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Simulation Data Management Survey Report

 

 

 








Simulation Data Management (SDM) is an emerging technology for improving the product development and sustainment process that encompasses the management of data, models, processes, documents and metadata intrinsic to performing modeling, simulation, and analysis.  However, while there is a significant amount of interest in this new area, there is also a wide variation of opinion across the industry on what SDM comprises, how to justify the business impact of investing in SDM, and how to minimize the risk of actually implementing SDM.

Formed in February 2008, the Simulation Data Management Working Group (SDMWG) provides a vendor-neutral, end-user driven consortium that promotes the advancement of the technology and practices associated with the management of engineering simulation data and processes.

The group is comprised of a mix of industrial end-users, consultants, vendors, and academia; it is led and directed by representatives of the industrial user community.  The heterogeneous nature of the SDMWG, a characteristic of the NAFEMS community as a whole, is a major strength of the group.  The diverse backgrounds also meant that it could not necessarily be assumed that all would share a common view of what SDM comprises.  It is human nature to allow one’s vision to be influenced by prior experience and it would not be at all surprising that a Product Data Management (PDM) or Product Lifecycle Management (PLM) vendor would not share the priorities of a simulation software (CAE) vendor or the developer of a process-integration or process-automation toolset.  Similarly, users from highly regulated industries such as Aerospace and Defense whose products need to be supported over many decades may see things differently from industries such as consumer goods where a product lifecycle might be measured in months.

To provide an understanding of the viewpoints of these various constituencies as well as to provide a baseline set of user requirements against which further SDM definition work could be targeted, the SDMWG decided to conduct a user survey, first of its own members and then opening it to the full NAFEMS membership. There was a total of 93 respondents to the overall survey although the number of respondents to each question varied slightly.  Those statistics are reported within each section of the report.

The survey questions were aimed at determining the scope of an SDM system in terms of categories of data to be handled, the level of abstraction and the process functionality offered.  Users were asked questions such as, “Should the SDM system be the controlling application for the category of data, should it merely be able to access the data through interfaces to other systems or, finally, is it simply out of scope?”

The survey content and findings are reported within logically grouped sections within this report, along with an in-depth review of each section.  These sections are:

• Demographics
• Scope of Simulation Data Management
• Product definition data
• Lifecycle state
• Simulation process and workflow
• Data related to other technical areas
• Granularity and classification of data
• Life expectancy of the data to be managed
• Data integrity and export to neutral formats
• Technological approach
• Additional input
• Suggestions for the NAFEMS Simulation Data Management Working Group 
• Conclusions

The relevant question or questions from the original NAFEMS survey is contained within the text of each major section so that the reader can directly refer to the question content and the answer options available to the survey respondent.

Contents


1. Introduction

2. Demographics

2.1 Geographic location and nature of organization
2.2 Presentation and interpretation of survey results
2.3 Area of interest in simulation
2.4 Experience with SDM systems
2.5 Experience or usage of PDM or PLM systems
2.6 Frequency of using data management systems
2.7 Basis of interest in Simulation Data Management

3. Scope of Simulation Data Management

4. Product Definition Data

5. Lifecycle State

5.1 In-work versus completed analysis
5.2 Management of data states

6. Simulation Process and Workflow

6.1 Process data
6.2 Analysis process capabilities
6.3 Hierarchical process modeling

7. Data Relating to Other Technical Areas

7.1 Reference data
7.2 Test data
7.3  Business data

8. Granularity and Classification of Data

8.1 Level of data abstraction / granularity
8.2 Structuring of data objects

9. Life Expectancy of the Data to be Managed

9.1 Completed analysis work including final reports
9.2 Metadata and knowledge
9.3 Models and associated databases
9.4 Execution processes and workflow
9.5 Ability to re-run processes and workflow
9.6 Output files and databases
9.7 Breakdown by industry sector

10. Data Integrity and Export to Neutral Formats

10.1 Data integrity functions an SDM system should provide
10.2 Requirements for the data integrity
10.3 Standards and data formats
10.4 Approach for exporting data to be provided by an SDM system

11. Technological Approach

11.1 Company approved
11.2 Individual preference

12. Additional Input

12.1 Other services to be provided by an SDM system
12.2 Capabilities or needs not adequately covered by the survey
12.3 General comments

13. Suggestions for the NAFEMS SDMWG

14. Conclusions




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About

NAFEMS Simulation Data Management Working Group

First Published - January 2012

Softback - 69 Pages