Operion Agent

Industrial maintenance fails in two ways: alarms that ring too late, or never. Fixed-limit alerts wait for a raw sensor to cross a threshold, by which time the damage is advanced. In our evaluation the legacy alarm never fired in 9 of 40 fault runs. Operion Agent replaces that with a complete decision pipeline. A transparent statistical detector learns each machine’s normal behavior, removes the effect of plant load, and flags drift early. An AI agent running DeepSeek-V4-Flash on the AMD Token Factory API then reads the evidence and the equipment manual, names the fault, and cites its sources. Every claim is checked against the data before it reaches the technician. The alert goes to the right person on shift, with the likely cause and the next step. A repair-versus-replace analysis then compares the five-year cost of each option. On a simulated plant with four pump fault types (bearing wear, cavitation, misalignment, motor overheating), Operion Agent detected all 40 fault runs. The median AI warning was 36.4 hours, against 6.2 hours for the legacy alarm. It diagnosed 97.5% of faults correctly, with every diagnosis passing the evidence check and no fallbacks. Over 720 healthy hours it raised no false alarms. Our results come from a simulated plant, and we say so plainly. Operion Agent is built to catch the failure early, explain why, and tell people what to do.