Method and system for monitoring and optimizing the operation of an alumina rotary kiln

A system for real-time monitoring and optimizing the operation of an alumina rotary kiln in a plant, the system comprises:

• an input/output interface for receiving real-time data of the alumina rotary kiln, via a plurality of sources;
• one or more hardware processors;
• a memory in communication with the one or more hardware processors, wherein the memory further comprises:
• a preprocessor for pre-processing the received real-time data,
• the one or more hardware processors configured to predict a gas and a solid temperature profile in the alumina rotary kiln over a predefined time period using the preprocessed real time data and a thermal model stored in a database,
• the one or more hardware processors configured to predict a quality of alumina in real-time in terms of a set of quality parameters using the predicted gas and solid temperature profile, the preprocessed real time data and a quality model, wherein the quality model comprises a data driven model using an output of the thermal model to predict the quality of alumina, wherein the quality model is retuned by identifying set of hyper-parameters, set of training data or set of tuning parameters such that difference between a predicted quality and a sensor measurement is within acceptable limits, using the operating condition data, design data, ambient condition data as well as measured lab data for quality over a period Tq or more;
• and
• the one or more hardware processors configured to identify an optimum set of parameters by satisfying a predetermined criterion based on a set of desired quality parameters, wherein the set of desired quality parameters for the quality of alumina are received from a user;
• and a display device for displaying
• the identified optimum set of parameters on the display device, wherein the predetermined criteria is an upper limit and a lower limit for the set of alumina quality parameters, wherein optimization is triggered automatically based on a time delay and checks predicted value of the alumina quality against desired range of alumina quality set by an operator after a set period, and when a deviation is beyond an acceptable limit, an optimization loop is triggered;
• the real-time predicted quality of alumina on a display device;
• and
• predict, by a simulator, resulting thermal signatures and product quality parameters considering kiln condition and ambient conditions and fuel quality for what-if scenario analysis, upon obtaining values for parameters such as primary and secondary air distribution, kiln rotation speed, fuel flow rate, raw material feed;
• and
• provide, by the simulator, optimum values for parameters such as primary and secondary air distribution, kiln rotation speed, fuel flow rate, raw material feed to meet the criteria in if-what scenario analysis, upon obtaining the desired quality parameters or thermal signature on screen, wherein the simulation is saved to the database and settings are implemented in the plant for execution in real-time.

One or more non-transitory machine readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

• receiving real-time data of the alumina rotary kiln, via a plurality of sources;
• pre-processing, via one or more hardware processors, the received real-time data;
• predicting, via the one or more hardware processors, a gas and a solid temperature profile in the alumina rotary kiln over a predefined time period using the preprocessed real time data and a thermal model stored in a database;
• predicting, via the one or more hardware processors, a quality of alumina in real-time in terms of a set of quality parameters using the predicted gas and solid temperature profile, the preprocessed real time data and a quality model, wherein the quality model comprises a data driven model using an output of the thermal model to predict the quality of alumina, wherein the quality model is retuned by identifying set of hyper-parameters, set of training data or set of tuning parameters such that difference between a predicted quality and a sensor measurement is within acceptable limits, using the operating condition data, design data, ambient condition data as well as measured lab data for quality over a period Tq or more;
• displaying, via the one or more hardware processors, the real-time predicted quality of alumina on a display device;
• receiving, via the one or more hardware processors, a set of desired quality parameters for the quality of alumina from a user;
• identifying, via the one or more hardware processors, an optimum set of parameters by satisfying a predetermined criterion based on the received set of desired quality parameters, wherein the predetermined criteria is an upper limit and a lower limit for the set of alumina quality parameters,
• wherein optimization is triggered automatically based on a time delay and checks predicted value of the alumina quality against desired range of alumina quality set by an operator after a set period, and when a deviation is beyond an acceptable limit, an optimization loop is triggered;
• displaying, via the one or more hardware processors, the identified optimum set of parameters on the display device;
• predicting, by a simulator, resulting thermal signatures and product quality parameters considering kiln condition and ambient conditions and fuel quality for what-if scenario analysis, upon obtaining values for parameters such as primary and secondary air distribution, kiln rotation speed, fuel flow rate, raw material feed;
• and
• providing, by the simulator, optimum values for parameters such as primary and secondary air distribution, kiln rotation speed, fuel flow rate, raw material feed to meet the criteria in if-what scenario analysis, upon obtaining the desired quality parameters or thermal signature on screen, wherein the simulation is saved to the database and settings are implemented in the plant for execution in real-time.