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Software & Analytics

Software & Analytics

The team at GE Research harnesses the power of computing, data and advanced analytics to enable the optimization of the "physical-digital" performance of industrial assets. We strive to accelerate the democratization of Industrial AI through software. Specifically, we seek to bring solutions to customers -- faster -- by developing software that writes software. Our question is: How can we develop software-defined machines that can foresee and adapt in order to -- eventually -- maintain and improve themselves with very little human intervention?

We view software as the skeleton, connective tissue, central nervous system, circulatory system and brain that integrates domain expertise, physics-based and (reduced order) machine learning models, sensor data and recommendations/controls. Bringing all of these together, software analytics can help optimize the lifecycle of industrial assets. For more than 100 years, GE Research has supported the GE domains of Power, Aviation and Healthcare to develop fundamental technologies, as well as to exponentially increase the use of real time and predictive analytics to improve inspections, maintenance and repair services. More recently, we have adopted this system-level thinking toward newer areas such as Renewable Energy and Additive Manufacturing. Our team has been an integral part of bringing Research to Reality.

As part of our mission to bring solutions to customers faster, we have streamlined the processes around transitioning workflows from early research prototypes to commercial outcomes. We partner with GE Research teams and external strategic partners to identify business needs, integrate domain expertise, reuse code and consolidate platforms. We are able to create personalized learning models of specific assets through multi-disciplinary teams from design, deployment, operational monitoring and maintenance.

  • Our Expertise

    Capabilities utilized for Software & Analytics

  • Physical-Digital Analytics

    Leveraging operational data, physical-based simulations and AI models to optimize production, improve quality, reduce costs and yield operational efficiency

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  • Industrial Software

    Bringing robust software development practices to interdisciplinary engineering teams to realize faster and more profitable outcomes

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