HighByte Blog
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Read company updates and our technology viewpoints here.
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Time to read: 4 Minutes  Posted by Tony Paine Communication within a start-up is pretty straightforward. If you have a question about a new product launch, you go directly to the owner or CEO. Problems with a design flaw? Talk to your lead engineer. As that business scales, your lines of communication become more complex. You may need to send information through multiple channels to get an answer. Without an easy way to send or retrieve information, it might get lost or misinterpreted or you may wait days for an answer. Anyone who has worked in that environment knows the inherent challenges.
Time to read: 4 minutes  Posted by Omar Ahmed Bill is leaving Acme Manufacturing Corporation. And when Bill leaves, he will take with him a tremendous amount of the tribal knowledge that he accumulated over the last 10 years at Acme. Bill has spent the last decade building out all of the industrial data systems and all of the individual connections between these disparate systems. Bill is the only person in the entire facility who has knowledge of the custom connections and interdependencies between OT and IT systems. With Bill leaving, the team at Acme is challenged with picking up the pieces and trying to gather up all of Bill’s tribal knowledge in order to maintain connectivity and prevent system downtime. The OT and IT teams must go deep into the custom code to try to understand and replicate what Bill has done. This is a challenging and cumbersome task, especially when troubleshooting broken integrations.
Time to read: 10 minutes  Posted by John Harrington Most manufacturing companies realize the benefits of leveraging industrial data to improve production and save costs, but they remain challenged as to how to scale-up their pilots and small-scale tests to the plant-wide, multi-plant, or enterprise level. There are many reasons for this including the time and cost of integration projects, the fear of exposing operational systems to cyber-threats, and a lack of skilled human resources.
At the root of all of these problems is the difficulty of integrating data streams across applications in a multi-system and multi-vendor environment, which has required some degree of custom coding and scripting. Standardizing data models, flows, and networks is hard work. Unlike an office environment with its handful of systems and databases, a typical factory can have hundreds of data sources distributed across machine controls, PLCs, sensors, servers, databases, SCADA systems, and historians—just to name a few. Industrial DataOps provides a new approach to data integration and management. It provides a software environment for data documentation, governance, and security from the most granular level of a machine in a factory, up to the line, plant, or enterprise level. Industrial DataOps offers a separate data abstraction layer, or hub, to securely collect data in standard data models for distribution across on-premises and cloud-based applications. These four use cases illustrate how Industrial DataOps can integrate your role-based operational systems with your business IT systems as well as those of outside vendors such as machine builders and service providers. Time to read: 5 minutes  Posted by Torey Penrod-Cambra Leveraging industrial information to make better decisions, faster is the ultimate goal of Industry 4.0, Smart Manufacturing, IIoT, and Advanced Analytics solutions. However, as industrial information networks expand to encompass more sensors, devices, and systems, the existing data infrastructure has become overloaded. Manufacturers and other industrial companies require an Industrial DataOps solution that can handle industrial data collection, transformation, and delivery at scale. Scalability is the name of the game.
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