Right now, over 69% of German Manufacturers are using Artificial Intelligence in some capacity. Their progress has been rapid, and adoption of everything from AI predictive maintenance on their high-speed rail to demand forecasting in production scheduling has put Germany at the forefront of machine learning in Europe and the rest of the world.
It’s impressive, even overwhelming, for businesses back home that are still reliably producing the same way they have been for years. For all of that advancement, however, the Germans won’t be too hard to catch. Let me explain.
A recent German article goes into detail on concern in the German manufacturing industry about losing their competitive edge to other nations. The simple reason is the technology they’ve adopted is neither proprietary nor out of reach for businesses worldwide. Cutting edge machine learning algorithms are freely available online for any data scientist with the know-how to use them. That means anybody can get custom machine learning set up for their business at a reasonable level of investment.
To break it down even further, the statistic of almost 70% of German manufacturers actively using AI covers a lot of applications. At the very high-end their transportation system can actively monitor degradation from millions of data points pulled in real time. This is an enormously expensive piece of technology that takes huge coordinated effort (and budget) to pull off. On the more reasonable side, machine learning can be used for tasks as simple as translation and language interpretation. That isn’t so different from software people already use on a daily basis, which suddenly makes the 70% statistic not so hard to imagine.
AI in manufacturing can easily be broken down into 2 main areas:
- AI using data from automated assembly lines
- Everything else
A hyper-efficient automated assembly line has tons of data. The robots connect and store all of their activity to a computer, where it can be analyzed and used for improvements, maintenance, and production statistics. This tightly controlled environment is perfect for AI.
As an example, some assembly lines have installed cameras pointing at common failure points on their automated machinery. Thousands of pictures are taken every day and examined by a machine learning algorithm to compare against pictures of previously failed machinery. By finding patterns in signs of wear and stress, the computer can accurately predict which machines are going to fail before any interruption to the production process occurs. That means near continuous assembly without unexpected downtime, which can quickly cost a manufacturer tens of thousands of dollars. In that sense, a custom AI predictive maintenance system can pay for itself in a single accurate prediction.
Any United States business already using automated systems is probably actively considering AI. It’s a logical step in a business model based on having a competitive advantage in technology.
Many other US manufacturers don’t have futuristic assembly lines populated by uncanny robots. These manufacturers are the backbone of the American economy, producing valuable and reliable goods that keep our small towns alive and our national commerce thriving. These businesses have tried and true methods that rely on hard working human labor to keep the lines running. Businesses like this might not see the need for cutting-edge technology like machine learning, and thus miss opportunities that come with improving their processes through automation.
At a basic level, all businesses have the opportunity to benefit from machine learning automation. The most mundane tasks in a business fall into paperwork and forms. Countless labor hours are spent filling out routine paperwork for things like tax documents, insurance, purchase orders, invoices, government regulation, and many other formulaic business documents. AI-driven paperwork automation can automatically update database fields and file documents with limited human input. That means you can take your office employees off of constantly filling out the same paperwork and assign them to more valuable tasks like process improvement and reporting.
By adopting easily available new technology, businesses can rapidly join the Automated Revolution. That will put American Manufacturers back in the global leadership position for cutting edge machine learning technology.