by Gary Mintchell | Mar 26, 2018 | Automation, Industrial Computers, Networking
Time Sensitive Networking, or TSN, extends and amplifies standard Ethernet as defined by the IEEE. The complete suite of specifications lacks a couple of areas, yet, but it is complete enough to begin using. NI (National Instruments) has been an early proponent of the technology participating in a testbed assembled by the Industrial Internet Consortium.
I’m a TSN believer. When the complete set of specs if finished and we see commercial-off-the-shelf chipsets, this high speed, deterministic network will be a game changer for the Internet of Things and indeed industrial control and automation. The amount of murmuring I’m hearing from suppliers confirms in my mind the potential.
NI has announced new CompactRIO Controllers that include NI-DAQmx and Time Sensitive Networking (TSN). These controllers offer deterministic communication and synchronized measurements across standard Ethernet networks to increase performance and help improve productivity in addition to flexibility. NI was the first to market with industrial embedded hardware supporting TSN, the next evolution of the IEEE 802.11 Ethernet standard, and provides these controllers as part of its continued investment in TSN. Engineers can use TSN to synchronize distributed systems across networks, which eliminates the need for costly synchronization cables.
As industries such as automotive, oil and gas, research and aerospace continue to implement the Industrial Internet of Things (IIoT), acquiring accurate, reliable and synchronized data across distributed nodes has become more challenging. As a result, companies must keep pace to ensure their systems are ready to meet these evolving requirements.
In the research space, A.M.S. Software GmbH is already taking advantage of the flexibility of CompactRIO with NI-DAQmx. “We are excited about the new CompactRIO Controller because of the flexibility it offers us,” said Klaudius Pinkawa, CEO of A.M.S. Software GmbH. “We needed to set up several experiments in a lab and then perform them on an aircraft in zero gravity. CompactRIO with NI-DAQmx allowed us to perform any experiment using the same hardware in both environments, which saved development time and reduced risks to the experiments.
The new CompactRIO Controllers feature:
- Submicrosecond synchronization with TSN over standard Ethernet for tightly synchronized, distributed measurements and control
- Shorter time to measurement than previous CompactRIO Controllers because of intuitive NI-DAQmx driver software
- Open and secure processing at the edge of the IIoT with the NI Linux Real-Time OS
- High-performance data analysis and control with an industrial-grade processor and onboard FPGA, programmable with LabVIEW FPGA
- Reliable operation in harsh environments with -40 °C to 70 °C operating temperature range, shock resistance up to 50 g and vibration resistance up to 5 g
With the addition of NI-DAQmx to the CompactRIO Controller family, engineers can access I/O directly from ready-to-use functions, which have made working with this driver the preferred data acquisition method for over 15 years. This intuitive driver coupled with the openness of the NI Linux Real-Time OS means users can continue to leverage the vast ecosystem of IP available for Linux, like Security Enhanced Linux (SE-Linux).
by Gary Mintchell | Mar 23, 2018 | Process Control, Security
Critical infrastructure control systems have been under cyber attack for years. Need we mention Stuxnet, the attack that brought the issue to the public eye? Pressure has been mounting on controls, automation, and IoT suppliers to protect a nation’s assets.
Siemens and eight partners signed a joint charter for greater cybersecurity at a recent Munich conference.
Highlights include:
- Ten action areas for greater cybersecurity
- Call for dedicated government ministries and chief information security officers
- Independent certification for critical infrastructures and solutions in the Internet of Things
The Charter of Trust calls for binding rules and standards to build trust in cybersecurity and further advance digitalization. In addition to Siemens and the Munich Security Conference (MSC), the companies Airbus, Allianz, Daimler Group, IBM, NXP, SGS and Deutsche Telekom are signing the Charter. The initiative is further welcomed by Canadian foreign minister and G7 representative Chrystia Freeland as well as witnessed by Elżbieta Bieńkowska, the EU Commissioner for Internal Market, Industry, Entrepreneurship and Small and Medium-sized Enterprises.
“Confidence that the security of data and networked systems is guaranteed is a key element of the digital transformation,” said Siemens President and CEO Joe Kaeser. “That’s why we have to make the digital world more secure and more trustworthy. It’s high time we acted – not just individually but jointly with strong partners who are leaders in their markets. We hope more partners will join us to further strengthen our initiative.”
The Charter delineates 10 action areas in cybersecurity where governments and businesses must both become active. It calls for responsibility for cybersecurity to be assumed at the highest levels of government and business, with the introduction of a dedicated ministry in governments and a chief information security officer at companies. It also calls for companies to establish mandatory, independent third-party certification for critical infrastructure and solutions – above all, where dangerous situations can arise, such as with autonomous vehicles or the robots of tomorrow, which will interact directly with humans during production processes. In the future, security and data protection functions are to be preconfigured as a part of technologies, and cybersecurity regulations are to be incorporated into free trade agreements. The Charter’s signatories also call for greater efforts to foster an understanding of cybersecurity through training and continuing education as well as international initiatives.
“Secure digital networks are the critical infrastructure underpinning our interconnected world,” said Canadian foreign minister Chrystia Freeland. “Canada welcomes the efforts of these key industry players to help create a safer cyberspace. Cybersecurity will certainly be a focus of Canada’s G7 presidency year.” The matter is also a top priority for the Munich Security Conference. “Governments must take a leadership role when it comes to the transaction rules in cyberspace,” said Wolfgang Ischinger, Chairman of the Munich Security Conference. “But the companies that are in the forefront of envisioning and designing the future of cyberspace must develop and implement the standards. That’s why the Charter is so important. Together with our partners, we want to advance the topic and help define its content,” he added.
According to the ENISA Threat Landscape Report, cybersecurity attacks caused damage totaling more than €560 billion worldwide in 2016 alone. For some European countries, the damage was equivalent to 1.6 percent of the gross domestic product. And in a digitalized world, the threats to cybersecurity are steadily growing: According to Gartner, 8.4 billion networked devices were in use in 2017 – a 31-percent increase over 2016. By 2020, the figure is expected to reach 20.4 billion.
by Gary Mintchell | Mar 21, 2018 | Data Management
Manufacturing technology professionals have been working with data of many types for years. Our sensors, instrumentation, and control systems yield terabytes of data. Then we bury them in historians or other databases on servers we know not where.
Companies are popping up like mushrooms after a spring rain with a variety of approaches for handling, using, analyzing, and finding all this data. Try on this one.
Io-Tahoe LLC, a pioneer in machine learning-driven smart data discovery products that span a wide range of heterogeneous technology platforms, from traditional databases and data warehouses to data lakes and other modern repositories, announced the General Availability (GA) launch of the Io-Tahoe smart data discovery platform.
The GA version includes the addition of Data Catalog, a new feature that allows data owners and data stewards to utilize a machine learning-based smart catalog to create, maintain and search business rules; define policies and provide governance workflow functionality. Io-Tahoe’s data discovery capability provides complete business rule management and enrichment. It enables a business user to govern the rules and define policies for critical data elements. It allows data-driven enterprises to enhance information about data automatically, regardless of the underlying technology and build a data catalog.
“Today’s digital business is driving new requirements for data discovery,” said Stewart Bond, Director Data Integration and Integrity Software Research, IDC. “Now more than ever enterprises are demanding effective, and comprehensive, access to their data – regardless of where it is retained – with a clear view into more than its metadata, but its contents as well. Io-Tahoe is delivering a robust platform for data discovery to empower governance and compliance with a deeper view and understanding into data and its relationships.”
“Io-Tahoe is unique as it allows the organization to conduct data discovery across heterogeneous enterprise landscapes, ranging from databases, data warehouses and data lakes, bringing disparate data worlds together into a common view which will lead to a universal metadata store,” said Oksana Sokolovsky, CEO, Io-Tahoe. “This enables organizations to have full insight into their data, in order to better achieve their business goals, drive data analytics, enhance data governance and meet regulatory demands required in advance of regulations such as GDPR.”
Increasing governance and compliance demands have created a dramatic opportunity for data discovery. According to MarketsandMarkets, the data discovery market is estimated to grow from $4.33 billion USD in 2016 to $10.66 billion USD in 2021. This is driven by the increasing importance of data-driven decision making and self-service business intelligence (BI) tools. However, the challenge of integrating the growing number of disparate platforms, databases, data lakes and other silos of data has prevented the comprehensive governance, and use, of enterprise data.
Io-Tahoe’s smart data discovery platform features a unique algorithmic approach to auto-discover rich information about data and data relationships. Its machine learning technology looks beyond metadata, at the data itself for greater insight and visibility into complex data sets, across the enterprise. Built to scale for even the largest of enterprises, Io-Tahoe makes data available to everyone in the organization, untangling the complex maze of data relationships and enabling applications such as data science, data analytics, data governance and data management.
The technology-agnostic platform spans silos of data and creates a centralized repository of discovered data upon which users can enable Io-Tahoe’s Data Catalog to search and govern. Through convenient self-service features, users can bolster team engagement through the simplified and accurate sharing of data knowledge, business rules and reports. Here users have a greater ability to analyze, visualize and leverage business intelligence and other tools, all of which have become the foundation to power data processes.
by Gary Mintchell | Mar 20, 2018 | Automation, Data Management, Internet of Things, Operations Management
Much of the interesting activity in the Industrial Internet of Things (IIoT) space lately happens at the edge of the network. IT companies such as Dell Technologies and Hewlett Packard Enterprise have built upon their core technologies to develop powerful edge computing devices. Recently Bedrock Automation and Opto 22 on the OT side have also built interesting edge devices.
I’ve long maintained that all this technology—from intelligent sensing to cloud databases—means little without ways to make sense of the data. One company I rarely hear from is FogHorn Systems. This developer of edge intelligence software has recently been quite active on the partnership front. One announcement regards Wind River and the other Google.
FogHorn and Wind River (an Intel company) have teamed to integrate FogHorn’s Lightning edge analytics and machine learning platform with Wind River’s software, including Wind River Helix Device Cloud, Wind River Titanium Control, and Wind River Linux. This offering is said to accelerate harnessing the power of IIoT data. Specifically, FogHorn enables organizations to place data analytics and machine learning as close to the data source as possible; Wind River provides the technology to support manageability of edge devices across their lifecycle, virtualization for workload consolidation, and software portability via containerization.
“Wind River’s collaboration with FogHorn will solve two big challenges in Industrial IoT today, getting analytics and machine learning close to the devices generating the data, and managing thousands to hundreds of thousands of endpoints across their product lifecycle,” said Michael Krutz, Chief Product Officer at Wind River. “We’re very excited about this integrated solution, and the significant value it will deliver to our joint customers globally.”
FogHorn’s Lightning product portfolio embeds edge intelligence directly into small-footprint IoT devices. By enabling data processing at or near the source of sensor data, FogHorn eliminates the need to send terabytes of data to the cloud for processing.
“Large organizations with complex, multi-site IoT deployments are faced with the challenge of not only pushing advanced analytics and machine learning close to the source of the data, but also the provisioning and maintenance of a high volume and variety of edge devices,” said Kevin Duffy, VP of Business Development at FogHorn. “FogHorn and Wind River together deliver the industry’s most comprehensive solution to addressing both sides of this complex IoT device equation.”
Meanwhile, FogHorn Systems also announced a collaboration with Google Cloud IoT Core to simplify the deployment and maximize the business impact of Industrial IoT (IIoT) applications.
The companies have teamed up to integrate Lightning edge analytics and machine learning platform with Cloud IoT Core.
“Cloud IoT Core simply and securely brings the power of Google Cloud’s world-class data infrastructure capabilities to the IIoT market,” said Antony Passemard, Head of IoT Product Management at Google Cloud. “By combining industry-leading edge intelligence from FogHorn, we’ve created a fully-integrated edge and cloud solution that maximizes the insights gained from every IoT device. We think it’s a very powerful combination at exactly the right time.”
Device data captured by Cloud IoT Core gets published to Cloud Pub/Sub for downstream analytics. Businesses can conduct ad hoc analysis using Google BigQuery, run advanced analytics, and apply machine learning with Cloud Machine Learning Engine, or visualize IoT data results with rich reports and dashboards in Google Data Studio.
“Our integration with Google Cloud harmonizes the workload and creates new efficiencies from the edge to the cloud across a range of dimensions,” said David King, CEO at FogHorn. “This approach simplifies the rollout of innovative, outcome-based IIoT initiatives to improve organizations’ competitive edge globally, and we are thrilled to bring this collaboration to market with Google Cloud.”
by Gary Mintchell | Mar 19, 2018 | Automation
Whenever people hear about automation or manufacturing technology, they always respond with “robots?”. Reading mainstream media where writers discuss manufacturing without a clue, they also seem fixated on robots. And most all of this ranges from partial information to misinformation. I seldom write about robotics because the typical SCARA or six-axis robots are still doing the same things they’ve always done—pick-and-place, welding, painting, material handling. They are better, faster, more connected, and in different industries, but in the end it’s still the same thing.
That is why I’m a fan of Rethink Robotics. These engineers are out there trying new paradigms and applications. Here is a recent release that I think bears watching. This news is especially relevant in the context of the visit I made last week to Oakland University and conversations with some students.
Rethink Robotics unveiled the Sawyer Software Development Kit (SDK), a software upgrade designed for researchers and students to build and test programs on the Sawyer robot. With a wide range of uses for university research teams and corporate R&D laboratories around the world, Sawyer SDK offers further compatibility with ROS and state-of-art Open Source robotics tools, as well as an affordable solution to increase access to advanced robotics in the classroom.
Sawyer SDK includes several advanced features that allow users to visualize and control how the robot interacts with its environment. Sawyer SDK now integrates with the popular Gazebo Simulator, which creates a simulated world that will visualize the robot and its contact with the environment, allowing researchers to run and test code in the simulation before running it on the robot. Sawyer’s Gazebo integration is completely open source, allowing students to run simulations from their individual laptops without a robot until they’re ready to test the code in real time. This approach allows professors to provide students with access to the industry-leading collaborative robots.
In addition to the Gazebo integration, Sawyer SDK includes a new motion interface that allows researchers to program the robot in Cartesian space. This development lowers the barriers for motion planning for programmers without a full robotics background. The new release also allows researchers to leverage new impedance and force control. Sawyer SDK also includes support for ClickSmart, the family of gripper kits that Rethink announced in 2017 to create a fully integrated robotic solution.
“Rethink’s robots are used in the world’s leading research institutions, which provides us with a wealth of feedback on what our research customers really want,” said Scott Eckert, president and CEO, Rethink Robotics. “As we have with all of our SDK releases, we’re continuing to set the standard in research with industry-leading features that allow universities and corporate labs to push the field of robotics forward and publish their research faster.”
Sawyer SDK is being piloted in robotics programs at multiple universities, including Stanford University, University of California at Berkeley, Georgia Institute of Technology and Northwestern University. Stanford’s Vision and Learning Lab works on endowing robots with diverse skills for both industrial and day-to-day personal robotics applications.
“Robotics is a field that combines technological and engineering skills with creativity, and the inventiveness our students have shown so far with the robots has been astounding,” said Dr. Animesh Garg, postdoctoral researcher in the Stanford University department of computer science. Animesh and his team of researchers have put Sawyer to use executing tasks directly from virtual reality (VR) input using automatic decomposition in simpler activities. Sawyer is also used for ongoing work in learning to use simple tools, such as hammers and screwdrivers.
Stanford University’s Experimental Robotics class allows students to think beyond day-to-day industrial tasks. They’ve trained Sawyer to draw, and track moving targets and hovering drones. Rethink’s Sawyer has enabled faster learning curves for researchers and students alike, making it easier than ever with the Sawyer SDK release.
The SDK will be available on all Sawyer robots, allowing access to both the Intera manufacturing software and the SDK software, starting in March 2018.
