HighByte Blog
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Read company updates and our technology viewpoints here.
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Time to read: 8 minutes Hannover Messe 2024 is just around the corner with the exhibit floor opening Monday, April 22 in Hannover, Germany. If you’ve never attended, Hannover Messe may truly be the world's leading trade fair for industrial technology, hosting more than 4,000 exhibitors and 130,000 on-site attendees each year. In this post, I’ll share a preview of what you can expect to see and hear from HighByte at the fair, including software demonstrations, product news, theatre presentations, and more. Time to read: 10 minutes One of the most common concerns I hear regarding the Unified Namespace (UNS) is the architecture lacks the versatility needed to address diverse downstream data consumers. Suppose quality, maintenance, and process engineers are all doing their part to support a production line. Quality teams need inspection results, maintenance teams need asset performance data, and process engineers need lot and process parameters. The teams need data sets that both overlap and differ by use case. These engineers are using different applications and services—anything from ERP modules for quality and maintenance to specialized ML platforms in the cloud—that each require very different data structures. Many of these applications and services do not easily interoperate with the UNS and its architectural conventions. They may not natively interface with MQTT brokers, nor should one expect them to. They may not consume payloads that were oriented around rigid asset hierarchy and publishing telemetry data from process control nodes. They may have completely different needs than what was envisioned when factory automation was installed and integrated. Their data needs can transcend how the UNS was initially architected and organized. HighByte Intelligence Hub can overcome these challenges. Through data modeling and pipelines, the Intelligence Hub enables the full potential of the UNS, delivering contextualized manufacturing data to the cloud. Let’s look at a sample architecture to see how. Time to read: 9 minutes In an earlier blog, “The power of payloads in your unified namespace,” I discussed the use of complex payloads combining multiple unified namespace (UNS) data streams to make the architecture more responsive to the diverse needs of consuming personas and systems. In this post, I want to show what these complex payloads might look like, how data models can enable a UNS architecture, and how easily HighByte Intelligence Hub can provide consuming systems with the necessary data—when and how it’s needed. Time to read: 8 minutes For quite some time, people have been asking us how the Intelligence Hub relates to a Unified Namespace (UNS). Is it a specific part of a UNS architecture, a platform by which one might build a UNS, or a UNS architecture itself? Over time, our answers have developed alongside the capabilities of the Intelligence Hub. From the beginning, the Intelligence Hub could connect to third-party MQTT brokers as well as model the data going in and out of them. And recently, we added an embedded MQTT broker to the Intelligence Hub to address brokering and provide the ability for MQTT clients to connect to the Intelligence Hub directly. These provided the functionality needed for much of what might facilitate or be considered a UNS, but it was missing a critical part: a way to visualize the contents. Time to read: 7 minutes The Unified Namespace (UNS) architecture pattern has proven to be an effective means to opening industrial data access up to the entire business, but the road to implementation is not without a few speed bumps. First, as industrial companies start to establish their hierarchy and build their UNS, they may find it difficult to get their data to follow their own rules. By its nature, UNS architecture draws from a multitude of different data sources, most of which present data in unique formats. Even superficially similar assets can format the data they generate in completely unique ways, and differences in data generated by wholly different machines, systems, and PLCs are even more stark. To limit problems in creating and operating a UNS, some industrial companies simply publish data from each system and device directly to an MQTT broker in their own topic namespace. This practice is not truly a UNS, and it offers little of the data accessibility and usability promised by this architectural pattern. Second, the UNS topic space typically follows the hierarchy: Site, Area, Line, Zone, Cell, and Asset. At each level, the information may include data from multiple systems including PLCs, SCADA, MES, CMMS, QMS, ERP, etc. On the consuming side, many users have unique needs that the UNS alone may not be able to meet. These challenges are what make consistent, easily scalable abstraction a critical part of your UNS. Time to read: 7 minutes The Unified Namespace (UNS) is among the fastest-growing data architecture patterns for Industry 4.0, promising easy publish-subscribe access to hierarchically structured industrial data. At HighByte, we define a UNS as a consolidated, abstracted structure by which all business applications can consume real-time industrial data in a consistent manner. A UNS allows you to combine multiple values into a single, structured logical model that can be understood by business users across the enterprise to make real-time decisions. But many industrials are finding that though they’ve loaded their device telemetry data in their UNS, they are struggling to use it. The UNS’ uniform data standards, hierarchical structure, and publish-subscribe pattern do an excellent job of providing easy, logical access to data, but business and analytics users often discover that they must subscribe to multiple data streams from separate levels of the hierarchy to get what they need for their applications. There are two problems with this approach: Time to read: 7 minutes For the past several months, 55 beta testers in 13 countries have been kicking the tires on HighByte Intelligence Hub version 3.0 and generously providing their feedback. Today, I’m excited to announce this major release is now available. Version 3.0 is a step change for the Intelligence Hub and for the Industrial DataOps market. It raises the bar for what a DataOps solution can be at Enterprise scale. It introduces a powerful new Pipelines builder to curate complex data pipelines. It makes the often-vague concept of the Unified Namespace (UNS) tangible and achievable with an embedded MQTT broker—reducing additional software, cost, and administration overhead for our customers. I sat down with HighByte Chief Product Officer John Harrington to talk about some of these advancements available in Version 3.0, including Pipelines. His thoughts are below. I also provide insights from our partner Goodtech, a deep dive on the embedded broker, a review of new project management capabilities, and more. Time to read: 6 minutes I’m excited to announce that HighByte Intelligence Hub version 3.0 is now available in beta. The release is packed with powerful new capabilities, including a fully integrated MQTT broker, enhanced Central Configuration, more intuitive user experience, and many more. These capabilities will enable you to rapidly deploy the data infrastructure you need to build a Unified Namespace (UNS), scale these deployments, manage the environment, and meet your advanced Industrial DataOps use case requirements. Time to read: 10 minutes The promise of Industry 4.0 has many manufacturing leaders thinking big. They envision a future in which real-time access to data opens the door to unprecedented levels of operational flexibility, predictability, and business improvement. For many, early-stage wins often lead to larger projects that stall or fail to scale because their data infrastructure couldn’t support the increasing project complexity. Enter Industrial DataOps. DataOps (data operations) is the orchestration of people, processes, and technology to securely deliver trusted, ready-to-use data to all the systems and people who require it. The first known mention of the term “DataOps” came from technology consultant and InformationWeek contributing editor Lenny Liebmann in a 2014 blog post titled, “DataOps: Why Big Data Infrastructure Matters.” According to Leibmann: “You can’t simply throw data science over the wall and expect operations to deliver the performance you need in the production environment—any more than you can do the same with application code. That’s why DataOps—the discipline that ensures alignment between data science and infrastructure—is as important to Big Data success as DevOps is to application success.” Time to read: 7 minutes Update: HighByte Intelligence Hub has evolved since this blog first published in July 2021. Please visit this post to learn how the Intelligence Hub now provides a complete UNS infrastructure solution. The unified namespace (sometimes referred to as the UNS or universal namespace) can be an allusive concept for many of us as we move to an Industry 4.0. world. At HighByte, we define the UNS as a consolidated, abstracted structure by which all business applications are able to consume real-time industrial data in a consistent manner. The benefits of a UNS include reduced time to implement new integrations, reduced efforts to maintain data integrations, improved agility of integrations, access to new data, and improved data quality and security. We are often asked if HighByte Intelligence Hub is a UNS. The answer depends on your priorities and project scope. We typically see three architectural patterns for implementing the UNS. HighByte Intelligence Hub can play a key role in each approach by both providing access and structure to the UNS or acting as the UNS. Time to read: 6 minutes Data modeling is all about standardization. It enables interoperability, shows intent, determines trust, and ensures proper data governance. Given the criticality of usable data at scale for Industry 4.0, many manufacturers have turned to ISA-95—probably the most commonly recognized data-modeling standard around the world—for guidance. Created by a standards committee at the International Society of Automation, the ISA-95 specification defines in detail the electronic information exchange between manufacturing control functions and other enterprise functions, including data models and exchange definitions. The purpose of ISA-95 is “to create a standard that will define the interface between control functions and other enterprise functions based upon the Purdue Reference Model”. Per the committee, the goal is to reduce the risk, cost, and errors associated with system integration. Historically, ISA-95 has been the guide for many off-the-shelf and bespoke manufacturing execution systems (MES). Today, ISA-95 also helps industrial organizations implement data integrations that link MES, enterprise resource planning (ERP) systems, IIoT platforms, data lakes, and analytics solutions. It also eases the implementation of a unified namespace (UNS) for enterprise data integration. The specification defines a hierarchal model for systems, detailed information models, and a data flow model for manufacturing operations management (MOM). Let’s take a look at these 3 key attributes in more detail and uncover how the ISA-95 specification can be applied within HighByte Intelligence Hub. Time to read: 7 minutes 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: 4 Minutes 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
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.
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