JODHPUR, 19-October-2022: Indian Institute of Technology Jodhpur has collaborated with industry partners to develop Data Pipeline Build-up and Machine Learning Model for Heat Exchangers of Oil and Petroleum Refineries. The work is being done in collaboration with Algo8 AI Private Limited.
Prof. Pradip Kumar Tewari, Head, Department of Chemical Engineering, and Dr. Angan Sengupta, Assistant Professor, Department of Chemical Engineering and Affiliated Faculty in SAIDE, IIT Jodhpur, along with their research team of Post Graduate Students are providing consultation service for this project.
Fouling of heat exchangers is a common phenomenon in refineries. Therefore, these units need to be periodically maintained through a complete shutdown or bypassing the maintained unit in the network. For its proper functioning, a controlled and schedule-based maintenance of heat exchangers is required. This particular problem requires a fundamental understanding of the applications of process engineering and data modelling techniques for a wide range of chemical engineering process units in industries, i.e., heat exchangers.
Speaking about the problem statement of this project, Prof. Pradip Kumar Tewari, Head, Department of Chemical Engineering, IIT Jodhpur, said, “Researchers at IIT Jodhpur are well capable of dealing with such a fundamental problem with its traditional chemical engineering knowledge base amalgamated with modern modelling and computation-based know-how in the field of chemical engineering.”
Highlighting the project, Dr. Angan Sengupta, Assistant Professor, Department of Chemical Engineering and Affiliated Faculty in SAIDE, IIT Jodhpur, said, “This particular project depicts that the present-day Chemical Engineering, of which computation for establishing industry 4.0 is an integral part, has traversed a long way from traditional Chemical Engineering and is capable to meet the new challenges of various process industries. To this end the Department of Chemical Engineering at IIT Jodhpur is well equipped.”
To address the same, the research team has developed a data-based model for control and schedule maintenance of heat exchanger networks to increase the efficiency of refineries. The provided solution includes:
- Comprehensive and verified predictive cleaning schedule for pre-heat trains
- Graphical interface to different refinery units for control mechanism
- Cleaning and purging data quality matched with the industry specification
This developed model can address the problem of fouling of heat exchangers in Oil refineries and can be applied in any Petroleum and allied industries.
Along with this, other objectives of this project include:
- Ø Condition monitoring of Heat Exchanger trains
- Ø Assess the network impact of each heat exchanger unit
- Ø Suggest the next scheduled date for cleaning
- Ø A graphical user interface to provide to visualize the predicted results and to verify the accuracy of the model
- Ø Model-based scheduled maintenance for Heat exchanger units at Oil Refinery sites to reduce overall maintenance costs
- Ø Model-based improved asset availability with in-time warnings
- Ø Model-based Improved shutdown turn-around time
IIT Jodhpur aims at responding to societal challenges using transformational technologies/ interventions with a multidisciplinary approach.
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