It’s well known that manufacturing in the US has fallen precipitously over the last few decades, especially in places like the Midwest’s Rust Belt.
Manufacturing in the United States has endured a pretty harrowing trajectory during the past few decades. The segment of Americans working in the industry has fallen from 32.1% of the total workforce at its peak in 1953 to roughly 8.5% in 2017, according to the Bureau of Labor Statistics.
A couple of years ago Radha Mistry, who leads foresight practice at Autodesk, presented a potential future for the manufacturing industry, a much more networked and flexible future. What if small towns impacted by local plant closures, with no jobs, no money, and a dying Mains Street were instead home to a new version of the industry? One modelled around “a network of configurable microfactories that leverages the manufacturing-as-a-service concept?”
Forward-thinking design workflows consider the afterlife of a building before it’s built: selecting low-impact materials and planning for the eventual disassembling of components to be repurposed elsewhere. As construction and manufacturing converge, could this type of innovative process extend to everything that’s made or built?
What if, somewhat like China is reinventing its Silkroad as the Belt and Road, the Rust Belt became the Rust Road?
Facilities would no longer be constrained by single-use equipment and highly specialized software tools capable of creating only a single product or part. Instead, think about one factory that could virtually upload a new toolset to reconfigure its workflow to meet new demands.
Instead of specializing in one part of a fixed process for one kind of product, workers could instead specialize in one part of a flexible system that adapts to changing products and demand.
A “nomadic systems architect” might mediate complex construction and manufacturing networks, assessing optimal technology solutions and resource constraints and then liaising between designers and builders across regions. […]
“[R]obot trainers” could be brought in to run simulations, use augmented reality (AR) and virtual reality (VR) to gather knowledge from workers, and then leverage those insights, coding them into machine-learning algorithms—ultimately training the robots to work better in partnership with humans.
Although ‘just’ a speculative scenario by Mistry’s team, these kinds of foresight exercises are based in research on real practices and trends, meant to provoke further thinking, a broadening of perspective, and thinking beyond the expected next steps, towards more innovative and, hopefully, more promising outcomes. With changing services, products, and supply chains, a network of flexible micro factories certainly sounds like an intriguing way of rekindling manufacturing regions.