Simulation Data Management

advertisement
Simulation Data
Management
How engineering enterprises can improve Productivity,
Collaboration & Innovation.
1
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
2
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?
3






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?
4
Engineering SDM
5

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
6

Data in large files

Unstructured solution results

Output from simulation processes, such
as substructures, images, plots, animation
files, reports.
Simulation Output
7
Conceptual Design
 Detailed Design
 Validation

To address these complexities engineering
Enterprises typically deploy large number of
Software tools.
Unique about ESDM?
8
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
9
SDM maturity levels.
10

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…
11

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….
12

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…
13
SDM Architecture - Solution
14
Real Example.
15





ANSYS EKM – Engg Knowledge Mgnmt.
GPFS – General parallel file system.
IBM storwize V7000 Unified.
IBM Sonas – Scaled out Network attached
Storage.
IBM DCS3700
16
SDM can be easily integrated with
PLM/PDM systems.
 Volume, velocity and variety affordably
handled with HPC systems.
 Automated SDM – better business
decisions.

Conclusion
17



http://www.cabotpartners.com/Downloads/wp_addressing
_engineering_simulation_data_mgt.pdf
http://www.ansys.com/Products/Workflow+Technology/Si
mulation+Process+&+Data+Management
http://step.nasa.gov/pde2007/NASA_ESA_PDE_5_07_Gen
e_Allen.pdf
References
18
19
Download