System Prognosis and Health Management
Reliability has become increasingly critical to today’s infrastructure systems – be it trains, HVAC or smart manufacturing. But as budgets continue to be stretched, maintenance, operations, manufacturing and design teams must find ways to maximize system life without compromising safety and operational uptime.
PARC’s condition-based maintenance (CBM) technologies empower engineers, operators and maintenance personnel to manage and improve the health and reliability of critical systems across a broad range of industries. With a strong foundation in model-based methods to facilitate potent first-principle representations of systems, PARC enables high-accuracy (greater than 90%) reliability, low false alarm rates and relevant field-deployable solutions. Our cross-disciplinary CBM suite includes software and hardware that leverage PARC’s key skills: sensing, modeling, diagnostics, machine learning, predictive analytics, rapid prototyping, artificial intelligence capabilities and patent portfolio.
With our work in system prognosis and health management, PARC is working towards enabling a world where self-aware, self-adaptive systems manage themselves autonomously with minimal human intervention, therefore taking system performance, maintenance and reliability to new levels.
Our work is centered around a series of Focus Areas that we believe are the future of science and technology.
We’re continually developing new technologies, many of which are available for Commercialization.