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CBM competency overview

[NOTE: Video draft available at https://www.wetransfer.com/downloads/ab1d804adad18b28c74e6c05dee5d97020160507045208/b1595a242e9883f1e1cad99f68f3ac0b20160507045208/27f0aa] The reliability and uptime of a myriad of infrastructure systems is becoming increasingly critical. As services budgets continue to be stretched - maintenance, operations, manufacturing, and design teams are under tremendous pressure to maximize system life and utilization without compromising safety and operational uptime. PARC’s technologies empower engineers, operators, and maintenance personnel to improve the reliability and maintainability of critical systems and transition from conventional schedule-driven inspections to effective condition-based maintenance (CBM). This video provides an overview of PARC's CBM technology suite of innovative software and hardware technologies that work together to offer insights into system health, safety, and performance. PARC’s sensing, modeling, diagnostics, machine learning, predictive analytics, rapid prototyping, and artificial intelligence, have been being developed and perfected over more than a decade. Major organizations are already taking advantage of PARC’s CBM Suite, including East Japan Railway, BAE Systems, General Motors, LG Chem Power, IHI, and Xerox, among others. Trains/rails, HVAC, elevators, transportation infrastructure, energy storage, and smart manufacturing are just a few industries and systems being disrupted as a result of PARC’s CBM technology. PARC’s CBM is a model-based approach, enabling higher than 90% accuracy and negligible false alarm rates, arming our customers with actionable data for informed deployment. It gives them the ability to deeply understand their systems to smartly manage and keep them in top shape, or be able to know when to take them offline to fix them before any unfortunate events. CBM is a step towards PARC’s broader mission to enable self-aware, self-adaptive systems. This is driven by PARC’s strong foundation of model-based methods to facilitate a potent first-principle representation of systems. This gives the system a deeper “self-awareness” and makes it easier to scale up to other conditions and climates and enables other system management functions. PARC is working toward enabling a paradigm where systems manage themselves autonomously with minimal to no human intervention, taking system uptime, performance, maintenance, and reliability to the next level.

Raghavan, A.; deKleer, J.; Kurtoglu, T. CBM competency overview . PARC website.