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Unifying Predictive Analytics and Real-time Process Optimization for Oil & Gas

A leading oil & gas company and one of GE’s most trusted and innovative partners had no way of integrating independent equipment issue detection capabilities. The company was losing money as a result of unplanned downtime due to maintenance scheduling issues and outdated software systems. They believed that a well-designed combination of IT assets would generate stronger insight than they had, affording them the ability to monitor offshore equipment from an onshore facility using real-time insight and predictive analytics.

  • General Electric
    GE is a diversified specialty equipment, infrastructure and financial services company. Their products and services range from aircraft engines, power generation, oil and gas production equipment, and household appliances to medical imaging, business and consumer financing and industrial products. GE believes new technologies will merges big iron with big data to create brilliant machines. This convergence of machine and intelligent data is known as the Industrial Internet, and it's changing the way we work. Year founded: 1892 Revenue: $148.5 billion (2014) NYSE: GE Featured Subsidiaries/ Business Units: - GE Digital - GE Predix - GE Intelligent Platform - Wurldtech
  • Construction & Buildings
  • Maintenance
  • Predictive Maintenance
    Predictive maintenance is a technique that uses condition-monitoring sensors and Machine Learning or rules based algorithms to track the performance of equipment during normal operation and detect possible defects before they result in failure. Predictive Maintenance enables the reduction of both schedule-based maintenance and unplanned reactive maintenance by triggering maintenance calls based on the actual status of the equipment. IoT relies on Predictive Maintenance sensors to capture information, make sense of it, and identify any areas that need attention. Some examples of using Predictive Maintenance and Predictive Maintenance sensors include vibration analysis, oil analysis, thermal imaging, and equipment observation. Visit our condition-based maintenance page to learn more about these methods.
  • A leading oil & gas company

  • GE’s Design Thinking team worked in close collaboration with the oil company’s team to co-create a system that would unify capabilities. To gain a richer understanding of the company’s specific needs, GE’s Design Thinking team visited one of the company’s facilities, where they demoed a prototype solution and received valuable feedback from the potential product’s end users. In addition to this site visit, the GE Design Thinking team scheduled weekly calls with the company to consistently seek their feedback on the prototype’s development. In this sense, GE’s Design Thinking process was truly one of co-creation, in which the potential product’s end user had a direct and influential impact on the product’s features and development strategy.

  • Downtime, Emergency Maintenance Work Orders, Equipment Status, Fault Detection, Notification Of System Issues
  • Mature (technology has been on the market for > 5 years)
  • Impact #1
    [Management Effectiveness - Real Time Information]
    The company recognized the value in the Design Thinking-created prototype’s ability to merge systems of predictive analytics and real-time data and authorized production of a finished product which seeks to enable better decision-making and greater efficiency. Although the product began as a customized solution to meet this company’s particular needs, it is now a core aspect of GE Oil & Gas’ software suite. This fact highlights Design Thinking’s ability to be both a pragmatic service, designing prototypes that fit custom parameters, and also a visionary service, conceiving of potential products that have the ability to catalyze new value for an entire industry.
    Impact #2
    Impact #3
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