Heating is often a major cost in industrial processes. Many companies require several heat sources and include extra sources for redundancy. This complexity frequently results in excess heat and unnecessarily high costs.
Production is usually controlled by a basic control system (e.g. DCS or SCADA). However, as process needs vary, production is not always optimized.
SentianController can automate the control of the heating system (burners/furnace) by learning system dynamics from historical data, which will then be used to predict the optimal set points for the desired output — even generalizing to scenarios never seen before — while at the same time reducing variation in output.
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