Progress Webinars

From labs to production for Industrial IoT

Despite growing adoption of the Industrial Internet of Things, many businesses are still losing billions to unplanned asset downtime and equipment failures. Cognitive anomaly detection and prediction can help IIoT companies address this issue. To learn more, join top machine learning and IoT influencer Ronald van Loon and Progress DataRPM Vice President of Product Ruban Phukan for our upcoming webinar.

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How Industrial IoT is Influenced by Cognitive Anomaly Detection and Prediction

The Industrial IoT sector is facing maintenance challenges related to their data processes. Traditional methods of anomaly detection aren’t providing the right solutions for every entity, which is why Cognitive Anomaly detection is filling the gaps in predictive maintenance.

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Monetizing IIoT with Cognitive Anomaly Detection and Prediction

The Industrial Internet of Things (IIoT) presents a huge opportunity for businesses, and it’s only getting bigger. Gartner predicts that by 2020, the number of IIoT-powered devices will reach 20.8 billion and they’ll be producing trillions of gigabytes of data. Cognitive anomaly detection and prediction can help businesses monetize this wealth of data and drive meaningful change throughout their operations.

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Future Proofing Asset Failures With Cognitive Predictive Maintenance

The array of connected automotive industrial assets generate mass volumes of operational data. This data can be effectively tapped to map out potential risks using cognitive predictive maintenance which can convey this insight to automotive industrial asset experts. By applying machine learning to operational data generated by critical factory & automotive assets, OEMs can gain greater insights into these risk creating factors.

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Uncovering Machine Secrets In Factory Floor Using Data

Manufacturers are constantly battling 24*7*365 days to ensure zero downtime. But the reality of the unpredictable nature of machines often puts manufacturers in a tight spot. Having a laser sharp, focused analytics on factory utilization, manufacturers can have a real-time status check on machines and respond to failures much ahead of time.

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Building Data Products for Predictive Maintenance

In continuation with our “Productizing your Data” Webinar Series, you can watch on-demand our third webinar “Building data products for predictive maintenance” featuring Cognitive Computing veteran, Dr.Kirk Borne, Principal Data Scientist, Booz Allen Hamilton and Ruban Phukan, Co-Founder and Chief Products and Analytics Officer, DataRPM.

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Demystifying Cognitive Approaches to Predictive Maintenance: Part 1

McKinsey Global Institute predicts that by 2025 the Internet of Things will generate up to $11trillion in value to the global economy. As companies compete with exploding volumes of data from sensors, the world of industrial analytics seems dominated by buzz-words rather than large scale implementations.

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Productizing Big Data to create business value

In continuation with our “Productizing your Data” Webinar Series, you can watch on-demand our third webinar “Building data products for predictive maintenance” featuring Cognitive Computing veteran, Dr.Kirk Borne, Principal Data Scientist, Booz Allen Hamilton and Ruban Phukan, Co-Founder and Chief Products and Analytics Officer, DataRPM.

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Building Data Products For Recommendations And Predictions

In continuation with our “Productizing your Data” Webinar Series, watch on-demand our second webinar “Building Data Products for Recommendations and Predictions ” with Robby Thomas, Solution Architect, Amazon Internet Services and Ruban Phukan, Co-Founder & Chief Products and Analytics Officer, DataRPM.

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Industrial IoT & Failure Prediction On Event Signals | Part 1

We are excited to announce our 3 part webinar series on “Industrial IoT and failure prediction on event signals”. In this series, we will highlight how companies can seize the opportunity to monetize the trillion dollar opportunity in IIoT by “connecting the unconnected” for cognitive insights. These cognitive insights from real time sensor/machine data can empower companies to achieve ground-breaking results in plant efficiency, improved productivity and “digital readiness for smart factory”. 

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Rebooting Operational Excellence in Automotive Paint Shops Using Analytics

Aging  infrastructure and volatility in prices of raw materials, often place automakers in the tight spot to continuously look for radical ways to reduce operational costs. With powerful nexus of forces such as IoT, IIoT and machine learning, automakers stand at the brink to experience not just incremental but transformational benefits.

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