by Gary Mintchell | Jan 29, 2021 | Manufacturing IT, Operations Management
The press release found its way into my email client proclaiming an update to a “modern edge” product from Litmus. Since I’m a fanatic on defining things, I wound up talking with co-founders Vatsal Shah and John Younes. I had written about the company in September, but it has been around since 2014.
The IT company conferences I’ve been attending have been all over the concept of “edge”, and OT companies have recently picked up the phrase. For an IT company, edge is at the end of the network with a device located in close proximity to where the work is done. I think for OT companies, it’s a similar, but opposite direction, view. The Litmus product is software that can reside on an amazing variety of compute devices.
Litmus contains a number of interesting and useful features. I was most captivated with the implementation of an app marketplace. There is a “public” one for apps from Litmus or third parties that a customer can install. There is also a “private” marketplace. For example, say an engineer in one plant solves a problem with an added app for their Litmus application. That engineer can add it to the private app store for use by engineers in other plants.
At the end of this post, I’ll include some edge definitions from Litmus that I found helpful. First, here is the latest news.
Litmus announced the release of Litmus Edge 3.0, a modern edge platform to collect and analyze data, build and run applications, and integrate edge data with any cloud or enterprise system. Litmus Edge 3.0 adds more device drivers to bring the industry-leading total to more than 250, with enhanced analytics, improved integration connectors, digital twin support, and expanded device management features.
“Litmus Edge is the only modern edge platform on the market that connects to all industrial assets and provides a complete data picture to improve industrial operations,” said Vatsal Shah, co-founder and CEO of Litmus. “Version 3.0 expands upon the product that already leads the industry with more device drivers, pre-built analytics and OT/IT integration capabilities, so customers can capture edge data and use it to perform local analytics or advanced use cases like machine learning and AI in the cloud.”
New features of Litmus Edge 3.0 include:
- Launched second generation industrial communication drivers focusing on security and scalability for southbound communications
- Enhanced Ready Analytics which now includes the ability to run Tensorflow and other machine learning algorithms natively on real-time ingested data
- Flows Manager updated to allow multiple instances of Flows – which can be tightly integrated or scaled or isolated with sandbox and production logics
- Enhanced cloud and enterprise Integration connectors including support for Splunk, Oracle DB, and other databases
- Improved user interface for application marketplace for one-click application orchestration
- Device management improvements including security, backup/restore and digital twin templates
Litmus Edge is a modern edge platform that collects data from any industrial asset, offers pre-built applications, KPIs and analytics, provides the ability to build and run custom applications, and integrates data with any cloud or enterprise system. Litmus Edge is easy to use and easy to deploy, offering the edge connectivity and data intelligence needed to power industrial use cases ranging from predictive maintenance to machine learning.
Litmus transforms the way companies enable Industrial IoT, Industry 4.0 and Digital Transformation with one goal in mind – unmatched time-to-value. Our modern edge platform for industry provides instant data connectivity, ready-to-use analytics, and the ability to orchestrate applications at scale. Litmus liberates the data locked in any industrial system to transform critical edge data into actionable intelligence that can power predictive maintenance, condition-based monitoring, and machine learning. Customers include 10+ Fortune 500 manufacturing companies, while partners like Siemens, HPE, Intel and SNC Lavalin expand the Company’s path to market.
Additional information:
The edge is focused on bringing computing as close to the data source as possible. The edge means running fewer processes in cloud and enterprise systems and moving them closer to the devices generating data, such as a standalone computer, an IoT device, or an edge server. Localizing computing minimizes the amount of long-distance communication between a client and server, thus transforming the way data is handled, processed, and delivered.
Industrial edge computing refers to the process of connecting all assets used in manufacturing, oil and gas, energy, transportation and more. Industrial edge computing analyzes all of the data at the asset and processes it instantly for real-time analytics or to integrate optimized data into cloud systems for further processing.
Edge and cloud technologies need to work together. To suggest one offers greater value over the other is simply not true. The edge is valuable for its ability to process high-volume data in real-time and handle complex analytics at the data source. The cloud is valuable for its ability to aggregate and analyze volumes of data from all data sources, including the edge.
The edge has three main components. Edge connectivity is the ability to connect to any industrial system and collect and normalize data for immediate use. Edge intelligence is concentrating data processing and analytics functions at the edge to take action and derive value at the data source. Edge orchestration is the ability to create, deploy, manage and update edge applications.
The vast importance of the edge is beginning to come to light as more industrial use cases are enabled. The edge powers preventative maintenance, condition-based monitoring, OEE, vision systems, quality improvements and more. Edge data can also power more advanced use cases like artificial intelligence and machine learning in the cloud. The intelligent edge is powering significant operations and process improvements.
by Gary Mintchell | Jan 28, 2021 | Asset Performance Management, Business, Manufacturing IT, Operations Management
About six months ago, ABB completed a divestiture of about 80% of its holding in ABB Power Grid business, and Hitachi acquired it. The new business, a joint venture, is called Hitachi ABB Power Grids. Today, it announced the integration of its Digital Enterprise solution with Hitachi Vantara’s Lumada portfolio of digital solutions and services for turning data into insights.
The two Hitachi business entities have agreed to rebrand the DE components as Lumada Asset Performance Management (APM), Lumada Enterprise Asset Management (EAM), and Lumada Field Service Management (FSM), adding to the growing portfolio of DataOps and Industrial IoT solutions.
The DE portfolio of solutions and its predecessors enable customers spanning multiple global industries to operate, analyze and optimize over $4 trillion of assets every day. With the incorporation of the DE portfolio into Lumada, this experience is further complemented by a leading technology engine to deliver access to information, systems, people and analytics across asset-intensive organizations.
With Digital Enterprise’s incorporation into Lumada, Hitachi ABB Power Grids’ energy domain experience will be augmented by Hitachi’s Lumada Industrial IoT platform. Hitachi was recently named a Leader in the 2020 Gartner Magic Quadrant for Industrial IoT Platforms based on Gartner Inc.’s evaluation of the company and its Lumada IoT software.
“Our software solutions and Lumada are highly complementary,” said Massimo Danieli, managing director, grid automation business unit, Hitachi ABB Power Grids. “Combining best-in-class Lumada IoT capabilities and the domain expertise built into Digital Enterprise applications provides both new and existing customers unparalleled flexibility and faster time to value, while preserving the value of their past software investments. The journey we began with our customers as part of the Digital Enterprise evolution story has become broader and more compelling, as we join the Lumada ecosystem.”
“Lumada Enterprise Asset Management and Field Service Management allow us to seamlessly expand our Ellipse EAM, enabling us to share information across all parts of our organization, tearing down silos and giving us the opportunity to formulate a longer-term, holistic strategy that reflects our specific business outcomes,” said Brian Green, general manager, asset management, from the Australian Rail Track Corporation (ARTC). “In addition, implementing these solutions allows us to optimize the quality of the data we collect and ensure safe, compliant and efficient business operations.”
“Bringing these solutions that each encapsulate deep domain expertise into the greater Lumada ecosystem gives customers an extremely powerful combination of tools to modernize their business,” said Chris Scheefer, senior vice president, Industry Practice, Hitachi Vantara. “The holistic view of assets and information provided by Lumada allows leadership to analyze and react in real-time, enabling efficient, effective operations and a foundation to create a more sustainable future.”
DE and Lumada also share core foundational features: a modern microservices design, vendor-agnostic interoperability, and a flexible deployment model, including cloud, on-premises and hybrid.
With the combination of Hitachi ABB Power Grids’ Digital Enterprise application portfolio and Hitachi’s Lumada solutions offered by Hitachi Vantara, customers will be able to benefit from additional data services including data integration, data cataloging, edge intelligence, data management, analytics and more.
The new integrated Lumada portfolio will offer advantages to customers in the following key areas:
1. Digital Transformation & Data Modernization – improving access to and insights from data
2. Connected Asset Performance – helping to predict and prevent asset failures
3. Intelligent Operations Management – improving oversight and maintenance of assets
4. Health, Safety & Environment – enabling safer environments for workers and the public
by Gary Mintchell | Jan 27, 2021 | Automation, Internet of Things, Sensors
Sometimes similar news comes in bunches, a little bit like a graph of an FFT. News from Swift Sensors and ABB take us from Covid to Space and back.
Swift Sensors Launches Sub-Zero Temperature Sensor to Meet COVID-19 Vaccine Monitoring and Storage Requirements
24/7 cloud-based wireless monitoring ensures vaccines are stored throughout the cold chain in the required sub-zero temperature ranges down to -100°C.
Swift Sensors, a provider of industrial IoT sensor solutions, launched a secure wireless vaccine storage unit monitoring and alert system to enable medical facilities and pharmacies to remotely monitor COVID-19 vaccine storage temperatures, automate data logging, and respond quickly in case of an equipment problem or power failure.
As vaccine suppliers and public health agencies expand the number of locations for vaccine delivery, pharmacies and clinics must quickly and safely store the vaccines to preserve the vaccines’ efficacy, prevent waste, and comply with data monitoring regulations. Swift Sensors has developed a wireless sensor system to achieve these goals.
“Data loggers have historically been used in cold-chain monitoring of vaccines, pharmaceuticals, and other critical perishable items. However, they lack the low cost, simplicity, and connectivity of wireless sensors connected to the internet,” said Ray Almgren, Swift Sensors CEO. “Our new sub-zero temperature sensor delivers an all-in-one, cost-effective solution for the safe and fast distribution and delivery of much-needed vaccines.”
Each Swift Sensors vaccine package includes at least one wireless remote temperature sensor to relay storage temperature data to an included wireless gateway.
The gateway sends data to a secure cloud-based Swift Sensors Console account. Pharmacy and clinic managers can view temperatures in real time on their computer or mobile device. They can also receive instant alerts via text, voice or email if the storage unit temperature exceeds established thresholds.
“Pharmacies and clinics can use our new sub-zero temperature sensor to monitor the super-cold temperatures the Pfizer vaccine requires or use our standard wireless remote temperature sensor to monitor Moderna vaccine storage conditions,” Almgren said. “Installation typically requires only a few minutes, and the device batteries last six to eight years.”
The Swift Sensors Console stores historical temperature readings so pharmacies and clinics can easily comply with CDC and state health department data logging requirements, without having to spend employee time manually recording or updating temperature data.
ABB sensor onboard SpaceX rocket to detect greenhouse gas emissions
An optical sensor manufactured by ABB was deployed with the successful launch of satellite Hugo from GHGSat, the emerging leader in greenhouse gas sensing services in space.
The ABB supplied optical sensor can map methane emissions from space at a resolution that is 100 times higher than any other sensors. Whilst previously only larger regions could be surveyed, for the first time the new greater granularity now allows the identification of the source of emissions. An additional nine units are currently under manufacture at ABB to be launched by the end of 2022 ready to be on-board across the first private satellite constellation dedicated to emission measurement.
Space offers the ideal location to freely monitor emissions across jurisdictions and quantitatively report on improvements. The ABB sensors will provide valuable insights which will enable governments and industries around the world to meet their emission reduction targets and reduce the negative impact on global warming.
With its involvement in the Canadian SCISAT mission and the Japanese GOSAT series of satellites, ABB has been at the forefront of the field of greenhouse gas sensing from space for more than two decades. ABB optical equipment already in space cumulates more than 100 years of reliable operation. The SCISAT sensor tracks long-term subtle composition changes in the earth’s atmosphere down to parts per trillion of more than 70 molecules and pollutants since 2003. Weather agencies across the world base their predictions on ABB equipment flying onboard the US National Oceanographic and Atmospheric Administration (NOAA) weather satellites (NPP and JPSS), which saves lives by improving the timeliness and accuracy of weather forecasts for up to seven days.
ABB is also a global leader in earthbound continuous emission monitoring with over 60,000 systems installed in more than 50 countries worldwide. Continuous Emissions Monitoring Systems (CEMS) continuously record and evaluate emission data across all industries. They provide important information for the environmental and economic operation of production facilities. The range includes the ACF5000 that accurately and reliably monitors up to 15 gas components simultaneously.
New ABB emission monitoring solution helps the maritime industry achieve decarbonization targets
The launch of ABB’s CEMcaptain will help shipping comply with the sulphur emission regulations that were enforced in 2020 and keep in check their CO2 footprint.
In January 2020, the low sulphur and nitrous oxide emission limits in the International Maritime Organization regulations became effective worldwide. CEMcaptain is a powerful emissions monitoring system from ABB designed to help the maritime industry meet these new regulations and become more sustainable. Its measurement and digital capabilities increase on-board safety, provide process optimization and substantially reduce ownership costs. By consistently achieving 98 percent and more uptime, the new system not only requires less maintenance effort but also saves time otherwise spent on handling non-compliance issues.
Designed with busy mariners and a regularly changing crew in mind, CEMcaptain is a multi-component analyzer system that continuously provides real-time data offering reliable measurement of emissions with the highest stability. Operating in even the harshest of conditions it integrates analyzer modules and sample handling components in a standalone cabinet, making installation easy.
Equipped with ABB’s renowned Uras26 non-dispersive IR gas analyzer, CEMcaptain simultaneously and continuously measures sulphur dioxide (SO2) and carbon dioxide (CO2) in line with regulation requirements. Each analyzer has two separate gas paths to allow for continuous CO2/SO2 measurement of separate streams, with up to four different components per analyzer module.
Fast fault reporting, diagnosis and repair are achieved via the on-site and remote digital services which help operators get closer to 100 percent availability for their gas analysis instrumentation. Dynamic QR codes are integrated into the ABB CEMcaptain system display panel. All relevant diagnostic information can be collected from the analyzer via a scanned code and transferred to ABB support. This means that maritime instrumentation technicians can send real-time information to an ABB service expert to get immediate guidance on appropriate maintenance. ABB Ability™ Remote Assistance with secured connectivity direct to ABB support is also offered for real-time solutions to problems. These features reduce the costly training of changing crews as well as the number of experts required on board. They also increase on-board safety by reducing crew exposure to emissions.
CEMcaptain GAA610-M is approved by all major classification societies (DNV GL, ABS Group, Lloyds Register, Bureau Veritas, ClassNK, Korean Register).
by Gary Mintchell | Jan 26, 2021 | Education, Personal Development, Workforce
I’ve been acquainted with Mike Nager for many years through business. We ran into each other a few years ago when he had switched from product management to leading the education team for an automation supplier.
He sent a copy of a book he’s just published for Kindle, The Smart Student’s Guide To Smart Manufacturing and Industry 4.0. It’s a subject I’m deeply interested in, so I checked it out.
I rate this book highly because the author accomplishes what he set out to do–“This book will introduce you to exciting career opportunities that smart manufacturing provides today.”
He continues, “Manufacturing output, which is essentially the amount of goods made in America, rises every year. The U.S. now produces more products than at any other time in history. Smart Manufacturing, also referred to as Industry 4.0, is starting to shake up the previous worldwide business model of off-shoring manufacturing operations to areas with low labor rates by making labor rates less relevant. You have an opportunity to join the industry as it reinvents itself.”
It reminds me of books given to me to read when I was in high school to entice me into an engineering career. It is understandably basic, but it is also inclusive. There is so much more to manufacturing and engineering than when I was making that decision. And Nager covers all the facets from highly educated process engineers to skilled technicians. And how to get there.
Half of the book is devoted to persuading students about the importance of manufacturing–both to the country’s defense and to the economic health of the area and country. Becoming an important part of manufacturing is not only a great career for the student, it also enables the student to be a contributing member of society. The remaining part discusses the wide variety of engineering and technical areas a student could choose from according to their interests and talents.
Nager covers technologies involved including hardware products and software concluding with a review of the so-called “soft skills” such as leadership that are essential to success no matter what the career path.
Get this book, order many. Pass them along to every junior high and high school student you know who could even remotely be interested in a manufacturing career.
by Gary Mintchell | Jan 25, 2021 | Asset Performance Management, Manufacturing IT, Operations Management
Amazon popped up on a recent post regarding Amazon Web Services. This news came to me from the analyst firm Interact Analysis. I’ve talked with executives there a few times, and I generally like the approach they take. I’m amused that IT companies think maintenance when they think manufacturing and then add predictive analytics, which they all have, combining them into predictive maintenance looking for a killer app.
Anyway, this analysis by Blake Griffin, senior analyst at Interact Analysis, has food for thought. Just what is Amazon up to with the manufacturing space?
- “The full development of Amazon’s industrial digitalization offering represents the first time a supplier has the ability to provide both the cloud storage and analytic capabilities under one entity”
- “If customers are looking to utilize the cloud for their industrial digitalization initiatives, Amazon would represent the fewest number of touchpoints between customer and supplier during the sales process”
- “Additionally, many manufacturers may already be using AWS for cloud storage but have yet to invest into further industrial digitalization technology. In these scenarios, Amazon would already have a ‘foot in the door’”
- Amazon offers an on-premise version of AWS for low latency applications – AWS Outpost: “In our opinion however, outpost will also serve as an option for customers looking to implement predictive maintenance who may be shy of hosting their operational data on the cloud… AWS Outpost will be regularly updated and patched… which ensures that users are still able to take advantage of the scale at which AWS operates”
On December 1st, 2020, Amazon announced a suite of new AWS machine learning services. To many, this announcement appeared to be Amazon’s launching off point towards being a major supplier of predictive maintenance solutions. However, this announcement follows a long history of Amazon carving out its capabilities in industrial digitalization. Since the ecommerce behemoth’s 2018 release of AWS IoT Sitewise, a service which enables its users to gather and organize asset health related data housed in repositories such as a historian, Amazon has consistently added to its industrial digitalization offering. Now, the company has a highly competitive solution with one capability completely unique to Amazon.
Amazon’s Industrial Digitalization Offering Has Been Developing for Years
In some ways, Amazon’s announcement of its new suite of machine learning services represents a rounding out of a predictive maintenance offering rather than a jumping off point. When manufacturers are looking at implementing predictive maintenance into their facilities, they are asking these fundamental questions:
- Which assets do I have visibility into already? How can I leverage this data?
- Which assets do I not have visibility into? What can I do to change that?
The announcement of AWS IoT Sitewise was Amazon’s solution to the first question. Many manufacturers in process industries generate large amounts of data from the devices controlling their machines. This data is often stored in a historian and without the tooling necessary to effectively manage and analyze such data, much of its value can be lost. AWS IoT Sitewise was developed so manufacturers could more effectively utilize this data for condition monitoring/predictive maintenance purposes. The solution is deployed through software housed in a gateway which then communicates the collected data to the AWS cloud. In our opinion, this marked Amazon’s true entry into the predictive maintenance market. Strategically, this was a logical first move. Amazon already had a wealth of analytical tools it could deploy to make use of data housed in a historian, the only thing needed was a mechanism for gathering and organizing that data to be analyzed.
Fast forward to Amazon’s recent announcement and we see the company moving to provide a solution to question two. One asset that is cited often as being “offline” from a condition data perspective are the mechanical portions of a motor driven system i.e. induction motors, gearboxes, bearings blocks, etc. These components are numerous throughout factory floors and their failure can represent significant loss of production if they are part of an application critical process. The industry has responded to this need by offering smart sensors, a wireless enabled sensor which can be connected to the side of a motor for purposes of gathering data on vibration and temperature behavior. These two data points, when combined with machine learning algorithms, can quickly illuminate what kind of stress motor components are facing and alert its users of problems ahead of failure.
One of the services announced in late 2020 has been coined Amazon Monitron. The solution utilizes smart sensors and gateways produced by Amazon to offer up data on the health of motor system equipment; effectively solving the problem of gathering data on assets not being monitored via historian data. This solution is in direct competition with predictive maintenance providers like ABB, Siemens, SKF, etc. In our view, the announcement of Monitron means Amazon now has a solution which fully addresses the needs of manufacturers looking to invest in predictive maintenance as part of a broader industrial digitalization initiative. Amazon’s utilization of data housed in a historian, combined with its smart sensor offering and vast analytics capability offered through AWS, make this solution as competitive as any on the market. Amazon does however have one distinct advantage over competition however: being a provider of cloud storage.
Amazon’s Unique Capability: Cloud Storage Ownership
Every platform offered by the major providers of predictive maintenance are built on cloud storage technology offered largely by either AWS or Microsoft Azure. ABB Ability cites Microsoft Azure as the landscape in which Ability operates. Similarly, Schneider Electric’s Ecostuxure platform utilizes Microsoft Azure. Siemens Mindsphere has developed the capability to be used with either AWS or Azure, announcing its compatibility with the latter in 2018. The full development of Amazon’s industrial digitalization offering represents the first time a supplier has the ability to provide both the cloud storage and analytic capabilities under one entity.
It is difficult to foresee what impact this will have on the partnerships AWS has in place with current industrial digitalization providers. What is easy to see however are the numerous advantages Amazon will have in potentially winning the business of those investing into industrial digitalization for the first time. If customers are looking to utilize the cloud for their industrial digitalization initiatives, Amazon would represent the fewest number of touchpoints between customer and supplier during the sales process. Additionally, many manufacturers may already be using AWS for cloud storage but have yet to invest into further industrial digitalization technology. In these scenarios, Amazon would already have a ‘foot in the door’ which would yield them an advantage when the time comes for users to begin evaluating providers of digitalization.
Amazon’s AWS Outpost Helps Overcome a Major Barrier to Predictive Maintenance Adoption
One of the largest barriers facing suppliers of predictive maintenance solutions is manufacturers’ reluctance to host its operational data on the cloud. Recently, Interact Analysis partnered with the Association for Packaging and Processing Technologies (PMMI) to produce a white paper and accompanying survey pertaining to adoption of predictive maintenance technology within the packaging industry. The whitepaper and survey results are available for download for free via this link. One of the questions asked in the survey looked at the adoption of predictive maintenance within OEM and system integrator offerings. “Our customers will not allow remote access to their machinery” received the second highest weighted score according to the survey.
Question: To what extent are the following statements describing the adoption of predictive maintenance (PdM) technologies at your company, true or false?
- We are not familiar with PdM technology.
- The added cost of PdM technology is too high to justify.
- We do not want to have to pay for an ongoing subscription to access sensor data from an automation vendor.
- The technology is too new.
- We currently offer machines with PdM technology
- None of our customers have expressed interest in PdM technology
- Our customers will not allow remote access to their machinery (remote monitoring)
This hesitancy by users to allow access to operational data has led suppliers to develop solutions which, instead of aggregating and analyzing data in the cloud, host their data for analysis onsite.
Amazon has addressed this concern by offering an on-premise version of AWS. This on-premise version of AWS, termed AWS Outpost, was released in 2019 and is designed to serve applications requiring low latency. In our opinion however, outpost will also serve as an option for customers looking to implement predictive maintenance who may be shy of hosting their operational data on the cloud. Keeping data onsite as opposed to in the cloud ensures the door to the OT network remains closed; something many manufacturers are keen to maintain.
Having the power of a modular cloud system like AWS on-premise is an incredibly powerful development in the predictive maintenance market. AWS Outpost will be regularly updated and patched by a regional AWS team which ensures that users are still able to take advantage of the scale at which AWS operates. This is an important consideration when working with machine learning algorithms which become more accurate when deployed at scale. Current on-premise predictive maintenance solutions sacrifice this accuracy in favor of the increased security which on-premise brings. With AWS Outpost, users will no longer have to make that sacrifice.
Additionally, if you define an edge device as the point at which data is pushed to the cloud, this solution effectively eliminates the need for such devices thus simplifying the overall architecture.
Final Thoughts
At the very least, this announcement should be taken as a signpost of future growth within an already fast-growing predictive maintenance market. Amazon does not enter markets which are expected to appreciate modestly; it enters markets whose opportunity could one day be worth billions of dollars. The amount of time spent developing, releasing, and improving upon Amazon’s industrial digitalization offering should be indicative of the faith the company has in the future of this market.
