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Key performance parameters (KPPs) are crucial for tracking and modeling performance throughout a system's lifecycle, from conceptualization to design to operations. However, as designs evolve and subsystems are constructed, it becomes increasingly challenging to monitor and comprehend the interplay between KPPs and other system requirements. This is especially evident in complex systems such as the Thirty Meter Telescope (TMT), necessitating the development of improved tools for visualizing the relationships between top-level science cases and multiple tiers of requirements and KPPs.
A comprehensive analysis of TMT KPPs has been done to ensure optimal performance for the TMT, including its first light adaptive optics system, NFIRAOS, and associated instruments, IRIS and MODHIS. Understanding the interdependencies between KPPs and requirements within these subsystems is critical for efficient design optimization. While our software solution, IBM DOORS, serves as a reliable tool for requirements management, it lacks an efficient means of establishing connections between requirements and KPPs. Consequently, we have enhanced our custom visualization tool, TraceTree, to facilitate the analysis of relationships between the project's science cases and KPPs. This allows us to identify the most demanding science cases for specific KPPs and determine how changes in KPP values can impact them. By establishing KPP traceability, we gain valuable insights into the potential consequences that alterations in requirements or predicted performance can have across the observatory.
This paper focuses on the definition and management of system-level KPPs and performance budgets at TMT. These best practices enable teams to refine budget estimates as designs progress and proactively identify areas of concern that may necessitate additional analysis or resources.
