“We’ve got a lot of work to do,” says U.S. Council on Competitiveness.
Competitiveness has replaced success in the manufacturing lexicon these days, with the ongoing struggle between low-wage offshore manufacturers and higher cost domestic producers.
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Measuring competitiveness isn’t easy, but the one metric quoted by everyone from President Barack Obama to your local Chamber of Commerce is “productivity.” But does anyone know what the term really means? The most common definition is the amount or value of goods produced per unit of labor, or sometimes per worker.
Depending on how you measure it, productivity can be as simple or as complex a measure as you want. One way is to simply divide sales by number of employees and another is to measure units of output per man-hours worked to produce them. For the manufacturing engineer, the latter is more interesting, since it takes pricing out of the equation. That’s the beauty of manufacturing engineering; we don’t need to know how much steel costs, we simply need to know that it’s better to use less of it to make the same washing machine.
Important economic policy, however, is often made on the basis of reshoring various measures of industrial productivity. It’s not the absolute measure of productivity that matters, but productivity improvement year-over-year, and comparisons to competing economies.
It’s in managing one’s workforce where things get confusing. Is a pick-and-place robot more productive than two manual laborers? Of course, but what if those two manual laborers are paid two dollars an hour? In that case, the robot must be measurably more efficient at the task, otherwise it’s a high-tech money waster.
With relative wage levels and mixed workforces however, things get a lot more complex.
Offshore jurisdictions with low wages and few or no health benefits, safety rules or labor laws have always had an advantage where industrial automation replaces human worker functions task for task.
When that first unit began unloading a die-casting machine at the New Jersey GM plant in 1961, it did the same task formerly done by a human worker. That kind of one-for-one replacement will rarely be cost-effective, even in today’s low interest rates, given the relatively high capital cost of general-purpose robotics.
You can probably see where I’m going with this. Until recently, most mass production processes have been designed and are configured for human operations, with robotics acting to replace workers. Current and future industrial automation is designed differently; machines are configured to play into the robot’s strengths, minimizing work in process, linear and radial tool travel and space allocated per machine.
Is this the reconfiguration of production lines that generated the real productivity benefit of automation, not simply the accuracy and repeatability of software-driven end effectors? That’s the real driver of reshoring: the ability to create production processes which produce low-cost, high-quality goods using technologies that cannot be duplicated by human hands. A truly efficient automated process could not be duplicated cost-effectively even if wages were zero. Industry-wide, we’re not there yet, but it’s coming quickly, especially as lower-cost, pick-and-place robots like Rethink Robotics’ Baxter, for example, gain widespread acceptance.
In the meantime, reshoring continues for the traditional reasons: higher wages in Asia, lower wages here and domestic oil production keeping prices low. This is not sustainable in the long run.