HighByte Blog
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Time to read: 7 minutes  Posted by Omar Ahmed Based on my conversations with more than 500 manufacturing companies and integrators over the past five years, I believe the Industrial Internet of Things (IIoT) will continue to be a paramount part of the manufacturing landscape in 2021. The new year will bring a continued increase in digitalization across enterprises. While we have seen an increase in “digital transformation” initiatives among manufacturing companies for several years, the COVID-19 pandemic and the challenges it created for production, safety, remote access, and supply chain have accelerated the urgency to make digitalization a reality. I also believe IIoT projects will continue to scale because of changes we are seeing in people, processes, and technology.
Here are five predictions for 2021. Time to read: 7 minutes  Posted by Aron Semle 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: 8 minutes  Posted by John Harrington How much time do you spend cleaning data?
If your factory is like most connected operations, you probably have tons of raw data streaming from connected devices to existing enterprise systems, bespoke databases, and a cloud data lake. This architecture often leads to inconsistent or even unusable data for several reasons. We know the Cloud is a key tool for digital transformation. It provides the scalability and storage capacity you need to collect and interpret vast amounts of data coming from the operations level. However, by nature, cloud platforms are IT-focused tools. They structure data differently than operational systems, which means IT must spend a lot of time cleaning the data before it can be used. And if the data moves directly to different enterprise systems, multiple teams across the organization will clean the data independently, leading to different versions of the truth. Time to read: 6 minutes  Posted by Aron Semle Let’s talk about getting OPC data into Microsoft Azure. When you search this phrase in Google, 90% of results provide this use case: streaming sensor data to the Cloud.
If your Industry 4.0 solution is streaming sensor data to the Cloud, you're doing it wrong. Now let me explain. On the factory floor, we have machines driven by PLCs, and we typically have an OPC server connected to those PLCs that feeds data into an HMI. OPC servers and HMIs work with tags, which are discrete streams of data. For example, one tag might be for pressure and another might represent the on and off state of the machine. When cloud technology like Microsoft Azure first entered the scene, vendors created IoT gateways to connect to the OPC server and send tag streams to the Cloud in a JSON format. It was the easiest thing to do, and once that connection was made, we thought we were done. |
