National Instruments Rebrands, Acquires Data Analytics Company

I debated for most of the day about using my energy to work on this blog post about NI (formerly known as National Instruments). It has long been one of my favorite companies. Its user conference, NI Week, overflowed with energy and bright engineers with big ideas. The founders were brilliant, yet humble, men. And I met some of the nicest people in the industry there.

Their marketing and PR people identified me with automation and control, for obvious reasons. Beginning in about 2010 or 2011, they seemed to become more distant until by the 2011 and 2012 NI Weeks, they didn’t talk to me about a single interview. I met with marketing people through 2014, and then all was quiet.

But I’m a keen observer. I noticed that industrial automation and even IoT were being rapidly de-emphasized in favor of the test market. That’s where the company started and remains the core competency. I also noticed that by 2012 the keynotes were no longer about “gee whiz” technology but rather about big engineering ideas—none of which were in industrial control and automation.

And they began emphasizing “NI” rather than the entire name more than 10 years ago.

Therefore, the big splash about rebranding and new directions were not entirely a surprise to me. Well, the green color scheme was. And I have a pet peeve about senior executives explaining what the logo means. I believe that a logo should be self-evident. But as for a new direction, everything they talked about were things I’ve seen them doing for years—solving big engineering problems, community contributions, diversity, sustainability. It’s almost like internally they realized what they had become. But I knew it. No longer the company of the small sale where the average order was $1,000, but now the company of solving big engineering problems.

Which is all good.

Even so, I am interested in data—data acquisition, analytics, and data used for problem solving.

Therefore, the acquisition. This should be a great move. I’m a possibility thinker, so I see these moves and see all the possibilities for good that can happen with a strong merger.

The news in short:

The acquisition strengthens data analytics software capability to provide enterprise-level value.

NI has entered into a definitive agreement to acquire OptimalPlus Ltd., a global leader in data analytics software for the semiconductor, automotive, and electronics industries. The acquisition will expand NI’s enterprise software capabilities to provide customers with business-critical insights through advanced product analytics across their product development flow and supply chain.

NI and OptimalPlus serve highly complementary positions in the semiconductor, automotive, and electronics industries. NI test systems are used in semiconductor manufacturing with OptimalPlus serving as a leading supplier of semiconductor manufacturing data analytics. Similarly, the NI automotive and electronics production test offerings are complementary to OptimalPlus’ growing automotive and electronics analytics business. Combining the strength of NI’s software-centric approach with OptimalPlus’ enterprise-level analytics software is expected to dramatically increase the value of test and manufacturing data, enabling product insights that will improve quality, efficiency and time to market for both NI and OptimalPlus customers.

“The addition of OptimalPlus’ data analytics capabilities will enable us to accelerate our growth strategy by increasing enterprise-level value for shared customers in the semiconductor and automotive industries.” said Eric Starkloff, NI President and CEO. “During this age of digital transformation, we remain committed to delivering innovative software and systems that leverage a robust data platform to address our customers’ business challenges. I welcome the employees of OptimalPlus and look forward to collectively accelerating our long-term growth ambitions.”

“OptimalPlus is excited to join the NI team. We are confident NI is the ideal partner to accelerate our innovation and increase sales opportunities through advanced product analytics,” said Dan Glotter, OptimalPlus Founder and CEO. “It is evident we share the unique commitment to high-quality software tools and need for world-class customer experience. The acquisition by a technology leader like NI is testament to the leading-edge innovation delivered by our R&D, Product and Data Science teams in Israel and to the great dedication and commitment of our employees across the world. Together with NI, we will provide enterprise-level analytics to enable customers to achieve their digital transformation objectives while expanding our customer reach.”

The acquisition is subject to customary closing conditions, including regulatory approval. The transaction is valued at $365 million and expected to close in early Q3 2020. OptimalPlus had 2019 revenue of $51 million and employs approximately 240 employees. Due to the highly complementary nature of the companies, there will be minimal cost synergies from this transaction. NI plans to fund the transaction through a combination of cash on hand and debt.

About OptimalPlus

OptimalPlus develops analytic solutions based on its big data platform technology which combines machine-learning with a global data infrastructure to provide real-time product analytics and to extract insights from data across the entire supply chain. Serving tier-1 suppliers and OEMs, in the market of semiconductor, automotive and electronic industries. The company provides technology to enhance key manufacturing metrics such as yield and efficiency, improve product quality and reliability and provide full supply chain visibility. OptimalPlus headquarters and R&D are in Israel with offices in Asia, Europe, and the United States.

Using Software Technology To Be Competitive In An Industrial Market

This is a story about Bill Johnson, vice president of operations for Madison, WI-based Madison-Kipp Corp. (MKC). The company makes precision machined aluminum die castings and subassemblies for the transportation, lawn & garden, and industrial markets. The company faced two objectives to enhance competitiveness—to bring down costs and raise efficiency.

“Technology is very important to us,” said Bill Johnson, vice president of operations for MKC. “We have to keep ahead of our competitors in many different areas. Using Ignition and taking real-time data from our processes helps us understand our data — which helps us make better decisions.”

Note: I very seldom write this type of story anymore. When we laid out the editorial direction for Automation World back in the day, I wanted stories about the intelligent application of automation with the people doing the work as the hero of the story. Typically, these stories come from the marketing department of supplier company. They write about what they know—the hero of the story is their product or service. Since these stories are so hard to come by, I decided not to pursue them for The Manufacturing Connection even though stories are more powerful than a bunch of bullet points.

Back to the story. Unfortunately there are no specific numbers about savings, but Johnson describes the “before” scene—that is, before they implemented Ignition by Inductive Automation, an industrial application platform with tools for building solutions in human-machine interface (HMI), supervisory control and data acquisition (SCADA), and the Industrial Internet of Things (IIoT).

“Some of the results we have are in the cost savings realm, and we’ve also seen improved efficiency,” said Johnson. “Before, engineers had to collect data on their own. This would take a long time. Now, we’re able to pull that data in and look at it and solve problems very quickly.”

“Using the built-in connectivity, the Ignition platform has filled a void for us between multiple manufacturers and platforms,” said Jay Sandvick, senior automation controls engineer at MKC. “It’s given us interoperability that we didn’t believe we could have. We now have accessibility to data streams we didn’t have before. And we have the ability to generate seamless reports from machines that were previously thought unconnectable.”

Dotti Jacob, industrial integration engineer at MKC, adds, “We are now allowed us to use different programming languages, and tie into all sorts of different systems, without being held back by proprietary issues.”

The platform’s interoperability has allowed MKC to streamline its systems. “Before Ignition, we were reliant on various software packages that were frankly a nightmare to maintain and pay for,” said Sandvick. “With Ignition, we have a single-point interface, a single cost, and it has more than exceeded our expectations in talking to various machines.”

Remote access has been greatly improved. “Before, if I was at a different facility and there were troubleshooting issues, I would have to travel there to help out,” said Jacob. “Now that we have Ignition, I can access the SCADA from anywhere and see in real time actual images of the different machines and what they’re doing, which is very helpful for troubleshooting. Having real-time data, we can access from anywhere allows us to see and address the issue a lot more quickly than we could in the past — which saves us time and money.”

You can use your software platform to allow customers visibility into the production of their orders. “Our customers really enjoy the ability to see real-time data on their products being produced,” said Scott Sargeant, vice president of sales for MKC. “It allows them to understand things without having to travel to our location — which of course saves them time and money. We’re talking about a paradigm shift in information sharing. It really gives our customers a window into the production environment. And our ability to provide this helps differentiate Madison-Kipp from other manufacturers.”

Sargeant adds, “Now our customers can see that data, can understand impactful events, downtime, and other important issues in production.”

Ignition allows users to import CAD drawings of the plant floor as the background for screens. The screens show real-time movement of robots, so operators always have an accurate view of what’s happening. “Before, we had to use these cookie-cutter images that were not very accurate to what was actually happening on the floor,” said Jacob. “Now we’re able to take a CAD drawing of the equipment, and it can move in real time with however the equipment’s moving, and that’s very helpful.”

Training is a key differentiator for technology suppliers. Jacob said Inductive University—the free online educational center with hundreds of videos allowing users to learn at their own pace has been an additional benefit. “When I started with Madison-Kipp, I’d never heard of Ignition,” said Jacob. “I was able to get up to speed very quickly because Inductive University has videos that teach you anything you need to know in order to be successful using the software.”

AI Research For Tomorrow’s Production

While at the Hannover Messe Preview last week in Germany, I talked with the representatives of a German consortium with the interesting name of “it’s OWL”. Following are some thoughts from the various organizations that compose the consortium.

Intelligent production and new business models

Artificial Intelligence is of crucial importance for the competitiveness of industry. In the Leading-Edge Cluster it’s OWL six research institutes cooperate with more than 100 companies to develop practical solutions for small and medium-sized businesses. At the OWL joint stand (Hall 7, A12) over 40 exhibitors will demonstrate applications in the areas of machine diagnostics, predictive maintenance, process optimization, and robotics.

Prof. Dr. Roman Dumitrescu (Managing Director it’s OWL Clustermanagement GmbH and Director Fraunhofer IEM) explains: “Our research institutes are international leaders in the fields of machine learning, cognitive assistance systems and systems engineering. At our four universities and two Fraunhofer Institutes, 350 researchers are working on over 100 projects to make Artificial Intelligence usable for applications in industrial value creation. With it’s OWL, we bring this expert knowledge into practice. In 2020, we will launch three new strategic initiatives worth 50 million € to unlock the potential for AI in production, product development and the working world for small and medium-sized enterprises.”

In the initiative ‘AI Marketplace’ 20, research institutes and companies are developing a digital platform for Artificial Intelligence in product development. Providers, users, and experts can network and develop solutions on this platform. In the competence centre ‘AI in the working world of industrial SMEs’, 25 partners from industry and science make their knowledge of work structuring in the context of AI available to companies.

Learning machine diagnostics and ‘SmartBox’ for process optimization

The Institute for Industrial Information Technology at the OWL University of Applied Sciences and Arts will present new results for intelligent machine diagnostics at the trade fair. Using a three-phase motor, it will be illustrated how learning algorithms and information fusion can be used to reliably identify, predict, and visualize states of technical systems. Patterns and information hidden in time series signals are learned and presented to the user in an understandable way. Inaccuracies and uncertainties in individual sensors are solved by conflict-reducing information fusion. For example, motors can be used as sensors. Within a network of sensors and other data sources in production plants, motors can measure the “state of health” and analyze the causes of malfunctions via AI. This reduces scrap and saves up to 20 percent in materials.

The ‘SmartBox’ of the Fraunhofer Institute IOSB-INA is a universally applicable solution that identifies anomalies in processes in various production environments on the basis of PROFI-NET data. The solution requires no configuration and learns the process behavior.

With retrofitting solutions of the Fraunhofer Institute, companies can prepare machines and systems in their inventory for Industrie 4.0 applications without major investment expenditure. The spectrum ranges from mobile production data acquisition systems in suitcase format for studies of potential to permanently installable retrofit solutions. Intelligent sensor systems, cloud connections and machine learning methods build the basis for data analysis. This way, processes can be optimised and more transparency, control, planning, safety, and flexibility in production can be achieved.

Cognitive robotics and self-healing in autonomous systems

The Institute of Cognition and Robotics (CoR-Lab) presents a cognitive robotics system for highly flexible industrial production. The potential of model-driven software and system development for cognitive robotics is demonstrated by using the example of automated terminal assembly in switch cabinet construction. For this purpose, machine learning methods for environ- mental perception and object recognition, automated planning algorithms and model-based motion control are integrated into a robotic system. The cell operator is thereby enabled to perform different assembly tasks using reusable and combinable task blocks.

The research project “AI for Autonomous Systems” of the Software Innovation Campus Paderborn aims at achieving self-healing properties of autonomous technical systems based on the principles of natural immune systems. For this purpose, anomalies must be detected at runtime and the underlying causes must be independently diagnosed. Based on the localization it is necessary to plan and implement behavioral adjustments to restore the function. In addition, the security of the systems must be guaranteed at all times and system reliability must be increased. This requires a combination of methods of artificial intelligence, machine learning and biologically inspired algorithms.

Predictive maintenance and digital twin

Within the framework of the ‘BOOST 4.0’ project, the largest European initiative for Big Data in industry, it’s OWL is working with 50 partners from 16 countries on various application scenarios for Big Data in production. it’s OWL focuses on predictive maintenance: thanks to the systematic collection and evaluation of machine data from a hydraulic press and a material conveyor system, it is possible to identify patterns in the production process in a pilot company. The Fraunhofer IEM has provided the technological and methodological basis. And successfully so: over the past two years the prediction of machine failures has been significantly improved in this specific application by means of machine learning methods. The Mean Time To Repair (MTTR) has already been reduced by more than 30 percent. The Mean Time Between Failures (MTBF) is now six times longer than before. A model of the predictive production line can be seen at the stand.

The digital twin is an important prerequisite for increasing the potential for efficiency and productivity in all phases of the machine life cycle. Companies and research institutes are working on the technical infrastructure for digital twins in an it’s OWL project. Digital descriptions and sub-models of machines, products and equipment as well as their interaction over the entire life cycle are now accessible thanks to interoperability. Requirements from the fields of energy and production technology as well as existing Industrie 4.0 standards and IT systems are taken into account. This is expected to result in potential savings of over 50 percent. At the joint stand, Lenze and Phoenix Contact will use typical machine modules to demonstrate how digital twins can be used to exchange information between components, machines, visualisations and digital services across manufacturers. Interoperability proves for the first time how the combination of data can be used to create useful information with added value for different user groups. For example, machine operators and maintenance staff can detect anomalies and receive instructions for troubleshooting.

Connect and get started – production optimization made easy

The cooperation in the Leading-Edge Cluster gives rise to new business ideas that are developed into successful start-ups. For example, Prodaso—a spin-off from Bielefeld University of Applied Sciences—has developed a simple and quickly implementable solution for the acquisition and visualization of machine and production data. The hardware can be connected to a machine in a few minutes via plug-and-play. The machine data is displayed directly in the cloud.

Prodaso has succeeded in solving a central challenge: Until now, networking machines from different manufacturers have been complex and costly. The Prodaso system can be retrofitted to all existing systems, independent of manufacturer and interface. In addition, the start- up also provides automated analysis and optimization tools. This enables companies to detect irregularities and deviations in the process flow at an early stage and to initiate appropriate measures. The company, founded in 2019, has already connected approximately 100 machines at companies in the manufacturing industry.

Inductive Automation Announces Ignition Firebrand Awards

Inductive Automation Announces Ignition Firebrand Awards

Inductive Automation has selected the recipients of its Ignition Firebrand Awards for 2019. The announcements were made at the Ignition Community Conference (ICC), which took place September 17-19. I get to see the poster displays and chat with the companies at ICC. I love the technology developers, but it’s fascinating to talk with people who actually use the products.

[Disclaimer: Inductive Automation is a long-time and much appreciated sponsor of The Manufacturing Connection. If you are a supplier, you, too, could be a sponsor. Contact me for more details. You would benefit from great visibility.]

The Ignition Firebrand Awards recognize system integrators and industrial organizations that use the Ignition software platform to create innovative new projects. Ignition by Inductive Automation is an industrial application platform with tools for the rapid development of solutions in human-machine interface (HMI), supervisory control and data acquisition (SCADA), manufacturing execution systems (MES), and the Industrial Internet of Things (IIoT). Ignition is used in virtually every industry, in more than 100 countries.

“The award-winning projects this year were really impressive,” said Don Pearson, chief strategy officer for Inductive Automation. “Many of them featured Ignition 8 and the new Ignition Perspective Module, both of which were released just six months ago. We were really impressed with how quickly people were able to create great projects with the new capabilities.”

These Ignition Firebrand Award winners demonstrated the power and flexibility of Ignition:

  • Brock Solutions worked with the Dublin Airport in Ireland to replace the baggage handling system in Terminal 2. The new system has 100,000 tags and is the largest Ignition-controlled airport baggage handling system in the world.
  • Corso Systems & SCS Engineers partnered on a pilot project for the landfill gas system of San Bernardino County, California. The pilot was so successful, it will be expanded to 27 other county sites. It provides a scalable platform with strong mobile capabilities from Ignition 8 and Ignition Perspective, plus 3D imaging from drone video and virtual reality applications.
  • ESM Australia developed a scalable asset management system to monitor performance and meet service requirements for a client with systems deployed all over Australia. The solution leveraged Ignition 8, Ignition Perspective, MQTT, and legacy FTP-enabled gateways in the field.
  • H2O Innovation & Automation Station partnered to create a SCADA system for the first membrane bioreactor wastewater treatment plant in Arkansas. The new system for the City of Decatur shares real-time data with neighboring water agencies as well as the mayor.
  • Industrial Networking Solutions created a new oil & gas SCADA system in just six months for 37 sites at ARB Midstream. The solution included hardware upgrades, a new control room, and a diverse collection of technologies with cloud-hosted SCADA, MQTT, Ignition Edge, and SD-WAN.
  • MTech Engineering developed an advanced real-time monitoring and control system for the largest data center campus in Italy. The project for Aruba S.p.A. had to work with huge amounts of data — and was done at a much lower cost than was possible with any other SCADA solution.
  • NLS Engineering created a single, powerful operations and management platform for more than 30 solar-power sites for Ecoplexus, a leader in renewable energy systems. The solution provided deep data acquisition, included more than 100,000 tags, and led to the creation of a platform that can be offered to other clients.
  • Streamline Innovations used Ignition, Ignition Edge, Ignition Perspective, and MQTT, to facilitate the automation of natural gas treating units that convert extremely toxic hydrogen sulfide into fertilizer-grade sulfur. The solution increased uptime, reduced costs, and provided access to much more data than Streamline had seen previously.
HPE Unveils Converged Edge Systems To Bridge OT and IT

HPE Unveils Converged Edge Systems To Bridge OT and IT

Hewlett Packard Enterprise (HPE) announced new HPE Edgeline Converged Edge System solutions that speed the deployment and simplify the management of edge applications, enabling customers to act on the vast amounts of data generated by machines, assets and sensors from edge to cloud.

I think this is another significant advance reflecting the utility of enterprise compute capability brought ever closer to the plant itself. If you are looking to be disruptive in your industry or are on a corporate engineering staff looking for OT alternatives, I’d suggest taking a long look at these technologies and then letting your imagination do its work.

The new solutions include:

  • HPE Edgeline OT Link Platform, an open platform that automates the interplay between diverse operational technologies (OT) and standard IT-based applications at the edge to enable intelligent and autonomous decision making;
  • HPE Edgeline systems management, the industry’s first systems management solutions designed specifically for the edge to ensure enterprise-grade reliability, connectivity and security;
  • HPE Edgeline EL300 Converged Edge System featuring OT link and HPE Edgeline systems management, providing superior resilience against harsh edge environments for a broad range of industrial deployments; and
  • HPE Edgeline Field Application Engineering Services are available from HPE Pointnext to help customers plan, build, and customize OT link-based Internet of Things (IoT) and cyber-physical systems.

To turn edge data into insight for real-time action, it must be processed close to its source to avoid the latency, bandwidth, and cost issues of sending the data to a remote data center. However, this opportunity comes with a set of unique challenges, including management of remote infrastructure, and the necessity to seamlessly connect sensors and industrial assets with IT applications at the edge.

“Deploying IoT, edge, and cyber-physical systems is a challenge requiring a fresh look at uniting the physical and digital worlds,” said Dr. Tom Bradicich, Vice President and General Manager, Converged Servers, Edge and IoT Systems, HPE. “With today’s announcements, we enable our customers to accelerate the delivery of applications that capitalize on edge data, safeguarded by enterprise-class management. And we lay the groundwork for a new ecosystem of intelligent edge solutions to drive innovation and growth across industries.”

Simplifying deployment of edge-to-cloud IoT and cyber-physical systems

Today, setting up an IoT or cyber-physical system is a laborious undertaking. It requires custom coding to orchestrate OT networks, control systems, and data flows with drivers, middleware, and applications running on IT systems. HPE Edgeline OT Link Platform is an open platform that significantly simplifies this process, reducing cost and time to market.

The solution includes:

HPE Edgeline OT Link Platform software, an open workflow engine and application catalogue, allowing customers to orchestrate components, data, and applications via a graphical drag-and-drop user interface. The HPE Edgeline OT Link Platform integrates an ecosystem of third-party applications running from edge to cloud – including AWS, Google, Microsoft, SAP, PTC, GE, and more – to make insights from the edge available across the enterprise and supply chain.

HPE Edgeline OT Link certified modules, HPE-developed adapters that connect to a broad range of OT systems, enabling bi-directional, time-sensitive, and deterministic control and communication, including high-speed digital input/output, CAN bus, Modbus, or Profinet. APIs and SDKs for these adapters are made available to the industry to facilitate third-party designs of OT link modules. OT link will also integrate FPGA modules to give customers maximal flexibility to connect to any industrial input/output device.

Enterprise-grade manageability and security at the edge

HPE also announced the industry’s first systems management solutions specifically designed to simplify the provisioning and management of edge infrastructure and applications, providing enterprise-grade manageability and security for remote systems with limited connectivity and IT expertise.

HPE Edgeline Integrated System Manager is embedded into HPE Edgeline Converged Edge Systems and features one-click provisioning, ongoing system health management, remote updates, and management even with intermittent wired and wireless connections. It also supports advanced security functions like preventing system boot file changes and remote system disablement during a security event. HPE Edgeline Infrastructure Manager software can remotely manage thousands of Edgeline Converged Edge Systems.

The HPE Edgeline Workload Orchestrator hosts a central repository for containerized analytics, AI, business, and IoT applications that can be pushed to HPE Edgeline Converged Edge Systems at the edge

Unparalleled convergence of OT and IT

The HPE Edgeline EL300 is a fan-less, low-energy system equipped with Intel Core i5 processors, up to 32GB of memory and 3TB of storage. It will also support Intel Movidius Myriad X vision processing units to enable video analytics and AI inference at the edge. The HPE Edgeline EL300 provides enhanced resiliency against shock, vibration, humidity, and dust, including IP50 and MIL-SPEC certifications, and can operate from -30 to +70 degrees Celsius. These features make the HPE Edgeline EL300 suitable to be deployed as an embedded system – for example, in production machines or in building infrastructure.

Expertise to accelerate deployment and create competitive advantage

To support these new offerings, HPE Pointnext, the services organization of Hewlett Packard Enterprise, provides HPE Edgeline Field Application Services, which help customers plan, design, build, and run IoT, edge and cyber-physical systems to accelerate deployment and ensure reliable and secure operation. These services include the evaluation of use cases, proof of value, solution deployment, and management of ongoing operations – helping customers get the most from OT/IT integrations.

Moreover, HPE Pointnext can help customers develop their own data acquisition, industrial network, and control components for HPE Edgeline OT Link Platform to create custom solutions and competitive advantage. HPE Edgeline OT Link Platform based solutions can be delivered on-premises with a turnkey deployment service, operated by HPE Pointnext.

Finally, HPE Edgeline EL300 Converged Edge System will be added to HPE GreenLake Flex Capacity, to deliver a consumption-based experience with usage-based payment, capacity metering, and tailored support, for customers who need a cloud-like experience for systems at the edge.