I think even mainstream media has caught up to the current hiring situation—it is hard to find qualified people to fill positions. Heck, even last night stopping at a Cracker Barrel on the drive home from Tennessee we saw a harried staff and only about half the tables filled. They didn’t have enough people to staff the place.
Now try to find skilled welders. How about hiring a robotic welder? Easy to program and install. Always shows up for work. No drug test required. A very interesting idea.
The new for-hire BotX Welder—developed by Hirebotics and utilizing Universal Robots’ UR10e collaborative robot arm—lets manufacturers automate arc welding with no capital investment, handling even small batch runs not feasible for traditional automation.
The press release tells us, “Nowhere in manufacturing is the shortage of labor felt as urgently as in the welding sector, which is now facing an acute shortage of welders nationwide. The industry’s hiring challenge, combined with the struggle metal fabrication companies experience in producing quality parts quickly and in small runs, prompted Hirebotics to develop the BotX Welder.
“Many people didn’t believe that collaborative robots could perform such heavy-duty tasks as welding,” says Rob Goldiez, co-founder of Hirebotics. “We realized the need of a solution for small and medium sized metal fabricators trying to find welders.” Hirebotics’ hire-a-robot business model built on the Universal Robot, set the foundation for the BotX. It is a welding solution powered by the UR10e cobot that is easy to teach, producing automation quality with small batch part runs.
The BotX is now available to early access customers and will officially launch at FABTECH in Chicago, November 11-14.
In developing BotX, Hirebotics addressed two major hurdles of robotic welding: the ease of programming and the ease in which a customer can obtain the system without assuming the risk of ownership. There are no installation costs with BotX and with cloud monitoring, manufacturers pay only for the hours the system actually welds. “You can hire and fire BotX as your business needs dictate,” explains Goldiez.
The complete product offering comes with the UR10e cobot arm, cloud connector, welder, wire feeder, MIG welding gun, weld table, and configurable user-input touch buttons. The customer simply provides wire, gas, and parts. Customers can teach BotX the required welds simply via an intuitive app on any smartphone or tablet utilizing welding libraries created in world-class welding labs. A cloud connection enables 24/7 support by Hirebotics.
“We chose Universal Robots’ e-Series line for several reasons,” says Goldiez. “With Universal Robots’ open architecture, we were able to control, not only wire feed speed and voltage, but torch angle as well, which ensures a quality weld every time,” he says. “UR’s open platform also enabled us to develop a cloud-based software solution that allows us to ensure a customer is always running with the latest features at no charge,” explains the Hirebotics co-founder. “We can respond to a customer’s request for additional features within weeks and push those features out to the customer with no onsite visits,” says Goldiez, emphasizing the collaborative safety features of the UR cobots. “The fact that they’re collaborative and don’t require safety fencing like traditional industrial robots means a smaller foot print for the equivalent working space, or put another way; less floor space to produce same size part. In many cases less than half the floor space of traditional automation,” he says. “The collaborative nature of the solution enables an operator to move between multiple cells without interrupting production, greatly increasing the productivity of an employee.”
PMI LLC in Wisconsin, was one of the first customers of the BotX. “A large order would mean, we need to hire 10-15 welders to fulfill it – and they’re just not out there,” says VP of Operations at PMI, Erik Larson. “Therefore, we would No Bid contracts on a regular basis. With the BotX solution, we now quote that work and have been awarded contracts, so it has really helped grow our business,” says Larson. “The BotX Welder doesn’t require expensive, dedicated fixturing and robot experts on the scene.” Now PMI’s existing operators can handle the day-to-day control of the BotX, which welds a variety of smaller product runs.
The Wisconsin job shop has now stored weld programs for more than 50 different parts in their BotX app. “We are now able to deliver quality equivalent to what we could accomplish manufacturing with very expensive tooling typically used with higher-volume part runs,” says PMI’s VP of Operations, mentioning the ease of accessing the solution. “Being able to simply hire the BotX Welder, and quickly switch between welds by using our smart phone—and only pay for the hours it works—is huge for us. It took our area lead, who had no prior robotics experience, half an hour to teach it how to weld the first part.”
Another significant benefit was PMI’s ability to get the BotX welds certified for customers who require this. “This now means we do not need to use certified welders to oversee the operation. As long as the cobot welder’s program is certified, any operator can tend the cobot welder. This really unlocks a lot of resources for us,” says Larson. “Hirebotics and Universal Robots really hit the mark with this, we’re looking forward to a long partnership with them.”
Podcast 194 of my long-running series—Beware Hype of OT and IT
Platforms come and go–sometimes quickly with turns in technology. IoT platforms were all the rage. Just like IT/OT Convergence and other hyped tech. But engineers are quietly working together to apply the technologies to solve business and industrial problems. Don’t watch the hype. Notice when everyone is using it.
The Industrial Internet of Things by definition is all about connections. Connecting hundreds of devices which often have differing protocols is a huge challenge. In an attempt to facilitate IIoT deployments, ioTium has announced an alliance with Telit. The agreement allows Telit deviceWISE gateway technology on the ioTium Edge App Store for single-click deployment.
After wading through a couple of paragraphs of marketing generalities, I found the best explanation with this quote. “With the cooperation of Telit, customers can now rapidly connect different communications protocols like BACnet, OPC, Modbus or even proprietary protocols to various IoT cloud offerings such as Azure IoT, Siemens MindSphere or private cloud end points,” said Sri Rajagopal, CTO, ioTium. “All commissioning, data mapping, and contextualization can now be done remotely, dramatically reducing the time and cost of flying technicians and data scientists to the site to remediate in person.”
Then the obligatory quote from the partner. I’ve talked with Fred Yentz for many years about connecting data. Here’s his thought on this announcement. “Our alliance with ioTium establishes a best-in-class approach for digital connectivity in the industrial world,” said Fred Yentz, president Strategic Partnerships, Telit. “Together, we are providing industrial enterprise customers a secure, plug-and-play way to connect any machine to cloud-based applications to capitalize on the benefits of Industry 4.0.”
Solving this problem is mainly what the various platforms are attempting. I would be interested in hearing what is actually working out in the field. Comment or send me an email. Something is working, because engineers are doing this.
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The short take: ADVICS and Macnica Networks, Inc. deploy FogHorn Edge Computing Software in Smart Factory Transition. We talk endlessly about IoT, digital transformation, and now Smart Factory Transition. Do these terms mean anything? I think we are seeing people do actual work by using digital technologies that they mostly already have pieces of. Then marketers come along and christen it with a name. We are witnessing real progress improving manufacturing and production with modern thinking and tech.
In this case according to the press release, a $5B automotive brake system manufacturer deploys FogHorn Lightning Edge Computing Software Platform for real-time data processing, machine learning and AI. Note: machine learning is usually considered a subset of AI.
ADVICS Co. Ltd., working with Macnica Networks Inc., has deployed FogHorn Lightning Edge Computing Software to provide onsite data processing, real-time analytics, and ultimately machine learning AI in its smart factory transition.
ADVICS supplies advanced, high-quality automotive brake systems and components globally. ADVICS partnered with Macnica Networks to digitize its manufacturing sites and integrate varied equipment data to enable edge-based real-time visualization and analytics of its manufacturing. The digital transformation has allowed ADVICS to identify production issues immediately and quickly determine the root cause therefore improving manufacturing efficiencies. Manual workloads surrounding data acquisition have also been significantly reduced, enabling operation leaders to spend more time on managing production.
“ADVICS digital transformation to a smart factory reflects their mission to contribute to the reliability of society by pursuing a better safety, environment and comfort through products that delight customers,” said Yuta Endo, vice president, general manager of business development and head of APAC operations at FogHorn. “We are excited to work with our partner, Macnica Networks, to help ADVICS enhance manufacturing efficiency. FogHorn Lightning is uniquely positioned to help companies transform streaming data into actionable, predictive insights right at the edge, providing real-time monitoring and diagnostics, streaming analytics, machine learning and operations optimization.”
FogHorn’s Lightning product portfolio embeds edge computing software locally, as close to the source of streaming sensor data as possible. FogHorn Lightning Edge platform delivers low latency for onsite data processing and real-time analytics in addition to its machine learning and artificial intelligence (AI) capabilities.
ADVICS is one of the 13 major Aisin Group companies. The main business is the development, production and sales of automotive brake systems and parts that make up these systems.
Macnica Networks is a member of the Macnica Group, a growing global technology distributor. The company has over 20 years of experience in product localization, sales, and technical support of computer network equipment. It supplies a full line of leading-edge network appliances, software, telecom solutions to its customers, and consistently brings innovative new products to their portfolio.
FogHorn is a developer of edge computing software for industrial and commercial IoT application solutions.
The concept of digital twins was born from the marriage known as cyber-physical systems. The cyber representation of a product or process was often held digitally within CAD/CAM or PLM systems. These became linked to the physical object through a feedback loop that kept the two in sync.
Digital Twin has moved from the esoteric to mainstream within industrial culture. And digital no longer is consigned to drawing databases, as my recent conversation with Michael Kanellos and Perry Zalvesey of OSIsoft reveals.
They described the process this way, “From devices all the way to buildings and factories, we’re now living in a world where everything is connected. And as these operations become more connected, it’s increasingly important to identify the strongest solution to monitor them. With the introduction of IoT, sensor and even AI technology to industrial operators, there’s been a surge of unfamiliar digital strategies – the latest being digital twins.”
OSIsoft prefers to consider digital twin as a loose term, as it can be either a complete network doppelganger or just a copy of key data streams to narrow in on specific issues. Everyone has their own preference and iteration.
OSIsoft named its digital twin technology the Asset Framework, which allows companies to take a project-by-project approach, creating solutions for each need on a rolling basis.
When one of its customers, DCP Midstream, began deploying OSIsoft’s AF tool it rolled out 12 AF based applications in two months, experiencing a $20-$25 million one-year return.
Application of OSIsoft’s Asset Framework has been strong in the water industry. Zalvesey says that his first work in the area was with modeling processes that were only static models. Today’s digital twins are dynamic. Designers can model the facility and objects within it. Each object has attributes that data are then associated with. Where originally there was a pump object—say we define “Pump 12” and associate data such as temperature and pressure and more. Now with Asset Framework, designers can create a template class “pump” and be able to replicate for as many pumps as a facility contains.
1. Asset Framework is the core digital twin offering. It’s as a relational layer on top of PI that combines all the data streams (temp, pressure, vibration) of an asset into one screen. A lot of people get fancy with the digital twin term but to us it’s a simulation combined with live data.
2. A simple AF template for a pump probably takes a half an hour to build. It can then be replicated ad inifinitum. It’s a drag and drop process. AF is part of PI Server (it was a separate product years ago but combined into it.) Complex ones can take months. Element, a company that OSIsoft helped incubate (and has since culled investment from Kleiner Perkins, GE and others) has built a service called AF accelerator. Basically, they parachute a team of data scientists to study your large assets and then develop automated ways to build AF templates for complete mines or offshore oil platforms. It still takes two months or so but they can streamline a lot of the coding tasks. BP used them.
3. Examples:
DCP. In 2017, the company launched an effort to digitize operations. One of the first steps was using PI to collect the data and use AF to create simple and complex digital twins. DCP has 61 gas plants for instance. Each one has been modeled with AF. Plant managers are show a live feed of current production, idealized production, and the differential in terms of gas produced and revenue. DCP discovered that it could increase production per plant on average $2000-$5000 per day, or millions a year, by giving the plant managers better visibility into current production and market pricing. In year one, it saved $20=$25 million, paying off the entire project (including the cost of building a centralized control center in Colorado and staffing it.) The next year (2018) it saved another $20 million.
MOL. One of the largest uses of AF. MOL tracks 400,000 data streams and has 21,000+ AF instances based on 300 templates (a single template can be replicated several times.) MOL says that it has added $1 billion EBITDA since 2010 by using its data better. With AF, for instance, they figured out why hydrogen corrosion was exceeding the norm. In some instances, they’ve used advanced analytics—an experiment to see if it could use high sulfur crudes required deep analytics—but most of the time MOL has made its improvements by creating AF templates, studying the phenomena and taking action.
Colorado Springs. Complete opposite end of big. It’s a small, regional utility.
Heineken uses AF to model its plants to reduce energy. Aurelian Metals used it to boost gold extraction from ore from 75% to 89%. Michelin saved $4 million because AF let them recover more quickly from a previous outage. Deschutes Brewery meanwhile boosted production by $450K and delayed a plant (per our 2018 meeting.
