Visualize, analyze and organize engineering data for better decision making
IBM® Rational® Engineering Lifecycle Manager visualizes, analyzes and organizes engineering lifecycle data and data relationships. It enables product development teams to search and query engineering data that is stored and managed in multiple sources and locations. Rational Engineering Lifecycle Manager helps teams make better use of engineering data for more effective engineering decisions and more efficient compliance with industry standards.
Rational Engineering Lifecycle Manager features:
- Clear views of relevant and related engineering data that are simple to use.
- Analysis of engineering data that shows the impact of changes.
- Data organization that provides context for queries and decision making.
- Open architecture and federated data approach that lets you visualize, analyze and organize engineering data throughout your organization.
Clear views of relevant and related engineering data
- View and search engineering data from different tool sources and locations, including data from globally distributed, cross-discipline tools.
- See engineering data at an element level that includes requirements, design model elements, test cases and work items.
- Present data grouped by role, process and industry needs.
- Show relevant data relationships in easy-to-understand visual formats.
- Increase capacity for innovation by making better use of engineering time previously spent using multiple tools to find and present information.
- Access views of cross-tool and cross-domain data in the context of industry compliance standards to help achieve, maintain and demonstrate compliance.
Analysis of engineering data
- See the functional, procedural or structural relationships among data to determine the impact of engineering changes.
- Filter and hide irrelevant information from search results to keep the focus on data relationships that can impact processes, procedures and business outcomes.
- Extract and analyze pertinent information from the vast amounts of engineering data generated by modern systems engineering and software development projects.
- Assess readiness at critical milestones and provide detailed insight into development status.
- Group data according to product or system structures to provide context for engineering decisions.
- Use product and system structures to support the reuse of engineering data in multiple products or systems.
- Create highly specific, plain language queries to group related data, for example, “Show all requirements and related test cases for the Japanese variant of the head-up display unit on car model 1000.”
- Improve engineering agility by reducing the time it takes to find, query and analyze engineering data and relationships.
- Generate documentation that was previously difficult to assemble manually from multiple sources.
Open architecture and federated data approach
- Use the search, query, visualization, analysis and organization capabilities of Rational Engineering Lifecycle Manager with multiple product and systems development tools including:
- IBM Rational DOORS®, IBM Rational DOORS Next Generation, IBM Rational Rhapsody® Design Manager, IBM Rational Team Concert™ and IBM Rational Quality Manager
- IBM Rational Focal Point
- IBM Rational Asset Manager
- Mathworks Simulink (via Rhapsody Design Manager)
- National Instruments TestStand (via Rational Quality Manager)
- Mentor Graphics electrical systems design tools (proof of technology demonstration available)
- HP Quality Center (Beta)
- Take advantage of an open architecture to enable Rational Engineering Lifecycle Manager to be used with additional 3rd party and in house tools. The specification for building the index used by Rational Engineering Lifecycle Manager is available through OSLC (Open Services for Lifecycle Collaboration) and a SDK (software development kit) for building an adapter is available through the Eclipse Lyo project.
- Employ a federated, linked lifecycle data approach to cross-tool and cross-domain relationships, avoiding the cost and difficulty of moving data into a single repository.