To help navigate the new world of machine intelligence, we have teamed up with the International Society of Automation (ISA) to provide informative articles discussing the power of machine intelligence and how facilities can best utilize intelligence to enhance operations, productivity and uptime.
Large Fortune 500 companies with deep pockets are investing in IIoT technologies. These projects are yielding results, although implementations are not without their challenges. An increasing number of industrial companies are looking at ways to leverage analytics, outside of the traditional applications that helped them on the production side. Some have a clear idea of what they want to achieve, some are trying to understand what various technologies could do for them. What does seem clear is that some form of IT/OT convergence and collaboration is necessary to achieve success.
There has been a lot of debate recently over the increasingly competitive and overlapping roles of operational technologists (OT) and information technologists (IT) within industrial automation.
Following our recent webinar with LNS, “Build an Analytics Anywhere Strategy today with the IIoT”, we have received a number of questions around the cost implications of implementing an IIoT strategy and how cloud and edge computing both play a part in an IIoT framework.
By 2050, the Earth’s population is set to swell from 7 billion to 9 billion. According to a 2015 report from the World Resources Institute, the agricultural sector will need to increase production by approximately 25% in order to meet the resulting demand.
For most manufacturers, the road to the Industrial Internet of Things (IIoT) is an evolutionary journey. And while it may be marked with twists and turns, it doesn’t have to be fraught with risk and uncertainty.
The Industrial Internet of Things (IIoT) can pay big benefits for organizations that do it right. It’s no surprise that a report by LNS Research and MESA International shows that more than 50% of manufacturers plan to pursue IIoT in the next 12 months. In fact, one of our gas pipeline customers has already saved over $9.8 million in maintenance downtime costs primarily because of IIoT.
Hydrocarbon producers face extreme pressures to reduce operational costs and boost efficiency. This is easier said than done. Standing in the way are outdated operational technology (OT) infrastructures that run supervisory control and data acquisition (SCADA) systems, historians, and automation control systems at satellite facilities and remote pumping stations. Often installed decades ago, these systems gather potentially valuable data, but it’s painful or even impossible to extract it for high-level analysis.