by Gary Mintchell | May 15, 2018 | Manufacturing IT, News
Walking through one of the Halls at the Hannover Messe, you suddenly find yourself in the Cloud—computing that is. There was Amazon Web Services, Microsoft Azure, and Google Cloud. The Manufacturing IT section just keeps growing. And getting more interesting.
One interesting aspect—I’m beginning to see articles speculating on the “end of Cloud computing.” Wonder what could come next?
Meanwhile, here is one piece of Cloud news I picked up. Amazon Web Services (AWS), an Amazon company, announced the general availability of AWS IoT Analytics, a fully-managed service that makes it easy to run simple and sophisticated analytics on massive volumes of data from IoT devices and sensors, empowering customers to uncover insights that lead to more accurate decisions for their IoT and machine learning applications.
AWS IoT Analytics collects, pre-processes, enriches, stores, and analyzes IoT device data at scale so companies can easily identify things like the average distance traveled for a fleet of connected vehicles, or how many doors are locked after work hours in a smart building, or assess the performance of devices over time to predict maintenance issues and better react to changing environmental conditions. With AWS IoT Analytics, customers don’t have to worry about all the cost and complexity typically required to build their own IoT analytics platform. AWS IoT Analytics is available today in the US East-1 (N. Virginia), US East-2 (Ohio), US West (Oregon), and EU (Ireland) regions, with support for additional regions coming soon.
“AWS IoT Analytics is the easiest way to run analytics on IoT data. Now, customers can act on the large volumes of IoT data generated by their connected devices with powerful analytics capabilities ranging from simple queries to sophisticated machine learning models that are specifically designed for IoT,” said Dirk Didascalou, VP, IoT, AWS. “As the scale of IoT applications continues to grow at a rapid rate, AWS IoT Analytics is designed to provide the best tools for our customers to mine their raw data, gaining insights that lead to intelligent actions.”
AWS IoT Analytics also has features like a built-in SQL query engine to answer specific business questions and more sophisticated analytics, enabling customers to understand the performance of devices, predict device failure, and perform time-series analysis. Also, AWS IoT Analytics offers access to machine learning tools with hosted Jupyter Notebooks through seamless integration with Amazon SageMaker. Customers can directly connect their IoT data to a Jupyter Notebook and build, train, and execute models at any scale right from the AWS IoT Analytics console without having to manage any of the underlying infrastructure.
Using AWS IoT Analytics, customers can apply machine learning algorithms to device data to produce a health score for each device in a fleet, prevent fraud and cyber intrusion by detecting anomalies on IoT devices, predict device failures, segment fleets of devices, and identify other rare events that may have great significance but are hard to find without analytics. And, by using Amazon QuickSight, a fast, cloud-powered business analytics service, in conjunction with AWS IoT Analytics, it is easy for customers to surface insights in easy-to-build visualizations and dashboards.
AWS IoT Analytics can accept data from any source, including external sources using an ingestion API, and integrates fully with AWS IoT Core. Launched in 2015, AWS IoT Core is a managed cloud platform that lets connected devices easily and securely interact with cloud applications and other devices. AWS IoT Analytics also stores the data for analysis, while providing customers the ability to set data retention policies.
Modjoul, Georgia Pacific, Teralytic, Siemens, OSIsoft, Pentair, 47Lining, Domo, NetFoundry, and Laird Technologies are just a few of the customers and Amazon Partner Network members using AWS IoT Analytics to uncover valuable insights within their data and use those findings to innovate across their specialized businesses.
Modjoul is a data invention company for wearable technology that is focused on keeping employees safe. “Our mission is to keep industrial workers safe, whether they’re working in or out of a vehicle,” said Eric Martinez, CEO and Founder, Modjoul. “In an eight-hour shift, we collect data 28,800 times per day from our connected activity tracker worn by each of our employees that includes 40 metrics including heart rate and activity level. With AWS IoT Analytics, we not only analyze all that health data, but also enrich it with location and environmental data, such as outdoor temperature, to get accurate analytics that prevent injuries and save lives. Today, we’re operating better and faster.”
Georgia Pacific is one of the world’s leading makers of tissue, pulp, paper, packaging, building products, and related chemicals. “At Georgia Pacific, our industry-leading dispensers allow us to deliver solutions to customers, not just sell products,” said Erik Cordsen, IoT Program Architect and Product Leader, Georgia-Pacific. “Now we are focused on making our dispensers ‘smart’ by adding sensors and connectivity that allow us to improve customer experience by providing real-time information about product levels and other statistics. With thousands of endpoints continuously feeding in data, we are using AWS IoT Analytics to enrich messages with location and product metadata in order to calculate platform health and value to our customers. AWS lets my team focus on solving the business problem instead of wrestling with technology.”
Teralytic is a soil health company focused on improving farmer’s yield by monitoring and improving the condition of their soils. “We have a network of soil-sensing IoT devices embedded in the soil from which data are collected, fed, and analyzed for us to understand the health of our customers’ agricultural ecosystems,” said Dan Casson, Vice President of Engineering, Teralytic. “We chose AWS IoT Analytics for its ability to filter outlier readings from our calculations and proactively detect issues as they arise so we can resolve them faster. In some cases, we’re able to identify and prevent issues before they occur. With AWS IoT Analytics, we use Machine Learning models to help detect situations where nutrients in the soil are at risk of leeching into ground water or runoff into surface water so the farmer can adjust the watering schedule, if needed. In addition to the environmental benefits, these machine learning models can help reduce a farmer’s costs as well as potentially increasing their yield.”
47Lining develops big data solutions and delivers big data managed services — built from underlying AWS building blocks like Amazon Redshift, Kinesis, Amazon Simple Storage Service (Amazon S3), and Amazon DynamoDB — to help customers manage their data across a variety of verticals including energy, life sciences, gaming, and financial services. “Because AWS IoT Analytics is designed around time-series data, it’s a great fit for our customers in industrial, energy, and oil & gas, who seek real-time decision support and process optimization,” said Mick Bass, Senior Vice President, Big Data Practice, 47Lining.
Domo is a computer software company that specializes in business intelligence tools and data visualization. “Since our inception in 2010, AWS has been a trusted service provider that keeps up with the demands of our dynamic business,” said Jay Heglar, Chief Strategy Officer, Domo. “We extended our relationship with AWS to IoT Analytics because we wanted a flexible option to enable faster access to machine-generated data for our customers. Through our proprietary connector to AWS IoT Analytics, we are ensuring our customers have access to one of the most innovative solutions, allowing them to leverage machine-generated data at scale.”
Laird Technologies designs, develops, manufactures, and supports wireless systems solutions and performance materials for wireless and other advanced electronics applications. “By combining our long range wireless sensor and gateway products with AWS IoT, our customers have been able to quickly and securely get data from their devices into the cloud,” said Paul Elvikis, Business Development Director for Industrial, Laird Technologies. “Unfortunately, they would often get overwhelmed with the amount of sensor data that would start coming in. Customers would struggle to figure out how to do anything with it. AWS IoT Analytics has been a great help in extending our capabilities to solve that issue for our customers.”
NetFoundry gives its customers and their applications control of their networks without any telco, hardware, or private circuit constraints. “The capabilities of AWS IoT Analytics in enabling the transformation of vast amounts of data into actionable information, without the high costs and steep learning curve of other IoT platforms, enables NetFoundry’s IoT customers to get the ROI they need,” said Michael Kochanik, Co-founder and Global Head of Channel Revenue, NetFoundry.“With AWS IoT Analytics, we can integrate IoT networking capabilities to provide our IoT customers with ‘one-stop shopping’ including data collection, networking, analysis, transformations, storage and visualization. Partnering with AWS enables our customers to get integrated, end-to-end agility, security, performance and cost efficiency at scale.”
AWS offers over 125 fully featured services for compute, storage, databases, networking, analytics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 54 Availability Zones (AZs) within 18 geographic regions and one Local Region around the world, spanning the U.S., Australia, Brazil, Canada, China, France, Germany, India, Ireland, Japan, Korea, Singapore, and the UK.
by Gary Mintchell | May 14, 2018 | Automation, Networking, News, Standards
Hannover Messe continues to reflect the trend of companies joining alliances to develop and promote standards and interoperability. While I did not have an interview with the Avnu Alliance while I was in Hannover, I talked with some members and obtained other information. Avnu Alliance promotes adoption of the Time Sensitive Networking (TSN) extension to Ethernet.
Specifically, Avnu Alliance is a community creating an interoperable ecosystem of low-latency, time-synchronized, highly reliable networked devices using open standards. Avnu creates comprehensive certification programs to ensure interoperability of networked devices. The foundational technology enables deterministic synchronized networking based on IEEE Audio Video Bridging (AVB) / Time Sensitive Networking (TSN) base standards. The Alliance, in conjunction with other complimentary standards bodies and alliances, provides a united network foundation for use in professional AV, automotive, industrial control and consumer segments.
The adoption pace of TSN from 2017 to 2018 was amazing.
I always drop by the Industrial Internet Consortium (IIC) area at Hannover and check out the TSN Testbed for Flexible Manufacturing. The testbed was developed with two major goals – to show TSN’s readiness to accelerate the marketplace; and to show the business value of TSN in converged, deterministic IIoT networks. Momentum is increasing for the testbed, with the IIC hosting its 10th plugfest in an 18-month timeframe at the Bosch Rexroth facility in Frankfurt, Germany and its 9th plugfest, which was held in Austin, TX in February at National Instruments (NI) headquarters following a joint workshop on interoperability with Avnu Alliance. The TSN Testbed recently integrated test tools from Avnu Alliance members, Calnex, Ixia and Spirent into plugfest activities, and demonstrated interoperability of TSN devices from more than 25 companies performing real-time automation and control automation functions over TSN.
Any Avnu Alliance member is welcome to join the IIC TSN Testbed or to participate in a plugfest. Upcoming plugfests will be held in Austin, TX from June 26-29, 2018 and in Stuttgart from July 24-27, 2018.
The Edge Computing Consortium (ECC) along with members and Avnu Alliance, hosted a press conference to announce new developments surrounding the newly created OPC UA TSN testbed. The testbed demonstrates six major IIoT scenarios mimicking processes found in smart manufacturing settings and utilizing products across different TSN vendors. Avnu Alliance is a key partner supporting the development of the testbed with the ECC in the shared goal of enabling manufacturers to test their products for interoperability and conduct trials of real-world systems as an early check for problems.
Tom Weingartner, Avnu Alliance member and Analog Devices’ marketing director for Deterministic Ethernet Technology Group, represented the Alliance at an announcement ceremony.
Paul Didier, Avnu Alliance member and IoT solutions architect, Cisco delivered a talk at the Industrie 4.0 meet the Industrial Internet Forum, in a presentation titled “Time Sensitive Networks – Where does the technology stand and what to expect”. He will provide an update on TSN and how manufacturers, alliances and liaison groups are working together to advance the technology and its implementation in the IIoT.
Paul will present an additional lecture for the Forum on “Modernizing Your Industrial Manufacturing Network”. The presentation will follow the findings coming out of the IIC TSN Testbed and its capabilities, including information on how manufacturing automation and control infrastructure vendors and key decision-makers can leverage TSN for a variety of operational benefits, including increased connectivity between devices and the ability to extract and analyze valuable information through interconnectivity.
“HANNOVER continues to be a key industry event for both Avnu Alliance members and liaison groups that we work with to educate and increase awareness of TSN as a solution for the growing IIoT,” said Todd Walter, Avnu Alliance Industrial Segment Leader and Chief Marketing Manager at NI. “Whether through the developments coming from the TSN testbeds, speaking engagements or product demonstrations, our members and partners are committed to creating an interoperable TSN network that gives all industrial devices a more streamlined path to participating in the TSN ecosystem.
by Gary Mintchell | May 1, 2018 | Automation, Internet of Things
I went from Germany to Las Vegas and the time change screwed with my posting schedule. So…I am finally finishing up my Hannover Messe reporting before I begin with my recent trip.
My last post detailed the first round of briefings with Hewlett Packard Enterprise. Today I’ll finish up.
But first, a digression.
OPC
Misinformation about what exactly OPC UA is continues to circulate within the industry. I had at least three conversations where people referred to OPC as proprietary. Plus OPC and MQTT are mistakenly considered competitive rather than complementary. OPC Foundation still has some evangelizing to accomplish.
A few years ago it appeared that major automation vendors were ignoring OPC and its interoperability tending toward self-encased solutions. In fact, I got dissed by some dude on YouTube for a report I did on that subject.
Time has passed. More and more people and companies recognize the value of interoperability and OPC UA. No doubt the PubSub helps in some cases. And without a doubt the combination of OPC UA and TSN is enticing to many.
HPE
HPE has devised an application dubbed “Remote Visual Guidance.” It began with an eLearning application HPE MyRoom. Integrated with a hard hat, a camera, and glasses that project an image to the user, the system enables remote support from an expert who may not be able to fly to the site. Imagine working in a remote location such as an offshore oil rig where flying in an expert is both dangerous and expensive, for example. The system comes in three versions—wearable say integrated with a hard hat, smart phone app, or tablet app. Therefore, the three versions are No hands, 1 hand, and 2 hands). Try this for a potential use case for a value add from an OEM. The OEM bundles the app with its machine. This gives the customer direct contact with remote expert for the cost of perhaps a service contract.
I had a good conversation with HPE’s Christian Reichenbach on Blockchain technology. I believe this technology is quickly moving past hype into something we can use. The concepts of trusted transaction and ledger have immediate appeal for industries such as pharma manufacturing. We can think of many more.
Reichenbach identifies three waves of blockchain.
Wave One is personal exemplified by crypto currency—the Bitcoin that garners most of the press
Wave Two came with Enterprise to Enterprise transactions. For example, he pointed to the vision system QA demo at the HPE stand. It uses blockchain to send QA report as a secure, trusted transaction that includes a record.
Wave Three includes Things to Things. This means systems around products leading to systems of systems thinking. Things become autonomous actors. They contract with each other with no middle man. It includes ledger systems. Let’s take the example of an HPE Edge Gateway plus Etherium (an HPE partner). Perhaps it’s the same concept as loyalty card scanning and giving you value for using it. Let’s look at a car. Currently there are lots of sensors but no marketplace to exploit all that data. Say we take Edgeline device connected to CANbus of the car. Then, say, connect to the rain sensor or a sensor in the shock absorber. Previously the end user gave data away for free, but now maybe the car makes a smart contract with weather channel or Waze and sells the data.
One last item I gleaned from the Microsoft booth. HPE has a starter kit to help users easily connect devices to the cloud using HPE Edgeline, Softing (OPC UA kit), and Microsoft Azure.
Overall analysis from HPE visit at Hannover was that IoT has matured in a sense from a department with a product to infusing into the entire manufacturing product and service portfolio.
by Gary Mintchell | Apr 24, 2018 | Automation, Manufacturing IT, Technology
Most of my time involves Hewlett Packard Enterprise (HPE) where I am devoting about 2.5 hours a day to interviews. As one person asked, what does HPE have to offer. Briefly described, HPE has a variety of compute devices, services, and partnerships.
One application was a prescriptive maintenance solution where IoT data is analyzed and the CMMS is notified to initiate a work order. We are not in the era of self-healing machines, yet, but we are one step closer where the machine can begin a maintenance workflow with information about what to repair.
The SecureEdge Data Center combines enclosures from Rittal, I/O from ABB, and Edgeline edge computing hardware from HPE into a scalable industrial center to provide IIoT data to the enterprise from ABB robotics and automation.
As a former machine vision integrator, I loved the video analytics demo application showing Relimetrics software to analyze servers in manufacturing. In this case, the application read a 2D barcode to determine the build, discovered the bill of materials, and then checked that all the proper components were in the assembly, that everything was properly installed, and there were no other defects.
One application of Edgeline edge compute devices, for example, is in partnership with National Instruments to accomplish complex testing at the edge with communication to the cloud as necessary. Edge compute is also important in autonomous vehicles where decisions must be quickly executed locally, but large amounts of data must also be communicated to the cloud for further analysis.
Speaking of partnerships, HPE has forged significant partnerships in the industrial world with ABB, GE Digital, OSIsoft, PTC (Kepware and ThingWorx), Rittal, and Schneider Electric. Most of these involve a significant IT infrastructure including power at the Edge from HPE along with data and connectivity plus solutions targeted to various industrial applications.
