Where Does Your Plant Lose the Most Hours?

Every operator gives us a different answer, and the pattern is telling: the gasifier is rarely the bottleneck. The gas cleaning train is where hours disappear, every time the feedstock changes.

The graveyard proves it. Enerkem has one commercial plant after 24 years. Fulcrum filed Chapter 11 in 2024. Entrade is insolvent. The common thread is the cleaning train — catalyst poisoning, tar fouling, sorbent breakthrough — not the gasifier.

Mean time between interventions is the number that never makes it into a brochure. Vendors quote tar conversion at steady state on a perfect pellet. Nobody quotes what happens on Tuesday when the waste supplier delivers a different batch.

SyngaPure is designed around exactly that failure profile: three integrated purification stages — catalytic tar reforming, particulate filtration, sorbent removal — under one AI control layer. When one stage comes under load, the others adjust. Tar spikes, the reformer setpoint moves and the filter cycles adapt. Breakthrough starts, the system schedules the swap instead of waiting for an operator to read the trend.

The concept already held in the field. At COMETHA, the X-150 ran 1,939 hours across three feedstocks with different ash chemistry, moisture, and calorific value — the AI layer held syngas quality across every transition without operator intervention. 47 automated startups, 100% success. 94% uptime. Zero clinkering. 99.98% tar conversion.

The honest caveat: bench validation is still running. Chemistry is proven; industrial validation is next. We are not pretending otherwise.

Backed by the BMWK go-inno programme.

So the question stands. Where does your plant lose the most hours? Drop your actual mean time between interventions in the comments — that number is the one we are designing against.