IIoT It’s All About Data—Machine-Learning Data Discovery

IIoT It’s All About Data—Machine-Learning Data Discovery

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.

Alliances Advance Edge to Cloud Analytics and Computing

Alliances Advance Edge to Cloud Analytics and Computing

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.”

Siemens Talks Manufacturing In America

Siemens Talks Manufacturing In America

A small group of journalists and writers trekked to the Detroit area March 12-13 to glimpse the future of Manufacturing in America sponsored by Siemens Industry and its local distributor/partner Electro-Matic. We toured the local Founders Brewery facility, visited with faculty and students of Industrial and Systems Engineering at Oakland University, and attended the annual thought leadership panel.

Food and Beverage

Founders Brewery, craft brewery founded in Grand Rapids, MI, built a smaller version of brewery/restaurant in downtown Detroit not far from Ford Field and Greektown. The automated part of the brewery and instrumentation was supplied by Siemens. We toured the brewery, had an awesome sandwich, and sampled some of the many craft beers from founders.


A complete change of pace (well, maybe not as I remember my college days) took us north to Rochester, MI to Oakland University. Robert Van Til, Ph.D., Pawley Professor of Lean Studies and Chair of Industrial and Systems Engineering (ISE), introduced us to his program and several students who explained their experiences both in class and working in local factories.

Siemens has donated much software and equipment to the program. Students explained how they had been trained in Siemens PLM software and used the simulation application to model real-world problems. They impressed me with a maturity I doubt that I had at that age, but also with how smoothly they integrated Lean Manufacturing concepts with their factory cell simulations.

-> An important point. I hold the impression left over from some years ago that young people view manufacturing negatively—as dark, dirty, unsafe, backwards places to work. Much to the contrary, these students all viewed manufacturing as a place to use their technical training to make an impact. They see how they can contribute to an organization immediately. I guess the work we’ve done over the past 20 years to clean up our factories and apply technology are being rewarded.

Finance 4.0

Nothing beats an early morning meeting to talk finance. Actually, it’s not that bad. Before the Wednesday summit meeting, we met with the Siemens Finance team. Note: we did this last year, as well.

Siemens has identified six challenges for manufacturers on the journey to Industry 4.0. Challenge No. 2 identifies access to finance for the scale of investment over time that manufacturers need to make in digital and automated technology platforms.

The team has released a white paper, “Practical Pathways to Industry 4.0 in the USA.” This would be Finance 4.0 for Industry 4.0. Snipping one section, “Integrated Strategic Finance,” here are a few points:

  • Evaluate potential sources of finance for both OPEX and CAPEX
  • Consider how you’ll finance all aspects of digital transformation
  • Align with strategic growth vision and technology investment
  • Find financing partners with willingness and skills for this journey
  • Is your CFO a ‘virtuoso’ in linking initiatives to financial outcomes

Siemens Finance has many financial instruments in place to help from brownfield upgrades to greenfield projects—and for complete equipment financing, not only Siemens equipment.

Thought Leadership Summit

Raj Batra, President of Digital Factory for Siemens Industry Inc., took the ball from MC Eddie Murray (former NFL kicker), discussing how manufacturing executives in the US are very optimistic about the near future for manufacturing. One large problem is finding talented people to fill the positions. He also discussed Siemens technology and how it is helping manufacturers, for example like adidas who in this “order the latest fashion online” world need to shrink the 18 month timeline from concept to delivery of new shoes. Siemens PLM to the rescue.

Greg LaMay, Director Global. PLM Implementation for KUKA NA, showed how his team is using Siemens PLM applications to break silos within the company to improve time to ship and customer experiences.

John Greaves, IoT, RF, and Blockchain Solutions Architect (with a portfolio like that, he could probably bring the world to an end 😉 ) at Lowry Solutions, showed how Blockchain (the technology used by Bitcoin, for example) is already used for critical supply chain applications.

Alan Beaulieau, Ph.D., Economist, and President of ITR Economics (check it out, he wrote a column for me at Automation World for several years and he’s a great speaker), gave his usual well researched and reasoned view of the economic scene. Hint: it’s better than you might think reading the newspapers or listening to TV. itreconomics.com

Industrial Internet Consortium Releases Endpoint Security Best Practices White Paper

Industrial Internet Consortium Releases Endpoint Security Best Practices White Paper

Security comes first to mind whenever we begin discussing connecting things in an industrial setting. And, of course, nothing connects things like the Industrial Internet of Things (IIoT). One place we often fail to consider in our security planning is at the endpoint of the network. Organizations and companies have been providing valuable assistance to developers by releasing best practices white papers. Here is one from a leading Industrial Internet organization.

The Industrial Internet Consortium (IIC) announced publication of the Endpoint Security Best Practices white paper. It is a concise document that equipment manufacturers, critical infrastructure operators, integrators and others can reference to implement the countermeasures and controls they need to ensure the safety, security and reliability of IoT endpoint devices. Endpoints include edge devices such as sensors, actuators, pumps, flow meters, controllers and drives in industrial systems, embedded medical devices, electronic control units vehicle controls systems, as well as communications infrastructure and gateways.

“The number of attacks on industrial endpoints has grown rapidly in the last few years and has severe effects. Unreliable equipment can cause safety problems, customer dissatisfaction, liability and reduced profits,” said Steve Hanna, IIC white paper co-author, and Senior Principal, Infineon Technologies. “The Endpoint Security Best Practices white paper moves beyond general guidelines, providing specific recommendations by security level. Thus, equipment manufacturers, owners, operators and integrators are educated on how to apply existing best practices to achieve the needed security levels for their endpoints.”

The paper explores one of the six functional building blocks from the IIC Industrial Internet Security Framework (IISF): Endpoint Protection. The 13-page white paper distills key information about endpoint device security from industrial guidance and compliance frameworks, such as IEC 62443, NIST SP 800-53, and the IIC IISF.

Equipment manufacturers, industrial operators and integrators can use the Endpoint Security Best Practices document to understand how countermeasures or controls can be applied to achieve a particular security level (basic, enhanced, or critical) when building or upgrading industrial IoT endpoint systems, which they can determine through risk modeling and threat analysis.

“By describing best practices for implementing industrial security that are appropriate for agreed-upon security levels, we’re empowering industrial ecosystem participants to define and request the security they need,” said Dean Weber, IIC white paper co-author, and CTO, Mocana. “Integrators can build systems that meet customer security needs and equipment manufacturers can build products that provide necessary security features efficiently.”

While the white paper is primarily targeted at improving the security of new endpoints, the concepts can be used with legacy endpoints by employing gateways, network security, and security monitoring.

The full Endpoint Security Best Practices white paper and a list of IIC members who contributed can be found on the IIC website.

Industrial Internet of Things Integral Part of Industry of Things Conference

Industrial Internet of Things Integral Part of Industry of Things Conference

The Industry of Things World USA conference in San Diego in its third year is becoming a premier Internet of Things (IoT) event in the US. Organized by weConnect in Berlin, Germany, it attracts a few hundred attendees, excellent speakers, and me (of course). The organizers leverage worldwide contacts–organizing similar events in Berlin and Singapore. They also have similar events in other technology areas.

Topics cover a range of IT and OT subjects. I make sure to get to the OT people who are here. This is a quick recap of what I’ve seen so far.

Charlie Gifford spoke at a breakout session on ISA95. He updated us on the latest changes proposed to the standard. His other focus was to promote event-driven architecture. He suggested that we build a library of operations events such that when an event occurs information about the change with the updated data is broadcast to subscribers. This is a great bandwidth saving over continuous point-to-point connections. He is also concerned with how to interconnect the many existing databases within a plant or production location.

Jagannath Rao, SVP of IoT and MindSphere for Siemens, discussed the evolution of MindSphere and its latest incarnation. Key point–Siemens has committed to openness–providing for open APIs especially in its MindSphere platform and adoption of open technologies such as OPC UA.

MindSphere v 2 enabled people to go out and do Proof of Concept (PoC) projects. From these Siemens could determine what customers were interested in and what the problems were that they were trying to solve. This all fed back into the product development process leading to the recent release of v 3.

V3, now a product, builds on open technologies–open being the key word. The platform moved from SAP Leonardo to Amazon Web Services (AWS) providing a more robust cloud experience. AWS is a Infrastructure as a Service, while MindSphere is Platform as a Service containing open APIs and data models. The next step on the journey is for Siemens to build out an ecosystem of 3rd party applications.

When asked about TSN, Rao also brought up 5G, both of which point out the importance of the Edge for initial processing of IoT data. Siemens is preparing for this next step, for example its Sinumeric Edge contains much analytics power, then ability to communicate information not just vast streams of data.

OPC vice president of marketing Stefan Hoppe, during his breakout session, discussed the acceptance of OPC UA in industry and the power of the release of publish/subscribe with OPC UA. His strong discussion point was to emphasize that OPC UA is not a protocol. It is an information model. It uses protocols—AMQP, MQTT, DDS, JavaScript, whatever to communicate the information from one device to another (or many). Proponents of a protocol who suggest that a protocol is superior to OPC UA miss the point that it’s not a protocol but actually an information model.

One key potential misunderstanding…Hoppe’s presentation made OPC appear to be German-centric and tied to the German Industrie 4.0. We need to keep in mind that the OPC Foundation Board is only 33% German, and that OPC UA lends itself to the digitalization efforts of any of the countries developing standards. It has become the official communication technology for many standardization efforts including the Open Process Automation Forum. It is truly global.

Lin Nease, IoT technologist at Hewlett Packard Enterprise, chatted with me at a one-on-one meeting about the edge and the power of Xeon server technology in its edge devices as well as software-defined control. I think I’ll be seeing more from HPE as it builds out its IoT infrastructure.

Industrial Internet of Things Becoming a Reality According to Survey

Industrial Internet of Things Becoming a Reality According to Survey

Industrial Internet of Things and Augmented Reality technologies and applications have progressed from curiosity and exploration into the realm of maturing applications. At least, a snapshot of PTC’s customer base alludes to this.

PTC has released its bi-annual “State of Industrial Innovation” research report series.

“As the technologies and business models surrounding the Industrial IoT and AR continue to mature, there are sure to be sequential trends in adoption,” said Mike Campbell, EVP, ThingWorx Platform, PTC. “PTC’s combination of market experience and access to an extensive volume of adoption data enable a truly comprehensive view of the state of these rapidly evolving markets.”

As cited in “The State of the Industrial Internet of Things” and “The State of Industrial Augmented Reality” reports, Industrial IoT and AR are no longer just emerging technologies to watch. Investing in these technologies has become the critical strategy for many organizations in 2018, particularly those in industries that have complex manufacturing and operational processes. Of PTC customers that have adopted Industrial IoT or AR technologies, 83 percent using Industrial IoT and 85 percent using AR had already transitioned, or plan to transition, their deployments to full-scale production environments within the next 12 months.

Highlights from the reports include:

The State of the Industrial Internet of Things

1. Industrial IoT adoption is currently dominated by large product manufacturers in industries such as industrial products (25 percent), electronic and high-tech (22 percent) automotive (13 percent), and aerospace and defense (11 percent).

2. The economic potential of the Industrial IoT has garnered the attention of the international communities and led to global initiatives aimed at fostering the growth of Industrial IoT worldwide.

3. A majority of applications in use today apply to manufacturing and operations (48 percent), where the data collected can be used to refine processes, predict maintenance requirements, and increase overall operational effectiveness.

4. The Industrial IoT is no longer an emerging technology – it has arrived. Industrial IoT deployments are in production today, across functions from product development through manufacturing and service.

The State of Industrial Augmented Reality

1. Industries such as industrial products (21 percent), automotive (11 percent), and aerospace and defense (8 percent) are leading the way in early AR adoption.

2. AR has broad applicability to all functions of the value chain, and especially service (19 percent) and manufacturing (18 percent).

3. The application of AR to serve as a powerful instruction and guidance tool is providing an entry point for many organizations, particularly those industries that are defined by hundreds of vital processes, such as real-time monitoring and increasing overall equipment effectiveness (OEE).

4. AR adoption is reaching a critical tipping point, spurred on by massive investments into the underlying hardware and software technologies that are enabling a rapid transition of pilot projects into full production environments.


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