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.
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.”
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.
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.
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
Two things I know–First, this is, and always has been, a blog. That means that it’s personal and written by me. On the other hand, I’ll gladly quote anyone relevant. Second, people who work for PR agencies are under great pressure. Evidently they get paid per placement rather than collaboration and effectiveness. Either they or their marketing clients have read about the great Search Engine Optimization (SEO) of “guest posts” on blogs. I am inundated with requests–mostly from people who have no clue what my market is.
This is one such request from an agency I don’t know about a company I don’t know. I seldom write about robots for a variety of reasons. Mostly it’s because there hasn’t been much that is news. But robots are greatly misunderstood especially by writers in mainstream media who have no clue but do have lots of readers. So this request, with a somewhat poorly written intro, contained an “infographic” (something I also dislike) busting some myths. It’s worth a scan. The company is Acieta. Following is the intro.
Flying cars and moon colonies might still be a ways off, but the future is here in a lot of ways. Anyone old enough to remember watching “The Jetsons” can recall a world in which human beings have it easy because robots are doing all the dirty work. We might not be at the point where robots are doing everything we don’t want to do ourselves. Nonetheless, in the manufacturing sector, robots now make up a significant portion of the “manpower” used to make the items we use every day. Modern manufacturing as we know it today wouldn’t be possible without the contributions of robots. However, there’s a lot of information most people don’t know about them. They may be concerned that robots will make human beings in the manufacturing sector obsolete. They may be worried that robots create an unsafe working environment for people. Or, they may even be concerned that one day robots will become smart and independent enough to take over the world.
Knowing some of the basic facts about today’s modern manufacturing robots can do a lot to help alleviate those concerns, however. For instance, even though robots do much of the heavy and dangerous jobs in the modern manufacturing facility that humans used to risk life and limb to do, they still can’t do everything themselves. Human beings still are needed on the production floor for many tasks involved in the manufacturing process, as well as programming and servicing the robots themselves.
There’s also no reason to worry about manufacturing robots deciding they don’t need people anymore. Although advancements in artificial intelligence are being made seemingly every day, the robots found in manufacturing environments by and large are only capable of doing what they are programmed to do. What’s more, today’s robots are so sophisticated that they can recognize when an unsafe condition occurs and stop what they’re doing immediately until people are out of harm’s way.
The following guide dispels some of the most common myths about robots. If you’re concerned about robots’ place in the modern manufacturing landscape, take a look and have your questions answered. The future is here, and it may be better than you think.