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Application of Statistical Modeling and Hypothesis Testing to Reinforce Model Validation Concepts in Bioprocess Control Laboratory


Affiliations
1 Department of Biotechnology, KLE Technological University, Hubballi - 31, India
2 Department of Mathematics, KLE Technological University, Hubballi - 31, India
 

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Bio-Process Control is the application of automatic control in the field of Biotechnology. The course emphasizes on the dynamic behaviour, physical and empirical modeling of bio-systems and advanced control strategies. The primary objective of process control is to maintain a process at the desired operating conditions with quality standards in an economic way and with safety aspects in place. In this backdrop, the present study was implemented as an exercise and structured inquiry experiments in Bioprocess Control Laboratory for VI semester undergraduate students of Biotechnology engineering. The course was hitherto taught in a conventional approach with analysis and interpretation of dynamic responses of different systems with standard inputs. The delivery of the exercise was implemented in three phases namely training, execution and assessment phase. In the present study dynamic response of control system was predicted with models and then compared with experimental observations. The resulting deviations therein, were analyzed for the possible underlying reasons and a chisquare goodness of fit test was performed to validate the model. The assessment of the students’ performance was done on individual basis through a Rubrics-based approach and attainment of the Program outcomes addressed was recorded which ranged from 80-95 %. The study helped in addressing the graduate attributes related to the investigation of complex problem, analyze the correlation of the experimental outcomes with underlying theoretical concepts and interpretation of results. A formal feedback from the students revealed that the active learning approach enhanced the understanding of the control engineering concepts through the application of statistical modeling and analysis.

Keywords

Bio-Process Control, Statistical Methods, Hypothesis Testing, Chi-Square Goodness of Fit Test, Model Validation, Regression Analysis.
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  • Application of Statistical Modeling and Hypothesis Testing to Reinforce Model Validation Concepts in Bioprocess Control Laboratory

Abstract Views: 315  |  PDF Views: 170

Authors

Laxmikant Patil
Department of Biotechnology, KLE Technological University, Hubballi - 31, India
Gururaj Bhadri
Department of Mathematics, KLE Technological University, Hubballi - 31, India
Shivalingsarj Deasi
Department of Biotechnology, KLE Technological University, Hubballi - 31, India
Anil Shet
Department of Biotechnology, KLE Technological University, Hubballi - 31, India
Veeresh Hombalimath
Department of Biotechnology, KLE Technological University, Hubballi - 31, India

Abstract


Bio-Process Control is the application of automatic control in the field of Biotechnology. The course emphasizes on the dynamic behaviour, physical and empirical modeling of bio-systems and advanced control strategies. The primary objective of process control is to maintain a process at the desired operating conditions with quality standards in an economic way and with safety aspects in place. In this backdrop, the present study was implemented as an exercise and structured inquiry experiments in Bioprocess Control Laboratory for VI semester undergraduate students of Biotechnology engineering. The course was hitherto taught in a conventional approach with analysis and interpretation of dynamic responses of different systems with standard inputs. The delivery of the exercise was implemented in three phases namely training, execution and assessment phase. In the present study dynamic response of control system was predicted with models and then compared with experimental observations. The resulting deviations therein, were analyzed for the possible underlying reasons and a chisquare goodness of fit test was performed to validate the model. The assessment of the students’ performance was done on individual basis through a Rubrics-based approach and attainment of the Program outcomes addressed was recorded which ranged from 80-95 %. The study helped in addressing the graduate attributes related to the investigation of complex problem, analyze the correlation of the experimental outcomes with underlying theoretical concepts and interpretation of results. A formal feedback from the students revealed that the active learning approach enhanced the understanding of the control engineering concepts through the application of statistical modeling and analysis.

Keywords


Bio-Process Control, Statistical Methods, Hypothesis Testing, Chi-Square Goodness of Fit Test, Model Validation, Regression Analysis.



DOI: https://doi.org/10.16920/jeet%2F2021%2Fv34i0%2F157160