• Newcrest Mining PI World customer story

    Newcrest Mining is one of the world’s largest gold producers. With mines across three countries, Newcrest produced 2.49 million ounces of gold just last year, with growth and exploratory projects in the pipeline. But producing more gold isn’t just a matter of working harder — the company has to delve deeper underground and explore increasingly remote parts of the world to meet their goals. For Newcrest, the answer was “a scalable modern platform for collection and mobilization of data to produce digital outcomes for our company, as well as advanced analytics, such as AI and data science,” said Nevena Andric, IT Solutions Lead at Newcrest Mining.
    Year: 2020

    Rolloos PI World Gothenburg 2019 customer story

    Offshore drilling is a complex and dangerous process, and ensuring employee safety in the middle of the sea on a drill rig is a top priority. Operators driving the driller rely solely on a visual confirmation from ground crews while moving drill pipes. Between numerous personnel, heavy equipment, and 30-foot drill pipes, the drill rig is a dynamic environment that’s ripe for accidents. After a safety incident involving a drill pipe striking a crew member, a client reached out to Rolloos, an OSIsoft partner, for help. To enable its client to mitigate accidents and know where team members are at all times, Rolloos turned its CCTV technology into a comprehensive red zone detection system. By piloting OSIsoft’s Edge Data Store (EDS) technology, Rolloos ensured that all data was accessible by offshore operators for immediate decision support and could be streamed onshore for further retrospective analysis. Not only did this enable real-time monitoring of both people and heavy machinery, data is now used to optimize processes and improve overall performance.
    Year: 2020

    Wirtualne Seminarium Regionalne - Polska - Jak wdrożyć i zapewnić ciągły rozwój Inteligencji Operacyjnej firmy


    Year: 2020

    Ask the PI System Expert - Q&A Session: Usage & Condition based and Predictive Maintenance

    In this lab, we walk through scenarios to illustrate the use of process data and machine condition data for usage-based, condition-based and predictive maintenance. Data sources include traditional plant instrumentation such as PLCs and SCADA, the newer IoT devices, and ...
    Year: 2020

    Using AMI Data to Provide Situational Awareness to Grid Ops


    Year: 2020