• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
  • Articles
  • News
  • Events
  • Advertize
  • Jobs
  • Courses
  • Contact
  • (0)
  • LoginRegister
    • Facebook
    • LinkedIn
    • RSS
      Articles
      News
      Events
      Job Posts
    • Twitter
Datafloq

Datafloq

Data and Technology Insights

  • Categories
    • Big Data
    • Blockchain
    • Cloud
    • Internet Of Things
    • Metaverse
    • Robotics
    • Cybersecurity
    • Startups
    • Strategy
    • Technical
  • Big Data
  • Blockchain
  • Cloud
  • Metaverse
  • Internet Of Things
  • Robotics
  • Cybersecurity
  • Startups
  • Strategy
  • Technical

The robot apocalypse is hard to find in America’s small and mid-sized factories

Reuters / 5 min read.
August 2, 2021
floq.to/xKELr

By Timothy Aeppel

CLEVELAND (Reuters) – When researchers from the Massachusetts Institute of Technology visited Rich Gent’s machine shop here to see how automation was spreading to America’s small and medium-sized factories, they expected to find robots.

They did not.

“In big factories – when you’re making the same thing over and over, day after day, robots make total sense,” said Gent, who with his brother runs Gent Machine Co, a 55-employee company founded by his great-grandfather, “but not for us.”

Even as some analysts warn that robots are about to displace millions of blue-collar jobs in the U.S. industrial heartland, the reality at smaller operations like Gent is far different.

Among the 34 companies with 500 employees or fewer in Ohio, Massachusetts and Arizona that the MIT researchers visited in their project, only one had bought robots in large numbers in the last five years – and that was an Ohio company that had been acquired by a Japanese multinational which pumped in money for the new automation.

In all the other Ohio plants they studied, they found only a single robot purchased in the last five years. In Massachusetts they found a company that had bought two, while in Arizona they found three companies that had added a handful.

Anna Waldman-Brown, a PhD student who worked on the report with MIT Professor Suzanne Berger, said she was “surprised” by the lack of the machines.

“We had a roboticist on our research team, because we expected to find robots,” she said. Instead, at one company, she said managers showed them a computer they had recently installed in a corner of the factory – which allowed workers to note their daily production figures on a spreadsheet, rather than jot down that information in paper notebooks.

“The bulk of the machines we saw were from before the 1990s,” she said, adding that many had installed new computer controllers to upgrade the older machines – a common practice in these tight-fisted operations. Most had also bought other types of advanced machinery – such as computer-guided cutting machines and inspection systems. But not robots.

Robots are just one type of factory automation, which encompasses a wide range of machines used to move and manufacture goods – including conveyor belts and labeling machines.

Nick Pinkston, CEO of Volition, a San Francisco company that makes software used by robotics engineers to automate factories, said smaller firms lack the cash to take risks on new robots. “They think of capital payback periods of as little as three months, or six – and it all depends on the contract” with the consumer who is ordering parts to be made by the machine.

This is bad news for the U.S. economy. Automation is a key to boosting productivity, which keeps U.S. operations competitive. Since 2005, U.S. labor productivity has grown at an average annual rate of only 1.3% – below the post-World War 2 trend of well over 2% – and the average has dipped even more since 2010.

Researchers have found that larger firms are more productive on average and pay higher wages than their smaller counterparts, a divergence attributed at least in part to the ability of industry giants to invest heavily in cutting-edge technologies.

Yet small and medium-sized manufacturers remain a backbone of U.S. industry, often churning out parts needed to keep assembly lines rolling at big manufacturers. If they fall behind on technology, it could weigh on the entire sector. These small and medium-sized manufacturers are also a key source of relatively good jobs – accounting for 43% of all manufacturing workers.

LIMITATIONS OF ROBOTS

One barrier for smaller companies is finding the skilled workers needed to run robots. “There’s a lot of amazing software that’s making robots easier to program and repurpose – but not nearly enough people to do that work,” said Ryan Kelly, who heads a group that promotes new technology to manufacturers inside the Association for Manufacturing Technology.

To be sure, robots are spreading to more corners of the industrial economy, just not as quickly as the MIT researchers and many others expected. Last year, for the first time, most of the robots ordered by companies in North America were not destined for automotive factories – a shift partly attributed to the development of cheaper and more flexible machines. Those are the type of machines especially needed in smaller operations.

And it seems certain robots will take over more jobs as they become more capable and affordable. One example: their rapid spread in e-commerce warehouses in recent years.

Carmakers and other big companies still buy most robots, said Jeff Burnstein, president of the Association for Advancing Automation, a trade group in Ann Arbor, Michigan. “But there’s a lot more in small and medium-size companies than ever before.”

Michael Tamasi, owner of AccuRounds in Avon, Massachusetts, is a small manufacturer who recently bought a robot attached to a computer-controlled cutting machine.

“We’re getting another machine delivered in September – and hope to attach a robot arm to that one to load and unload it,” he said. But there are some tasks where the technology remains too rigid or simply not capable of getting the job done.

For instance, Tamasi recently looked at buying a robot to polish metal parts. But the complexity of the shape made it impossible. “And it was kind of slow,” he said. “When you think of robots, you think better, faster, cheaper – but this was kind of the opposite.” And he still needed a worker to load and unload the machine.

For a company like Cleveland’s Gent, which makes parts for things like refrigerators, auto airbags and hydraulic pumps, the main barrier to getting robots is the cost and uncertainty over whether the investment will pay off, which in turn hinges on the plans and attitudes of customers.

And big customers can be fickle. Eight years ago, Gent landed a contract to supply fasteners used to put together battery packs for Tesla Inc – and the electric-car maker soon became its largest customer. But Gent never got assurances from Tesla that the business would continue for long enough to justify buying the robots it could have used to make the fasteners.

“If we’d known Tesla would go on that long, we definitely would have automated our assembly process,” said Gent, who said they looked at automating the line twice over the years.

But he does not regret his caution. Earlier this year, Tesla notified Gent that it was pulling the business. “We’re not bitter,” said Gent. “It’s just how it works.”

Gent does spend heavily on new equipment, relative to its small size – about $500,000 a year from 2011 to 2019. One purchase was a $1.6 million computer-controlled cutting machine that cut the cycle time to make the Tesla parts down from 38 seconds to 7 seconds – a major gain in productivity that flowed straight to Gent’s bottom line.

“We found another part to make on the machine,” said Gent.

(Reporting by Timothy Aeppel in Cleveland; Editing by Matthew Lewis)

Categories: News
Tags: Institute, news, research, technology

About Reuters

Primary Sidebar

E-mail Newsletter

Sign up to receive email updates daily and to hear what's going on with us!

Publish
AN Article
Submit
a press release
List
AN Event
Create
A Job Post

Jobs

  • Software Engineer | South Yorkshire, GB - February 07, 2023
  • Software Engineer with C# .net Investment House | London, GB - February 07, 2023
  • Senior Java Developer | London, GB - February 07, 2023
  • Software Engineer – Growing Digital Media Company | London, GB - February 07, 2023
  • LBG Returners – Senior Data Analyst | Chester Moor, GB - February 07, 2023
More Jobs
Host your website with Managed WordPress for $1.00/mo with GoDaddy!

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

News

  • Ex-Apple designer Ive, OpenAI’s Altman discuss AI hardware -The Information
  • Samsung SDI to invest $2 billion to build second joint battery plant in US with Stellantis
  • China lists mobile app stores that comply with new rule, but Apple missing
  • Germany halts e-cars solar subsidy programme amid high demand
  • Pegatron India fire traced to workers’ failure to turn off switch -sources
More News

Related Online Courses

  • Oracle Cloud Data Management Foundations Workshop
  • Data Science at Scale
  • Statistics with Python
More courses

Footer


Datafloq is the one-stop source for big data, blockchain and artificial intelligence. We offer information, insights and opportunities to drive innovation with emerging technologies.

  • Facebook
  • LinkedIn
  • RSS
  • Twitter

Recent

  • 5 Reasons Why Modern Data Integration Gives You a Competitive Advantage
  • 5 Most Common Database Structures for Small Businesses
  • 6 Ways to Reduce IT Costs Through Observability
  • How is Big Data Analytics Used in Business? These 5 Use Cases Share Valuable Insights
  • How Realistic Are Self-Driving Cars?

Search

Tags

AI Amazon analysis analytics app application Artificial Intelligence BI Big Data business China Cloud Companies company costs crypto customers Data design development digital environment experience future Google+ government information learning machine learning market mobile Musk news Other public research sales security share social social media software strategy technology twitter

Copyright © 2023 Datafloq
HTML Sitemap| Privacy| Terms| Cookies

  • Facebook
  • Twitter
  • LinkedIn
  • WhatsApp

In order to optimize the website and to continuously improve Datafloq, we use cookies. For more information click here.

Dear visitor,
Thank you for visiting Datafloq. If you find our content interesting, please subscribe to our weekly newsletter:

Did you know that you can publish job posts for free on Datafloq? You can start immediately and find the best candidates for free! Click here to get started.

Not Now Subscribe

Thanks for visiting Datafloq
If you enjoyed our content on emerging technologies, why not subscribe to our weekly newsletter to receive the latest news straight into your mailbox?

Subscribe

No thanks

Privacy Overview

This website uses cookies so that we can provide you with the best user experience possible. Cookie information is stored in your browser and performs functions such as recognising you when you return to our website and helping our team to understand which sections of the website you find most interesting and useful.

Necessary Cookies

Strictly Necessary Cookie should be enabled at all times so that we can save your preferences for cookie settings.

If you disable this cookie, we will not be able to save your preferences. This means that every time you visit this website you will need to enable or disable cookies again.

Marketing cookies

This website uses Google Analytics to collect anonymous information such as the number of visitors to the site, and the most popular pages.

Keeping this cookie enabled helps us to improve our website.

Please enable Strictly Necessary Cookies first so that we can save your preferences!