HighByte Blog
Read company updates and our technology viewpoints here.
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Read company updates and our technology viewpoints here.
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Time to read: 5 minutes The real value of Industry 4.0 is realized when manufacturers unlock the power of analytics. With the addition of artificial intelligence (AI) and machine learning (ML), organizations can transform raw data into predictive, meaningful insights. But manufacturers must first overcome a structural barrier to connect their process historians with their analytical applications. This is where HighByte Intelligence Hub comes into play. The latest release of the Intelligence Hub extends connectivity from enterprise systems to historian and time-series database applications, including PI System and InfluxDB. It removes a major disconnect between operational technologies (OT) and the business systems where organizational leaders access the information to make strategic decisions. Time to read: 7 minutes When I first joined the HighByte team, I knew two things. First, modeling industrial data is immensely powerful. After spending a decade interacting with tags and seeing firsthand how building context from tags in the Cloud is painful, I knew that modeling data at the Edge would be a game changer. The second thing I knew is that we were going to build a lot of connectors. This is par for the course in the industrial world where a mix of legacy and new equipment is the norm. We started with the most common and generalized standards, like OPC UA, HTTP, MQTT, and SQL to cast a wide net for connectivity options inside the factory. But it was clear that as we progressed, the market would demand explicit connectors for common systems. That is why I am excited to announce new connectors in version 2.2 for OSIsoft PI System (now part of the AVEVA portfolio), InfluxDB, and Oracle Database. All three connectors support both reading and writing data, and interacting with these systems in advanced ways, without needing to read a manual. Time to read: 7 minutes I love the chaos of an early market like DataOps for Manufacturing. It’s clear that things are changing, but what technologies and approaches will win out is less obvious. In these types of markets, as a solution provider, it’s equally fun to watch them mature. One sign of a maturing market is the type of questions early customers ask about a solution. At first, the questions are different variations of “Does it work?” or “How is it different than a, b, or c?” as customers try and understand the solution and how it solves their problem. As the market matures, the questions shift focus to technical requirements like “What’s the performance with 10,000x?” or “Does it support high availability?” Here at HighByte we’re seeing more scale and reliability questions in early engagements, a sign that both the market and the product are maturing. That’s why I’m excited to announce some key features in version 2.1 that make HighByte Intelligence Hub more scalable and reliable to fit the needs of your production environment. Time to read: 7 minutes Industry 4.0 solutions start with the same problem. How do I collect critical data from the factory floor? This sounds easy, but in reality, factory floors are highly heterogenous environments. It's common to have a newer machine that is highly connected sitting next to a 30-year-old machine with no connectivity at all. This forces teams to get creative. They might use an OPC UA server for one machine, SQL for the next, and retrofit another with new sensors that publish data via REST or MQTT. Each situation is unique, and teams need flexible solutions to leverage the connectivity options they have in place today. That’s why I am excited to announce the release of HighByte Intelligence Hub version 1.3. This release is full of new capabilities that allow our customers to gather data from many sources in the factory, rapidly add context to the data, and reliably deliver it to their platforms of choice. These additional capabilities greatly expand the connectivity options available to our customers. Here are the highlights:
Time to read: 6 minutes
A modern industrial facility can easily produce a terabyte of data each day. With the proliferation of sensors and the recent wave of real-time dash-boarding, artificial intelligence, and machine learning technologies, we should be seeing huge productivity gains. Unplanned maintenance of assets and production lines should be obsolete.
But this is not the case. Access to data does not mean it is useful. Industrial data is very raw and must be made “fit for purpose” in order to extract its true value. Furthermore, the tools used to make the data fit for purpose must operate at the scale of an industrial facility. With these realities in mind, I’ve written a practical, seven-step guide for manufacturers and other industrial companies to make their data fit for purpose. |
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