A QSLS Engineering White Paper
Executive Summary
This white paper examines a naval Track Management System development project for the US Navy's surface fleet and identifies how the Quantifying System Levels of Support (QSLS) methodology could have enhanced decision-making, reduced costs, and improved outcomes. The Track Management System was successfully delivered by a team at General Dynamics Mission Systems led by Ron Townsen as Lead Architect, but faced several challenges during its development lifecycle. This case study illustrates how QSLS—a breakthrough approach to quantitative architecture assessment—could have provided substantial benefits throughout the project's lifecycle, potentially avoiding costly redirections and schedule concerns.
Introduction to Naval Track Management Systems
Track Management Systems (TMS) serve as a critical component in naval combat systems, responsible for collecting, correlating, and distributing data about all entities detected by ship sensors. These systems must operate with extreme reliability in real-time environments, processing thousands of potential tracks from space through sub-surface, while maintaining accurate situational awareness for the crew and combat systems.
The Track Management System discussed in this case study was developed for the Program Executive Office Integrated Warfare Systems (PEO IWS) of the US Navy to also include Missile Defense. Initially modeled after the Ship Self Defense System (SSDS) Mk 2 architecture, it was designed to integrate with both Aegis destroyers and eventually SSDS Mk 2 itself, demonstrating its fundamental importance to surface fleet operations.
Project Background and Implementation
In 2010, the Lead Architect was identified by the Chief Engineer for PEO IWS based on previous experience developing the Track Management system for SSDS Mk 2 at Raytheon. The system architecture focused on:
A central data storage system for track information
Evaluation mechanisms for incoming sensor data to sort detections into new tracks, updates to existing tracks, or track deletion
Communication systems to provide targeted track updates to remote computing systems based on their specific needs
Maintaining synchronization between the central storage and distributed components
The development team utilized UML for system modeling with embedded coding and generated test scripts directly from these diagrams, implementing software engineering best practices for the time. The system was successfully deployed and integrated with Aegis destroyer computer systems, and later served as an upgrade to the original SSDS Mk 2 Track Management System.
After successful deployment, responsibility for the system was transferred to the Surface Navy Lab for maintenance and continued enhancement. Subsequently, the system underwent architectural evolution to adopt a microservices architecture pattern, representing a significant transformation from its original design.
Challenges Encountered in Traditional Development
While the Track Management System was ultimately successful, the development process experienced several challenges that are common to complex systems engineering projects:
Architectural Selection Limitations: The initial architecture was based primarily on prior implementation experience rather than quantitative evaluation of multiple alternatives.
Design Mechanism Optimization: The team relied heavily on individual designer expertise and preferences rather than quantitative assessment of design options.
Implementation Redirection: Several implementation approaches had to be abandoned and reworked when they failed to deliver expected results.
Integration Platform Compatibility: Significant implementation work had to be backed out due to incompatibility between modern design patterns and the older timing-based approaches used in legacy integration platforms.
Stakeholder Communication: Extensive discussions with platform integrators were required to provide confidence in the system's ability to meet their needs and schedule.
Schedule and Cost Management: While the project ultimately met its schedule, there were periods of uncertainty and concern about timeline adherence.
Architectural Evolution: The later transition to a microservices architecture represented significant rework that might have been avoided with early architectural assessment.
How QSLS Would Have Enhanced the Project
The Quantifying System Levels of Support (QSLS) methodology addresses these challenges by providing a mathematical framework for evaluating architectural decisions objectively. Here's how QSLS would have benefited the Track Management System development:
1. Architectural Alternatives Evaluation
QSLS would have enabled quantitative comparison of different architectural approaches, including the centralized model that was implemented and the microservices approach that was eventually adopted. Through mathematical analysis of how each architecture supported key quality attributes like performance, reliability, and modifiability, the team could have made more informed architectural selections.
Potential Impact: The project might have adopted microservices architecture from the beginning, avoiding the significant costs associated with architectural transformation after deployment. In addition, without QSLS, there is no guarantee that microservices is the best choice.
2. Design Mechanism Optimization
Rather than relying solely on designer intuition, QSLS would have provided quantitative measurements of how different design mechanisms supported the system's quality attributes and business drivers. This would have enabled objective comparison of design alternatives.
Potential Impact: More optimal design choices would have reduced rework and increased system performance, potentially shortening development time.
3. Implementation Risk Reduction
By establishing clear quantitative linkages between implementation approaches and architectural goals, QSLS would have highlighted potential misalignments before they became problematic in the code. Particularly, it would have identified compatibility issues between modern design patterns and legacy timing-based approaches used in integration platforms reducing many discussions and rework.
Potential Impact: Fewer implementation redirections would have reduced wasted effort and prevented the costly backing out of implementations that proved incompatible with existing systems.
4. Enhanced Stakeholder Communication
QSLS provides quantitative evidence of how architectural and design decisions support stakeholder requirements. This objective data would have complemented the side-by-side collaboration with platform integrators allowing platform integrators to find potential problems earlier in the design and implementation process.
Potential Impact: Reduced time spent in justifying architectural decisions and increased stakeholder confidence earlier in the project lifecycle.
5. Schedule and Cost Optimization
By reducing uncertainty in architectural and design decisions, QSLS would have mitigated schedule risks associated with rework and redirection.
Potential Impact: More predictable development timelines and potentially lower overall development costs.
Quantifying the Potential Benefits
Based on analysis of similar defense projects, we can estimate the potential impact QSLS could have had on the Track Management System development:
Area of Impact | Traditional Approach | With QSLS | Potential Savings |
Architectural Evaluation Time | 3-4 weeks | 1-2 weeks | 2 weeks |
Design Iterations | 5-7 major revisions | 2-3 major revisions | 30-40% reduction |
Implementation Rework | 15-20% of total effort | 5-8% of total effort | 10-12% of project budget |
Stakeholder Review Cycles | 8-10 formal reviews | 4-6 formal reviews | 40% reduction in review effort |
Architectural Evolution Costs | Major post-deployment refactoring | Potentially avoided | 50-70% of refactoring costs |
While every project is unique, these estimates reflect typical improvements seen when quantitative architecture assessment methods are applied to complex systems engineering projects.
QSLS Application to Future Naval Combat Systems
Looking forward, the application of QSLS to naval combat systems development offers significant opportunities for the US Navy and defense contractors to improve system quality while reducing costs and development timelines:
Systems-of-Systems Integration: QSLS provides unique capabilities for quantitatively assessing interactions between individual systems within larger naval combat architectures.
Evolution Planning: As naval combat systems continue to evolve, QSLS can quantify the impact of proposed changes on quality attributes and business drivers.
Technology Refresh Decision Support: QSLS can provide objective measurements to support decisions about when and how to refresh technology components within long-lived systems.
Cross-Domain Security Analysis: For systems with multi-level security requirements, QSLS can quantify the security impact of architectural decisions.
Vendor Selection: When selecting between vendor-provided components, QSLS offers a framework for objective evaluation of how each alternative supports system requirements.
Conclusion
The Track Management System case study illustrates both the success possible with traditional architecture-led systems engineering and the potential for improvement through quantitative methods. While the system was successfully deployed and met its requirements, the development process experienced challenges that could have been mitigated through the application of QSLS.
As naval combat systems grow increasingly complex and interconnected, the need for quantitative architecture assessment becomes more critical. QSLS represents a paradigm shift in systems engineering, moving from qualitative assessment based primarily on experience to quantitative evaluation based on mathematical analysis.
By adopting QSLS for future naval combat system development, the US Navy and its contractors can expect reduced development risk, lower costs, shorter schedules, and ultimately, more effective combat systems for the surface fleet.
About QSLS Engineering
QSLS Engineering delivers breakthrough technology for quantifying system architecture, design, and implementation decisions. Our patent-pending methodology enables organizations to make data-driven decisions throughout the systems engineering lifecycle, significantly reducing risk and improving system quality.
For more information, visit www.qslsengineering.com or contact info@qslsengineering.com.
© 2025 QSLS Engineering Inc. All Rights Reserved. Patent Pending Technology - Case Number: 18/925,529
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