by Gary Mintchell | Jul 30, 2018 | Commentary, Technology
Everybody has a list of transformative technologies. A news release from an advisory firm, ABI Research, came my way a few weeks ago. Its analysts came together and compiled a list of eight technologies they feel will be transformative in manufacturing and then they fit them with Smart Manufacturing. That latter phrase is one of the descriptors for the new wave of manufacturing strategy and technology.
We will have difficulty contesting the list. Most of these are, indeed, already well along the adoption path. I find it interesting that they refer to IIoT platforms, but they don’t view those as transforming technologies but rather as a sort of sandbox for the technologies to play in.
[This is a Gary aside—when an analyst firm makes a list of suppliers, I’d advise not considering it to be comprehensive. Rather the list is usually comprised of companies that the firm’s analysts get to sit down with and receive in-depth briefings.]
The ABI report identifies eight transformative technologies:
1 Additive manufacturing
2 Artificial intelligence (AI) and machine learning (ML)
3 Augmented reality (AR)
4 Blockchain
5 Digital twins
6 Edge intelligence
7 Industrial Internet of Things (IIoT) platforms
8 Robotics
From the ABI news release, “The manufacturing sector has already seen increased adoption of IIoT platforms and edge intelligence. Over the next ten years, manufacturers will start to piece together the other new technologies that will eventually lead to more dynamic factories less dependent on fixed assembly lines and immobile assets. Each step in this transformation will make plants and their workers more productive.”
“Manufacturers want technologies they can implement now without disrupting their operations,” says Pierce Owen, Principal Analyst at ABI Research. “They will change the way their employees perform jobs with technology if it will make them more productive, but they have no desire to rip out their entire infrastructure to try something new. This means technologies that can leverage existing equipment and infrastructure, such as edge intelligence, have the most immediate opportunity.”
ABI summary of its research
The transition towards a lights-out factory has started, but such a major disruption will require an overhaul of workforces, IT architecture, physical facilities and equipment and full integration of dozens of new technologies including connectivity, additive manufacturing, drones, mobile collaborative robotics, IIoT platforms and AI.
IIoT platforms must support many of these other technologies to better integrate them with the enterprise and each other. Those that can connect and support equipment from multiple manufacturers, such as PTC Thingworx and Telit deviceWISE, will last.
After decades of producing little more than prototypes, the AM winter has ended and new growth has sprung up. GE placed significant bets on AM by acquiring Arcam and Concept laser in 2016, and Siemens announced an AM platform in April 2018. Other leading AM specialists include EOS, Stratasys, HP and 3D Systems.
ML capabilities and simulation software have made digital twins extremely useful for product development, production planning, product-aaS, asset monitoring and performance optimization. Companies with assets that they cannot easily inspect regularly will significantly benefit from exact, 3D digital twins, and companies that manufacture high-value assets should offer digital twin monitoring as-a-service for new revenue streams. Innovative vendors in digital twins and simulation software include PTC, SAP, Siemens, and ANSYS.
The above technologies have already started to converge, and robotics provide a physical representation of this convergence. Robotics use AI and computer vision and connect to IIoT platforms where they have digital twins. This connectivity and AI will increase in importance as more cobots join the assembly line and work alongside humans. The robotics vendors that can integrate the most deeply with other transformative technologies have the biggest opportunity. Such vendors include the likes of ABB, KUKA, FANUC, Universal Robots, Rethink Robotics and Yaskawa.
“The vendors that open up their technologies and integrate with both existing equipment and infrastructure and other new transformative technologies will carve out a share of this growing opportunity. Implementation will go step-by-step over multiple decades, but ultimately, how we produce goods will change drastically from what we see today,” concludes Owen.
by Gary Mintchell | Jul 27, 2018 | Internet of Things, Organizations
Platforms that serve to expedite the interaction and collaboration of apps in the Internet of Things (IoT) are sort of the next new thing. There are several that some of the IT analyst firms are following. Trouble is the term allows for a wide variety.
One I’ve written about several times here and here and here is open source developed under the auspices of the Linux Foundation with major leadership and contributions by Dell Technologies. It’s called the EdgeX Foundry. The initiative includes 47 member companies.
The second major release of the platform (California) has just seen the light of day. I picked up information from a blog post by Jim White, Vice Chair of the Technical Steering Committee and Distinguished Engineer and Project Lead of the IoT Platform Development Team within Dell Technologies IoT Solutions Division.
Following is a lightly edited version of his blog concerning the announcement.
While EdgeX is only a year old, our community is demonstrating its staying power with the second major release in its first year. The California release, which follows Barcelona, shows the commitment and dedication of many who see the importance and potential of developing a flexible, open source, IoT software platform for the edge that provides connectivity and interoperability while still allowing value add.
So, what is new with the California release? A lot! But before we get into the details, I want to highlight that the biggest focus of this release was to introduce a few key security capabilities and to make EdgeX smaller and faster.
Security
EdgeX began its existence without security and organizations wanting to leverage the platform had to add their own security capability. Today, EdgeX incorporates some of the first security elements. These initial elements, while useful on their own, are essential building blocks to additional security features in the future.
The first security elements include a reverse proxy that helps protect the REST API communications and a secrets store. With the EdgeX reverse proxy in place – as provided by incorporating an open source product called Kong – any external client of an EdgeX micro service must first authenticate themselves before successfully calling on an EdgeX API.
The secure storage facility was provided by incorporating the open source Vault (Hashicorp) product, and it allows items such as username/password credentials, certificates, secure tokens, etc. to be persisted and protected within EdgeX. These types of “secrets” will allow EdgeX to, for example, encrypt data, make HTTPS calls to the enterprise, or connect EdgeX to a cloud provider in a secure manner.
Performance and Scalability
The EdgeX Foundry Technical Steering Committee decided early last year in the project’s formation that we would release twice a year – once in April and once in October. You probably noticed that it’s not April.
Last year, we decided that EdgeX needed to be smaller and faster to better function effectively at “the edge”, which the largely-Java code from the seed donation was going to make difficult. To do this, we needed to rebuild the EdgeX microservices in Go Lang – and do so by our spring 2018 release. This was not a small endeavor and it was made at a time when the EdgeX Foundry developer community was just coming on board. We knew it would take a bit more time, but we were committed to this, and added two more months to this release cycle.
The extra time was well worth it! With the California release, we’ve dramatically lowered the footprint, startup time, memory and CPU usage. Take a look at the statistics below, which compares services from our first community release last October (Barcelona) to our current release (California).

We still have work to do, but it’s now possible to run all of EdgeX on something like a Raspberry Pi 3.
Additional Features
In addition to the initial security capabilities and reducing the size and latency of the platform, this release includes other work – some visible to the user while some features are more hidden but improve the overall quality of EdgeX.
• Several additions were made to the export services to provide additional “northbound” connectivity, to include connectors for XMPP, ThingsBoard IoT, and Brightics IoT
• We improved the documentation and now have documentation stored with the code in Github – allowing it to be maintained and updated more like code by the community
• Arm 64 is now fully supported. In fact we worked with the Linux Foundation to add external environments and tools to create native Arm 64 artifacts.
• We added blackbox tests for all the micro services. These are now kicked off as part of our build and continuous integration processes.
• Other improvements were made to our continuous integration – to help streamline developer contributions
On to Delhi
Our next release, named Delhi, will come out in October 2018. Due to the extended release cycle for California, the Delhi release cycle is going to be short. The significant features planned for Delhi include:
• Initial manageability services and capability
• Device Service SDKs (Go/C) and at least one example device service
• The next wave of security features to include access control lists to grant access to appropriate services and improved security service bootstrapping
• Better/more unit testing and added performance testing
• Adding the last of the refactored and improved Go Lang microservices
• Outlining options and a potential implementation plan for alternate or additional database support
• An EdgeX UI suitable for demos and smaller installations
by Gary Mintchell | Jul 25, 2018 | Automation, Technology
Collaborative describes the latest and most important trend in robots. Even if I was summarily dismissed when I asked that question of the CEO of a robotic arm company at an IT event, I stand by that analysis.
Lately Mobile Industrial Robots (MiR) news came to my attention. I’ve put off writing until I connected with Ed Mullen, US VP of Sales for this Danish company.
He told me that MiR designs and manufactures Autonomous Mobile Robots (AMR) which are a bit like a quantum jump from the older Automated Guided Vehicles (AGVs) with which you may be familiar. Especially if you’re older, like me.
AGVs followed a path which was usually a wire laid in the floor. It followed its route around the facility. Cool, but not really very intelligent.
AMRs operate similar to modern autonomous technology using a 2D map of the facility and a location system plus laser scanning LIDAR. Tell it a place to go, and like a GPS it calculates the best route and directs the mobile robot to its destination—safely. I have actually interacted with one of the company’s earlier versions at a trade show where it continuously ran a route around the booth.
He tells me that the company is really more of a software company than hardware. The object is to take open source software and package it so that the customer has great flexibility for applications while usually going from unboxing to operations in under an hour.
Product news
The latest product news is the launch of its MiR500 AMR. The robot has a lifting capacity of 500 kg (1102 lbs) and can automatically collect, transport and deliver pallets with speeds of nearly 4.5 miles per hour (mph). The MiR500 joins the MiR100 and MiR200 to form a complete fleet of flexible and easy-to-program MiR robots for both heavy and light transport that can optimize logistics throughout the entire production chain, from the warehouse to the delivery of goods.
“With the MiR500, we are extending the proven, strong technology and safety features that have made us the leading global supplier of autonomous mobile robots,” said Thomas Visti, CEO of Mobile Industrial Robots. “The MiR500 was developed to meet the needs of customers who have used our other robots and now see huge potential in the automation of the internal transport of heavy items and Euro-pallets. With MiR500, we’re setting new standards for how companies can use autonomous mobile robots.”
The user interface matches that used in the MiR100 and MiR200, which already optimize production processes in many of the world’s biggest multinational companies such as Airbus, Flex, Honeywell, Hitachi and Danone. The difference is the MiR500’s size, lifting capacity and areas of application.
“MiR500 is an extremely robust robot, so it’s perfect in industrial environments,” Visti said. “We’ve also incorporated the principles from the MiR100 and MiR200, where flexibility and user-friendliness are key attributes. This means that the MiR500 can be programmed without prior experience. It’s also simple to develop and replace top modules such as pallet lifters, conveyor belts and robot arms, so the robot can be used for different transport purposes.”
MiR has grown quickly since its founding in 2013, with sales rising by 500 percent from 2015 to 2016, and 300 percent from 2016 to 2017. With its second US office opening in San Diego this spring, and strong growth continuing worldwide, MiR expects to increase the number of employees from 65 to about 120 in 2018.
Acquisition
But wait, there’s more. Teradyne Inc. and the shareho6lders of Mobile Industrial Robots (MiR) announced the acquisition of privately held MiR of Odense, Denmark for €121 million ($148 million) net of cash acquired plus €101 million ($124 million at current exchange rate) if certain performance targets are met extending through 2020.
“We are excited to have MiR join Teradyne’s widening portfolio of advanced, intelligent, automation products,” said Mark Jagiela, President and CEO of Teradyne. “MiR is the market leader in the nascent, but fast growing market for collaborative autonomous mobile robots (AMRs). Like Universal Robots’ collaborative robots, MiR collaborative AMRs lower the barrier for both large and small enterprises to incrementally automate their operations without the need for specialty staff or a re-layout of their existing workflow. This, combined with a fast return on investment, opens a vast new automation market. Following the path proven with Universal Robots, we expect to leverage Teradyne’s global capabilities to expand MiR’s reach.”
MiR was profitable in 2017 with annual revenue of $12 million USD, more than triple 2016 revenues and had Q1’18 sales of $5 million.
“Joining Teradyne allows us to advance our engineering and development investments to provide greater value to our customers and further expand our market leadership in industrial autonomous mobile robots,” said Thomas Visti, CEO of MiR. “Teradyne’s worldwide reach, world-class engineering and support capabilities, financial strength and proven model for leveraging those strengths will help us grow in new and existing markets worldwide.”
“My main focus is to get our mobile robots out to the entire world,” said Niels Jul Jacobsen, CSO, founder of MiR. “With Teradyne as the owner, we will have strong backing to ensure MiR’s continued growth in the global market.”
by Gary Mintchell | Jul 24, 2018 | Internet of Things, Operations Management
Successful digitalization requires data. Data, in turn, originates often from sensors. The Industrial Internet of Things runs on this data providing a valuable use case of tying a manufacturing enterprise together from supply chain through customer experience.
Mahesh Veerina, CEO of Cloudleaf, walked me through an application based on his company’s technology that indeed ties a supply chain in the pharma industry together. Start with sensors on approximately 5,000 pallets. Each meshes via sub-MHz unlicensed radios through 30 intelligent gateways reporting 16 million data points. Cloudleaf’s SaaS software gathers the data, performs the analytics, then feeds custom dashboards for different roles at the customer’s company. Oh, and continuous learning through Artificial Intelligence (AI) creates a virtuous cycle that constantly improves the system.
The return on investment (ROI)? Estimated at between $70 million and $100 million.
Cloudleaf has announced the next generation of its patented Sensor Fabric, the IoT-at-scale solution that optimizes management of distributed assets throughout any enterprise value chain.
Cloudleaf’s next-generation Sensor Fabric maintains an intelligent grid at the edge for global commerce, making digitization a reality for enterprise customers and value chain partners. Its easy-to-deploy intelligent sensors, gateways and cloud technologies minimize costs and maximize quality, efficiency and reporting standards. At the same time, Cloudleaf’s patented solution generates a continuous stream of increasingly predictive data that enables an enterprise to monitor, measure and manage distributed assets –– on the ground and on the fly. Key enhancements include:
• Comparative multi-location movement history maximizes yield and improves asset utilization.
• Lifecycle tracking optimizes business processes, managing dwell times, cycle times, asset condition changes and other variables.
• Value Loss analytics measure inefficiencies in asset handling, storage and usage.
• Path Modeling provides compliance tracking, monitoring and reporting.
• Next-gen control center enables on-the-fly deployment, calibration, and management of Sensor Fabric, with easy to use web and mobile dashboards.
Unlike products that occasionally add new features and functionalities, Sensor Fabric essentially upgrades itself. Tens-of-millions-per-day messaging sparks multiplier machine learning. The result is agile and actionable insights in virtually any industrial process. The longer Sensor Fabric is deployed, the smarter the industrial process is.
“We are extremely gratified by the extraordinary market acceptance that Cloudleaf is achieving,” said Veerina. “More and more extended enterprises in a wide range of industries are asking Cloudleaf to help them achieve the kinds of efficiencies and ROI that our current customers are gaining. In the very near future, we expect to begin announcing the addition of a number of industry leaders –– including internationally known household names – to our rapidly growing customer base.”
by Gary Mintchell | Jul 23, 2018 | Automation, Operator Interface, Productivity
As manufacturing shifts towards smart factories, with interconnected production systems and automation, engineers at the University of Nottingham are leading a £1.9m project to develop a predictive toolkit to optimise productivity and communication between human workers and robots.
This research fits in with much other reporting I’ve done including the work of Dell Technologies on “human-machine partnerships.”
DigiTOP is one of seven national projects to create novel digital tools, techniques and processes to support the translation of digital capabilities into the manufacturing sector, funded by the Engineering and Physical Sciences Research Council (EPSRC).
It comes following the industry-led Made Smarter review, chaired by Siemens Chief Executive Juergen Maier, which stated that industrial digitalisation could be worth as much as £455bn to UK manufacturing over the next decade.
DigiTOP officially started on 1st July with the first month dedicated to project set up activities culminating in our internal kick off meeting at the end of the month, after which we should have a more outward focus. The project will take 39 months and complete on 30 September 2021. The twitter account @DigiTOP_Project will be regularly updated, and they are in the process of setting up a website to aid dissemination of progress.
A digital toolkit for the optimisation of operators and technology in manufacturing partnerships, DigiTOP will be led by Professor Sarah Sharples at the University of Nottingham in collaboration with Loughborough University, Cranfield University, University of the West of England, BAE Systems, Babcock International, Synertial Labs Ltd, Artinis Medical Systems B.V., High Value Manufacturing (HVM) Catapult and Jaguar Land Rover Ltd.
The toolkit will focus on using human factor theories and data to digitally capture and predict the impact of digital manufacturing on future working practices. Demonstrators will be used to test the implementation of sensing technologies that will capture and evaluate performance change and build predictive models of system performance.
The project will also provide an understanding of the ethical, organisational and social impact of the introduction of digital manufacturing tools and digital sensor-based tools to evaluate work performance in the future workplace.
DigiTOP’s findings will help companies that are planning to implement digital manufacturing technologies to understand how it will alter working practices, and how to optimise workplace designs to take these changes into account.
The tools developed within DigiTOP will help industry to design future work which might take place with a human and robot working in collaboration to complete a task or help with understanding how to design a data visualisation which shows how current parts of the factory are performing, and where maintenance or systems change might be needed in the short or long-term future.
Professor Sharples said: “The manufacturing industry, with the drive towards ‘Industrie 4.0’, is experiencing a significant shift towards digital manufacturing. This increased digitisation and interconnectivity of manufacturing processes is inevitably going to bring substantial change to worker roles and manual tasks by introducing new digital manufacturing technologies to shop floor processes.
“It may not be enough to simply assume that workers will adopt new roles bestowed upon them; to ensure successful worker acceptance and operational performance of a new system it is important to incorporate user requirements into digital manufacturing technologies design.
“New approaches to capture and predict the impact of the changes that these new types of technologies, such as robotics, rapidly evolvable workspaces, and data-driven systems are required,” adds Professor Sharples, who is Associate Pro-Vice Chancellor for Research and Knowledge Exchange for Engineering at Nottingham.
“These approaches consist of embedded sensor technologies for capture of workplace performance, machine learning and data analytics to synthesise and analyse these data, and new methods of visualisation to support decisions made, potentially in real-time, as to how digital manufacturing workplaces should function.”
The EPSRC investment arose out of work conducted by the Connected Everything Network Plus, which was established to create a multidisciplinary community focussed on industrial systems in the digital age.
EPSRC’s Executive Chair, Professor Philip Nelson, said: “The adoption of advanced ICT techniques in manufacturing provides an enormous opportunity to improve growth and productivity within the UK.
“The effective implementation of these new technologies requires a multidisciplinary approach and these projects will see academic researchers working with a large number of industrial partners to fully harness their potential, which could generate impact across many sectors.”
