Revolutionizing Metal Manufacturing Through AI!
High school students may use AI to compose a research paper, then verify it for plagiarism and use AI-checking software to avoid being discovered. They do every effort to avoid truly picking up the skill of writing. In a similar way, a shop owner engages press brake operators who primarily just learn how to use the parts that are handed to them.
They never learn about bend allowances and deductions, k-factors, the behavior of various metals, the formation of the radius, back gauging techniques, bump bending, etc. — all the possibilities that air forming on a press brake provides, in general. Simply put, they follow the machine’s instructions.
Companies may use technology as a crutch in these situations, using it to avoid dealing with employees who don’t show up, make mistakes all the time, or don’t care. Technology thus becomes the only point of differentiation, at least until the store down the street makes a comparable investment.
The potential impact of AI on the knowledge occupations that everyone assumed were immune to automation is what makes it so disruptive. The truth could be a little more complicated, especially when you take into account how it might affect the design shop of the future.
Think about the press brake operators once again. The fabricator makes a training investment this time. With a basis in metal fab grammar, they are able to be inventive and push the boundaries. They begin to make connections as well.
They discuss micro tabbing and nesting techniques, how many little brackets can be bent at simultaneously, and how part removal automation can lift and stack a mini-nest of small parts with laser and punch press workers.
The options seem limitless. In these settings, shop floor occupations are knowledge jobs as well, and thus are less likely to be automated away than other roles in the fab shop. People are still required for operation, maintenance, and process improvement in even the most highly automated industries.
The narrative shifts as you enter the workplace. A few bespoke fabricators currently provide automated order processing and quotation. When I went to 247TailorSteel in The Netherlands seven years ago, one of the most spectacular enterprises I’ve ever seen, there were only two people working there.
A large number of employees simultaneously controlled several press brakes with automatic tool changes, lasers, and automated guided vehicles that transported components between operations.
Clients received quotations right away after uploading 3D CAD files. Approved orders were automatically processed, scheduled, and nested. Other US businesses, notably OSH Cut in Utah (whose creator Caleb Chamberlain also contributes a piece to Fabricator.com), are already adopting this strategy.
I seem to remember the founder of 247TailorSteel saying he was hesitant to provide more services like welding and assembly since it would make automating the order flow more difficult. It is one thing to quote a cut and bent item, but it is quite another to quote a substantial subassembly that includes a range of manufactured and acquired components.
Will this always remain the case, though, given how much processing power has advanced recently? Very likely not. Yet, given the foundation that is being set in other areas, automated quoting, scheduling, and order processing algorithms may someday fall under the umbrella of artificial intelligence.
After all, AI is currently writing computer code. If you search for “AI code generator,” a list of websites that translate natural language will appear.
One day, each of us could be able to simply ask an AI engine to “write a program that would manage orders for this project” without any further interaction. Several firms are already using low-code programs like Microsoft Power Apps, which is included with Office 365, to create bespoke software, whether it be for task tracking, inspection reporting, or anything else. Would AI enable low-code applications to transition to no-code apps?
Despite all of this, businesses still require individuals to conceptualize such software in the first place. It’s still artificial, after all. At least for the time being, it just carries out our instructions.
It will be more difficult for individuals to conceive of novel solutions if they rely too heavily on technology. In a future when AI has taken over,
In conclusion, AI is already changing and will continue to change the metal production business. AI has the potential to greatly boost efficiency, lower costs, and promote sustainability in the sector through optimizing production processes, enhancing product design, and predictive maintenance.
To make sure that AI technologies are employed in a way that benefits the business and society as a whole, it is crucial to properly supervise their deployment. AI has the potential to be a potent instrument for fostering innovation and expansion in the metal production sector with the right planning and management.
