Most manufacturers have tried AI or automation, but experimentation alone has not delivered a worthwhile return for everyone.
Most manufacturers have experimented with artificial intelligence or automation in some form, Manufacturing Dive reports. But the report also says not all have achieved a good return on their investment, drawing views from Pella, Hexion, and other companies.
That gap matters because a working demonstration is not the same as a profitable plant operation. A system may perform its task while delivering too little extra output, quality, or uptime to repay its purchase and operating costs.
Managers should set the business test before installing equipment. Choose a baseline, a target, and a measurement period. Useful measures might include units produced, defects, labor hours, downtime, maintenance cost, or energy use.
Integration belongs in that calculation. A robot or automated system may need to work with existing machines, production software, safety controls, and operator routines. Frequent manual corrections, difficult changeovers, or added support work can erase expected savings.
The available account does not establish which manufacturing tasks were tested, how investments were measured, or how many projects moved into regular production. It also does not establish plant-level results or payback periods for the companies mentioned.
The practical next step is to keep measuring after the trial ends. Compare the system’s full operating cost with a specific improvement during normal production—not just a successful demonstration.