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Inferential and virtual analyzers started to occupy a space on replacing physical process analyzers with the trust of accuracy and repeatability. AIGC inferential analyzers are built using analytical and empirical techniques with deep statistical regression to accurately estimate process parameters
A high-fidelity, dynamic simulation model, connected to the plant data system and distributed control system can be a useful analytical soft-sensing tool. AIGC simulation model calculates all relevant process parameters and can predict parameters that are not measured in the plant. The model can also estimate equipment performance indicators such as furnace efficiency, exchanger fouling, compressor efficiency, catalyst activity, etc. in real-time, which cannot be measured using physical instrumentation.
The simulator will also have an auto tuning module, which will ensure the simulation model remains current with changing plant conditions and replicates the natural process at all times.