Geopolitical Risk and Industrial Policy Drive Reshoring and FDI Announcements

Harry Moser has been a tireless crusader for bringing manufacturing jobs back to the USA. Sometimes economic forces overpower desires. The economics of offshoring have weakened over time. Then the pandemic revealed supply chain weaknesses. Factors are coming together to bring jobs closer to markets. This is news of a first half 2023 Reshoring plus Foreign Direct Investment (FDI) job announcements.

We expect to see upwards of 300,000 jobs announced by year-end. EV battery and chip investments along with other essential product industries supported by Bidenomics account for the bulk of the announcements.

Several factors have come to light that substantiate the strength of U.S. reshoring and FDI trends. In the first quarter of this year, average spending on U.S. factory construction was more than double the average from the past 17 years.  Reshoring Initiative data parallels the magnitude and focus of the construction investments. Independently conducted surveys on reshoring actions by U.S. companies also correlate very closely with Reshoring Initiative data on jobs announced over the past 12 years (Exhibit 1) adding validity to both data sets.

Reshoring and FDI job numbers demonstrate exceptional progress for U.S. manufacturing after decades of offshoring. If this progress can be combined with an industrial policy that supports greater cost competitiveness, we will continue our rapid strengthening of U.S. supply chains.

The Reshoring Initiative’s 1H 2023 Report contains data on U.S. reshoring and FDI by companies that have shifted production or sourcing from offshore to the United States.

 “We publish this data to show companies that their peers are successfully reshoring and that they should reevaluate their sourcing and siting decisions,” said Harry Moser, founder and president of the Reshoring Initiative. “With 5 million manufacturing jobs still offshore, as measured by our $1.2 trillion/year goods trade deficit, there is potential for much more growth. We also call on the administration and Congress to enact policy changes to make the United States competitive again.”

About the Reshoring Initiative

A 55-year manufacturing industry veteran and retired President of GF Machining Solutions, Harry Moser founded the Reshoring Initiative to move lost jobs back to the U.S. He was named to the Industry Week and Association for Manufacturing Excellence (AME) Halls of Fame for his efforts with the Reshoring Initiative.

Generative AI Industrial Copilots to Deliver Contextual Intelligence

As I noted in my last post, the two key words for 2023 are Generative AI and Sustainable. This news concerns the release of more Copilots. These are from SymphonyAI. The company claims that generative and predictive AI are enhancing efficiency by 30%, reducing maintenance costs by 50%, and expediting decision-making by 70%. (I don’t know how they can measure the last one and the first two are huge numbers. But I will buy that there should be measurable improvements.) The three announced Copilots are designed to help frontline workers speed operations and improve efficiency.

The three role-based copilots—Plant Performance Copilot, Digital Manufacturing Copilot, and the Connected Worker Copilot—provide enhanced human-like interaction so workers can get beyond standard data analytics and analysis to understand what happened, why, and more importantly, anticipate future events. Assisted by copilots, plant managers, operators, engineers, and technicians can swiftly identify, diagnose, and overcome operational hurdles with instant initiation of corrective and mitigating actions.

Built on SymphonyAI’s next generation predictive and generative AI Industrial Reasoning and Insights Platform (IRIS), the copilots integrate within SymphonyAI industrial applications. The copilots leverage Microsoft Azure OpenAI alongside an industrial knowledge graph that includes events, sensor data, asset details, product documentation and manuals, and reliability and maintenance reports. All three copilots contextualize, process, and analyze data from various manufacturing sources. Data is presented in natural language to create actionable insights, enhance operations, reduce downtime, and bolster overall productivity.

Plant Performance Copilot enables users, including plant managers, maintenance, and reliability engineers, to quickly uncover and implement recommended actions to enhance plant performance by using natural language in a chat format rather than querying databases, interpreting dashboards, or accessing knowledge repositories. It interacts across all relevant data sources for critical asset processes, delivering targeted user assistance, recommends actions, and forecasts plant performance through contextual, proactive insights and automated workflows. Leveraging natural language, it accelerates root cause analysis from generated anomalies, including quantified KPI impact of underperforming assets and processes, along with recommended remediations.

Digital Manufacturing Copilot streamlines and strengthens manufacturing operations by seamlessly tying workflow, production, and asset data together to unveil invaluable production process optimization and bottleneck prevention insights. Generative AI adds a more intuitive ability to run what-if scenarios for production scheduling, boost throughput, and improve overall equipment effectiveness (OEE) metrics.

Connected Worker Copilot can quickly and comprehensively scan machine manuals, procedures, knowledge bases, and other sources of data to provide instant, contextual recommendations and information to users in natural language, enabling them to instantly identify and resolve problems without having to conduct time-consuming research or consult more experienced colleagues. Integrated with SymphonyAI Connected Worker, the copilot streamlines inspections, reduces rework, and minimizes resource waste for frontline workers. Natural language access to troubleshooting guides, maintenance manuals, and procedure documentation fosters smooth operations with clear insights into workflow metrics and assists new employees with a simple screen tap.

Retrocausal Raises $5.3M Round to Meet Demand for Generative AI Manufacturing Assembly Optimization Solution

I have a built-in marketing hype detector. I hear so much hype that sometimes it goes into overdrive. The hype cycle of the past few years has be artificial intelligence (AI). Everything is AI. That was even before ChatGPT soared into everyone’s attention span.

So, when I hear about a company with a product using Generative AI, I need to be shown.

I wrote about Retrocausal a few months ago. Then I sort of forgot about it. This press release about the company raising another round of financing gave me the excuse to talk with CEO Dr. Zeeshan Zia.

The funding was straightforward. I wanted to know more about what the software does and how Generative AI fits into the picture.

Retrocausal, a leading platform provider for manufacturing process management, today announced a $5.3M financing round co-led by Glasswing Ventures, One Way Ventures, and Indicator Ventures, along with participation from existing investors Argon Ventures, Differential Ventures, Ascend Vietnam Ventures, Incubate Fund US, SaaS Ventures, Hypertherm Ventures, Stage Venture Partners, and Techstars.

One product of the company is Assembly Copilot. This product uses a number of vision and projected video displays to guide workers—especially new, untrained ones—into a proper assembly workflow. It shows what to do next and how to assemble. It will go to the next step without any specific input from the worker. In other words, it does its job and gets out of the way. All of us who have ever developed automation systems know that when the automation gets in the way of the work, then the worker will turn it off.

Funding will be used to meet the increased market demand for its proprietary generative AI technology, Retrocausal’s Kaizen Copilot software for Manufacturing Assembly Optimization. Retrocausal’s solution simplifies manual assembly operations and the underlying processes to empower the low-skilled workforce to take on high-skill manufacturing jobs. 

Kaizen Copilot (check out video) is way cool. An industrial engineer or supervisor sets up a prototype workstation along with a worker. Components are arranged and work instructions defined. A camera, even the one on their smartphone, is installed above with the entire operation in the field of view. The software captures the work—motions, locations, relative positions—and analyzes the process. Kaizen Copilot uses a Generative AI recommendation engine to analyze the workflow, material placements, and worker motions to provide suggestions for better workstation layout and assembly order.

The big problem Retrocausal addresses is the labor crisis in manufacturing. According to the National Association of Manufacturers, by 2030, the manufacturing skills gap, caused by the labor market’s struggle to find workers with highly technical and manual expertise, could lead to 2.1 million unfilled jobs risking over $1 trillion in losses that year alone. 

Retrocausal’s Copilot software allows an untrained worker to become productive on a new process within five minutes and deliver the productivity and quality of someone who has had months of training, resulting in 25% greater First Time Yields (FTY) and 90% less assembly-related scrap costs. 

Retrocausal’s Copilot extends its impact beyond individual performance. It equips production supervisors and junior industrial engineers with the capability to radically overhaul workstation design and re-balance assembly lines. Production supervisors and junior industrial engineers can improve workstation design and re-balance assembly lines to minimize the operator headcount needed to run a line while eliminating bottlenecks leading to 35% greater value per operator.

“We are thrilled to receive the continued support of Glasswing Ventures, new investors One Way Ventures and Indicator Ventures, and our existing investors, in helping us meet the growing demand for our offering,” said Dr. Zeeshan Zia, CEO of Retrocausal. “This latest round will help our team accelerate deployment as we continue to leverage AI to address the manufacturing talent shortage and re-imagine manufacturing assembly processes.”

Robots Descend on Cowboys Stadium to Help Address Labor Shortages

Here’s a good reason to visit AT&T Stadium in Arlington, Texas (home of the Cowboys) other than an NFL football game. More than 20 robotics and automation vendors will showcase hands-on demonstrations at large free-to-attend ‘Waves of Innovation’ event on November 15

Here is a stat repeated over most of the USA. Despite the Dallas metro adding more than 10,000 manufacturing jobs over the past 10 months, the region still has more job vacancies than applicants.

“Historically low labor participation rates in our area means manufacturers are often unable to staff their shifts,” says Nick Armenta, regional manager of Olympus Controls, an engineering services company that specializes in the integration of motion control, machine vision, and robotic technologies. In Texas, there is currently 0.8 unemployed persons per job opening, a gap that is especially pronounced in manufacturing.

Olympus Controls is now inviting manufacturing professionals to AT&T Stadium for ‘Waves of Innovation’ a unique event featuring live demonstrations of the newest automation and robotics solutions presented by veteran problem solvers ready to discuss attendees’ manufacturing challenges.

Armenta looks forward to hosting more than 20 different automation companies showcasing a wide range of automation; from collaborative robots handling grueling sanding and polishing tasks, to vision-guided robotic arms picking up items using deep learning algorithms, along with applications for automated machine loading, laser marking, and much more.

Details:

When: November 15, 3:00-7:00 pm CT

Where: Choctaw Club – Silver Room North, AT&T Stadium, 1 AT&T Way Arlington, TX 76011

Free to attend: Register here

Scott Paulk, engineering manager with Alexandria Industries in Dallas, is excited to attend Waves of Innovation. “Knowing what’s out there makes our automation journey easier,” he says, emphasizing that his company already has 40% of its work centers robotically automated. “We sometimes struggle with hiring skilled labor, automation helps offset this by enabling us to reallocate resources. Another benefit of robots is they get the younger generation intrigued; this has no doubt led to employees selecting our companies over a potential competitor.”

Aircraft Tooling Inc., a Dallas-based repair center for the aviation industry also attending the event, was surprised to find that collaborative robots (cobots) could withstand the high temperatures and harsh environment while performing plasma spray processes. A task their employees have now been freed up from performing. Thermal spray supervisor at Aircraft Tooling, Juan Puente, readily admits that despite the cobot having “won their hearts”, there was significant hesitation as to whether the robot would operate reliably in the spray booth’s extremely hot and dusty environment. “We were very surprised. I thought the robot wouldn’t stand it,” he says.

Nick Armenta looks forward to surprising more Texan manufacturers. “Unlike most of the American economy, manufacturing requires your physical presence. Knowing the local talent and resources close to you will radically enhance your capabilities,” he says. “By bringing Waves of Innovation to Dallas, we are illuminating both the developing and established talent we already have here in Texas.”

Waves of Innovation exhibitors include:

Apex Dynamics, Asyril, Cobot Depot, Copley Controls, Datalogic, Dorner Conveyors, Epson Robots, Flexxbotics, Kane Robotics, Mecademic, National Tooling and Machining Association (NTMA), Nidec Corporation, Olympus Controls, Panasonic, Robotiq, Robotunits, Texas Manufacturing Assistance Center (TMAC), Spira Vision, University of Texas at Arlington (UTA), Zebra Robotics.

Platinum sponsors: Universal Robots, Mitsubishi Electric

Using Remote Experts Becoming Technically and Economically Feasible

Last winter the hype cycle concerned metaverse, augmented reality (AR), virtual reality (VR). I wrote about a conversation with GridRaster Co-Founder Dijam Panigrahi about his company’s take on “immersive mixed reality for enterprises.” That was in January this year. Not long after came ChatGPT and the hype cycle went into overdrive on Artificial Intelligence. Now everything is AI.

This seemed to be a good time to talk with Dijam again following up to see if he wanted to add AI to the AR/VR talk and come full circle beyond the hype cycle. Also he is not the marketing lead. We can skip the buzzwords and hype and focus on why and how rather than stay at a more superficial plane.

GridRaster provides the platform, foundation if you will, for using AR and VR hardware of your choice in order to accomplish real-world tasks. Talking with me, he’ll focus on industrial and manufacturing applications.

The marketing pitch leading to this conversation included sustainability. We broached that topic through the lens of minimalism. The idea of using technology to minimize use of resources.

OK, disclaimer, my son is a commercial airline pilot. I encourage all of you to go out and fly somewhere. However, if you have a problem with an asset, you may not want to wait hours/days for an expert to fly in from somewhere far away only to discover that a critical tool was located elsewhere.

How do we get these tools that may include AR or VR and/or AI to the front line worker in order to accomplish the task quickly and efficiently. For example, he told me, imagine a worker facing an aircraft grounded somewhere. It never requires maintenance where there is a maintenance hub. Now, the company must fly in an expert.

Now, what if we give that front-line worker something like a Microsoft HoloLens backed up with the GridRaster platform? Now between the local camera and 3D modeling (digital twin), the expert can see what is happening right at the instant. That expert can now see what’s happening, the worker can see information displayed through the device, and the expert can now guide the worker to complete the repair. Saves time, expense, fuel.

Dijam sees the platform and applicability extended to design engineering. Designers use clay models and iterative detailing to prototype a new car. With 3D modeling and conversations with a variety of design engineers, the team can iterate faster. This same applicability extends even into the manufacturing of the product.

I mentioned that I first wrote about these applications about 23 years ago. But the networks were too slow, the hardware too clunky, and the tools limited. He said, sure, look at how unit prices of many things have decreased, networks moving now even into 5G, data moving from centralized cloud to hybrid and edge. Technology continues to improve speed, ease of use, price for application. Plus GridRaster solving the infrastructure problem.

They have tried their application in manufacturing and have found that an AR solution helps a worker with one year of experience perform as well as one with five years. Given the worker shortage problem all over the world, this alone would justify a purchase.

Case Study Returning Used Mobile Phones to the Supply Chain

Last winter I got sucked in by an advertisement from Verizon. My wife was due for a new iPad and could use a new iPhone. I was thinking about upgrading my 2-year-old iPhone. The ad looked like a good deal to trade in a bunch of stuff and walk out with new equipment. In the end, you never get the deal exactly as advertised because of nuances. But we did it.

I bet you’ve traded in a phone or two in your life. Ever wonder what happens to those old traded-in phones? You are about to find out.

A publicist I’ve known for a while who (unlike most these days) knows me and what I like to write about, pitched me a story about an actual user of automation. I said great, I’d like something beyond just a new feature in the software. Except the company was Assurant. I looked them up. An insurance company. In 25 years, I doubt that I’ve written about insurance once.

But she’s trustworthy and the application seemed appropriate, so here we are. A story about how a division of Assurant has built a big business taking in traded-in mobile phones and reinserts most of them back into the supply chain. If you’ve bought a refurbished phone, chances are it went through one of their facilities.

That’s how I wound up on a Microsoft Teams call with Brandon Johnson. He is the Senior Vice President of Engineering and Automation at Assurant, a leading global business services company that supports, protects and connects major consumer purchases. Johnson oversees all engineering and automation initiatives related to the mobile device lifecycle across 20 locations worldwide. His primary responsibility is to lead a team that implements innovative software and robotics technologies to enhance efficiency, safety, quality, and device value.

We’ll walk through the process they have developed for processing 15 million phones per year. Then we’ll look at how automation has improved workforce stability, worker safety, and throughput.

First, Johnson told me his background and education were industrial engineering and operations management. Automation was something he picked up along the way. Before automating anything in the processes at Assurant, though, he emphasized two things:

  • They don’t automate simply to replace workers
  • Every automation project must have a business purpose

So, what happens when your used phone hits one of their facilities?

Incoming material is all in boxes. There is no uniformity to the boxes. They must all be opened and the phones removed. The original process used people with razor box knives. These are a safety hazard (I know, I had a job using them once). The job also was not challenging which led to excessive attrition.

After phones are decartoned, they are provided with a QR Code ID. They proceed to a charging station as all need a minimum amount of charge for downstream processes. They go to a cosmetic grading station and then sorting into those who have potential high value and those not so much to those that will just be ground for recycling. Next comes a diagnostic test station where 65 tests are performed. Data cleaning comes next. This is a crucial step and Assurant is certified for data cleaning. They’ll perform and value-added repair if feasible. Then, on to the warehouse to be sold and shipped.

Automation has been added so far:

  • Machine to slit the incoming boxes and cartons. This changed the job from manual knives to a technician job. That job is more stable and has value-added skills
  • Cosmetic grading is highly complex and subjective. Assurant has developed a patented automation for inspection and grading the phones. Once again, a high-turnover job turned into technician roles leading to a more stable and trained workforce.
  • Diagnostics testing has been upgraded from a single workstation where they’d dump a bunch of phones on a person and they’d perform all the tests on a single computer. Now there is a flow to the system easing the bottlenecks. 
  • A robotic feeder brings phones to the charging stations and plugs them in saving yet another rote job.

I asked about recycling the powder from groundup phones. They send to a third party who can extract the various metals from the powder for reinsertion into that supply chain.

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