Why the U.S. Needs Automation to Keep Manufacturing Jobs Viable

Published on 24 Apr, 2017

Manufacturing Industry Business Analysis

The current Trump administration, in conjunction with the manufacturing sector, would have to address a growing need to convert an existing ‘semi-skilled’ workforce to a ‘tech-skilled’ workforce, which would directly align itself with the march of automation.

A promise to bring back manufacturing jobs to the U.S. was the mainstay of President Trump’s campaign in 2016.

The delivery of this promise was largely based on a strategy of renegotiating trade agreements with countries like Mexico, China and so on. As a result, President Trump signed an executive order to pull out of the Trans-Pacific Partnership (TPP), and his administration is currently working on amendments to the NAFTA agreement.

Simply renegotiating trade agreements may not be enough to revive manufacturing jobs in the country, however.

The steady rise of automation within the manufacturing landscape, especially the advent of robotics, Industry 4.0, as well as disruptors such as 3D printing have to be factored into any manufacturing job revival plan.

The Bureau of Labor Statistics estimated that the U.S. lost 5.6 million manufacturing jobs between 2000 and 2010. Industries such as textiles and furniture manufacturing were among the hardest hit among the sectors that suffered severe downsizing. Sectors such as automotive manufacturing soon followed suit. A study conducted by the Center for Business and Economic Research at Ball State University concluded that automation was directly responsible for 85 percent of the jobs lost during this period.

Since 2010, on-going investment in manufacturing automation has resulted in the manufacturing sector‘s output per person index reaching 125.512 (Q4 2016) from 101.975 (Q4 2006), highlighting the positive impact of automation.  Further The Boston Consulting Group forecasts that “the share of tasks performed by robots will rise from a global average of around 10 percent across all manufacturing industries today to around 25 percent by 2025.”

All signs indicate that combating the march of automation and a transition to an era of digital manufacturing would be an exercise in futility.

The current Trump administration, in conjunction with the manufacturing sector, would have to address a growing need to convert an existing ‘semi-skilled’ workforce to a ‘tech-skilled’ workforce, which would directly align itself with the march of automation.

SK Gupta, director of the University of Southern California’s latest ‘Center for Advanced Manufacturing’ believes that automation and advanced manufacturing will play an important role in bringing jobs back to the U.S.

According to Gupta, “automation will make American manufacturers competitive again, since much of the manual labor will be free — performed by robots, working round the clock.”

However, he states that American workers would now have to develop tech related skills and abilities to manage these robotic workers.

To achieve these tech related skills, the Trump administration would have to build a new system of developing a ‘tech skilled’ workforce. The system can be built through a two-pronged approach:

  • Training programs and vocational programs should be made available to Americans at grass root levels, and at a subsidized/affordable rate, especially those which directly cater to high growth manufacturing sectors such as electric vehicles or aerial drones.
  • Push large manufacturing sector companies to use predictive skill mapping techniques in order to identify skill sets of the future. Once these skill sets are identified, the program would place workers (who would be directly impacted) into retraining and reskilling programs.

Katherine Newman, author of "Reskilling America: Learning to Labor in the 21st Century," and vice chancellor for academic affairs at the University of Massachusetts believes the country would have to address the skill problem starting from grass root levels.

According to Newman, a part of the solution to creating tech relevant workforce is to “funnel money from the educational budget to technical schools, rewarding teachers working in these fields and creating apprentice partnerships”.

Greenville, South Carolina formerly a major textile-driven economy witnessed a decline owing to competition from Asia and Mexico. However, the state moved away from its dependency on the textile industry by attracting investments from major companies such as General Electric, BMW, ABB, Fluor, Michelin and Bosch. Greeneville’s existing workforce underwent reskilling and retraining to fill in the new jobs created by these investments. The factories of these major companies are largely automated, managed entirely by workers who have transitioned from basic skills sets to more technical skill sets involving computers and robotics.

The Trump administration would also have to think beyond its policy of bringing back manufacturing jobs and also focus on creating a globally competitive manufacturing base. The US already has one of the key ingredients to becoming a competitive manufacturing base — an ability to create world-class automated manufacturing platforms.

According to the Boston Consulting Group’s report on ‘The Robotics Revolution’, wider adoption of robots, in part driven by a newfound accessibility by smaller manufacturers, will boost output per worker up to 30 percent over the medium-term. The Trump administration would have to focus on creating an ‘automation adoption’ plan for the manufacturing industry for the next 10-15 years.  This would help the country remain competitive against the likes of South Korea, China and Thailand, who have been aggressively incorporating automation in their respective manufacturing sectors.

The ‘automation adoption’ plan would also inadvertently drive the need for ‘advanced manufacturing skills’, which provides an opportunity for the next generation of workers to undergo grass root level training and reskilling for the current workforce.

 

 

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This post first appeared on mbtmag.com.

 


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