such as substructures, images, plots, animation files, reports. Simulation Output

  8. Conceptual Design • Detailed Design • Validation To address these complexities engineering Enterprises typically deploy large number of Software tools. Unique about ESDM?

  9. Generally, enterprises are divided into 3 maturity levels regardless of their size. • Higher maturity level? • Better dealing with unrelenting data deluge. • Reduced Complexity. • Lower maturity level? • Opportunity to improve engineering productivity and innovation. Classifications

  10. SDM maturity levels.

  11. Isolated Islands: Single Tenancy • SD data stored in Stand-alone systems. • Data retrieval, management, consolidation task • Cumbersome, manual and time consuming. • Unstructured nature of data. • Greater data loss and greater data security risk. • Lower access to data. A bit in detail…

  12. An Archipelago: Replicated Tenancy • Data within many interconnected islands. • More coordination. • Improved data management/storage tasks. • Improved engineering productivity and innovation. • More agile and flexible. In-Detail Contd….

  13. Cloud : Multi tenancy • Access to data from anywhere. • Visualization and automated reporting. • Rapid access = improved decision making. • Flexibility and easy to use. • Improved productivity. • Data management and security. • Reduced total cost to ownership (TCO). In-Detail Contd…

  14. SDM Architecture - Solution

  15. Real Example.

  16. ANSYS EKM – Engg Knowledge Mgnmt. • GPFS – General parallel file system. • IBM storwize V7000 Unified. • IBM Sonas – Scaled out Network attached Storage. • IBM DCS3700

  17. SDM can be easily integrated with PLM/PDM systems. • Volume, velocity and variety affordably handled with HPC systems. • Automated SDM – better business decisions. Conclusion

  18. http://www.cabotpartners.com/Downloads/wp_addressing_engineering_simulation_data_mgt.pdfhttp://www.cabotpartners.com/Downloads/wp_addressing_engineering_simulation_data_mgt.pdf • http://www.ansys.com/Products/Workflow+Technology/Simulation+Process+&+Data+Management • http://step.nasa.gov/pde2007/NASA_ESA_PDE_5_07_Gene_Allen.pdf References

  19. Thank you

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