Journal Articles

1. Palla, G. L. P., & Pani, A. K. (2023). Independent component analysis application for fault detection in process industries: Literature review and an application case study for fault detection in multiphase flow systems. Measurement, 112504. Link
2. Arpitha, V., & Pani, A. K. (2022). Machine Learning Approaches for Fault Detection in Semiconductor Manufacturing Process: A Critical Review of Recent Applications and Future Perspectives. Chemical and Biochemical Engineering Quarterly, 36(1), 1-16. Link
3. Venkata Vijayan S., Mohanta, H. K., & Pani, A. K. (2022). Adaptive non-linear soft sensor for quality monitoring in refineries using Just-in-Time Learning—Generalized regression neural network approach. Applied Soft Computing, 119, 108546. Link
4. Pani, A. K. (2022). Non-linear process monitoring using kernel principal component analysis: A review of the basic and modified techniques with industrial applications. Brazilian Journal of Chemical Engineering, 39, 327-344. Link
5. Venkata Vijayan S., Mohanta, H. K., & Pani, A. K. (2021). Support vector regression modeling in recursive just-in-time learning framework for adaptive soft sensing of naphtha boiling point in crude distillation unit. Petroleum Science, 18(4), 1230-1239. Link
6. Beena A.M., Pani, A. K. (2020). Fault Detection of Complex Processes Using nonlinear Mean Function Based Gaussian Process Regression: Application to the Tennessee Eastman Process. Arabian Journal for Science and Engineering, 46, 6369-6390. Link
7. Singh, H., Pani, A. K., Mohanta, H. K. (2019). Quality monitoring in petroleum refinery with regression neural network: Improving prediction accuracy with appropriate design of training set. Measurement, 134, 698-709. Link
8.  Morey, A., Pradhan, S.,  Kumar, R. A., Pani, A. K., Vijayan, V. S., Jain, V., Gupta, A. (2019) Pollutant monitoring in tail gas of sulfur recovery unit with statistical and soft computing models. Chemical Engineering Communications, 206, 69-85. Link
9.  Siddharth, K., Pathak, A., Pani, A.K. (2019) Real-time quality monitoring in debutanizer column with regression tree and ANFIS. Journal of Industrial Engineering International, 15, 41-51. Link
10.  Pani, A. K., Mohanta, H. K. (2016). Online monitoring of cement clinker quality using multivariate statistics and Takagi-Sugeno fuzzy-inference technique. Control Engineering Practice, 57, 1-17. Link
11. Pani, A. K., Amin, K. G., & Mohanta, H. K. (2016). Soft sensing of product quality in the debutanizer column with principal component analysis and feed-forward artificial neural network. Alexandria Engineering Journal, 55, 1667-1674. Link
12. Pani, A. K., & Mohanta, H. K. (2015). Online monitoring and control of particle size in the grinding process using least square support vector regression and resilient back propagation neural network. ISA transactions, 56, 206-221. Link
13. Pani, A. K., & Mohanta, H. K. (2014). Soft sensing of particle size in a grinding process: Application of support vector regression, fuzzy inference and adaptive neuro fuzzy inference techniques for online monitoring of cement fineness. Powder Technology, 264, 484-497. Link
14. Pani, A. K., Vadlamudi, V. K., & Mohanta, H. K. (2013). Development and comparison of neural network based soft sensors for online estimation of cement clinker quality. ISA transactions, 52(1), 19-29. Link
15. Pani, A. K., & Mohanta, H. K. (2011). A survey of data treatment techniques for soft sensor design. Chemical Product and Process Modeling, 6(1). Link
16. Pani, A., & Mohanta, H. K. (2009). Application of soft sensors in process monitoring and control: A review. The IUP Journal of Science & Technology, 5(4), 7-20. Link
17. Pani, A. K., Jha, R. K., & Singh, K. K. (2006). Studies on Smith predictor control scheme. Chemical Engineering World, 41, 55-59.
    

1.   Agrawal, G., Chaudhary, A., & Pani, A. K. (2020, April). Temperature Optimization in Non-isothermal Tubular Reactor using Genetic Algorithm. In 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA) (pp. 23-26). IEEE. Link

2.    Shukla, A., Bhatt, H., & Pani, A. K. (2020, February). Variable selection and modeling from NIR spectra data: A case study of diesel quality prediction using LASSO and Regression Tree. In 2nd International Conference on Data, Engineering and Applications (IDEA) (pp. 1-6). IEEE. Link

3.    Basu D., Pani, A. K. (2019, February) Back pressure monitoring of power plant condenser using multiple adaptive regression spline. In 2nd International conference on Computing, Communications and Data Engineering (CCODE-2019). Link

4.     Ahuja, K., Pani, A. K. (2018, February) Software sensor development for product concentration monitoring in fed-batch fermentation process using dynamic principal component regression. In 2nd International conference on soft computing and network systems (ICSNS), IEEE. Link

5.    Jain, V., Kishore, P., Kumar, R. A., Pani, A. K. (2017, February) Inferential sensing of output quality in petroleum refinery using principal component regression and support vector regression. In Advance Computing Conference (IACC), 2017 IEEE 7th International, pp. 461-465. IEEE. Link

6.    Pani, A. K., & Mohanta, H. K. (2013, February). A hybrid soft sensing approach of a cement mill using principal component analysis and artificial neural networks. In Advance Computing Conference (IACC), 2013 IEEE 3rd International (pp. 713-718). IEEE. Link

7.    Pani, A. K., Amin, K. G., & Mohanta, H. K. (2012, July). Data driven soft sensor of a cement mill using generalized regression neural network. In Data Science & Engineering (ICDSE), 2012 International Conference on (pp. 98-102). IEEE. Link

8.    Pani, A. K., Vadlamudi, V., Bhargavi, R. J., & Mohanta, H. K. (2011, July). Neural Network Soft Sensor Application in Cement Industry: Prediction of Clinker Quality Parameters. In Process Automation, Control and Computing (PACC), 2011 International Conference on (pp. 1-6). IEEE. Link

9.  Pani  A. K., & Mohanta H. K., (2011, February) Importance of Data Analysis and Treatment for Soft Sensor Design: Application to Continuous Rotary Cement Kiln. 2nd Conference on Advances in Chemical Engineering, Thapar University, AChemE - 2011.

10.  Vadlamudi V. K., Pani A. K., Bhargavi R. J., Mohanta H. K, (2011, December). Development of Fuzzy Logic Based Soft Sensor for Prediction of Free Lime Content in the Cement Clinker. Indian Chemical Engineering Congress CHEMCON – 2011.

11.  Pani A. K., Vadlamudi V. K., Bhargavi R. J., Mohanta H. K., An RBF Neural Network based Soft Sensor Development for Prediction of Cement Clinker Properties. Indian Chemical Engineering Congress CHEMCON – 2011.