The innovative SIAT developed by NEC offers value to Lockheed Martin as it addresses the development of complex systems and the uniqueness of deep space exploration.
FREMONT, CA: Lockheed Martin and NEC Corporation signs a collaboration agreement to widen their partnership using NEC's System Invariant Analysis Technology (SIAT). The firms are also finalizing a licensing agreement with a multi-year option. Across the space domain, Lockheed Martin is using AI technology to offer proactive insights during production and for operational mission needs.
This collaboration will continue to offer proven artificial intelligence (AI) and machine learning (ML) potentials across product lifecycles with a focus on accelerating the system diagnostics' speed and efficiency. This positively affects the design and production phases of spacecraft development, including applications on NASA's Orion vehicle for the Artemis mission. The power of AI is used across the entire enterprise. With a trusted partner like NEC, companies gain the resources to expand their potentials at scale across the internal operations. By proactively analyzing telemetry data, the companies can offer systems even faster and optimize the employees' work every day.
For many years, Lockheed Martin and NEC have been working together to evaluate the effectiveness of SIAT for early production testing and operational instances. As a result, Lockheed Martin has combined SIAT into the Technology for Telemetry Analytics for Universal Artificial Intelligence (T-TAURI) AI service. This enables the organization to drive proactive anomaly identification during the design, development, production, and test phase of spacecraft development.
NEC's SIAT advanced analytics engine leverages data gathered from sensors to learn the behavior of systems comprising computer systems, power plants, factories, and buildings, allowing the system itself to automatically identify inconsistencies and prescribe resolutions. By combining within Lockheed Martin's T-TAURI platform, a comprehensive time series analysis framework, the team can get an exhaustive, holistic understanding of a system, developing a foundational system for innovative technologies like system-level digital twins.
AI will be applied on future missions in many ways, including future ground station help for customer satellite operations and expanding the application for human-rated systems to demonstrate an increase in the speed of anomaly identification and root cause analysis on the mission.