Sriram Devanathan

Biography

Dr. Sriram Devanathan is the Head of Center for Excellence in Advanced Materials and Green Technologies and Professor & Vice-chair in the Department of Chemical Engineering and Materials Science. He comes to Amrita with ten years of industrial experience at the 3M Company in Minnesota, Texas and California (USA) and seven years experience in academic research as a graduate student at Iowa State University, USA, where he also received his Ph. D. He has a Certificate of Six Sigma Black Belt Training from 3M, and has successfully led quality improvement/cost reduction projects in various 3M Company manufacturing plants in the US, Canada, Singapore and Japan. His areas of interest include Low-cost Materials, Waste-to-Energy Technologies, Process Intensification,Six Sigma, Fault Diagnosis, Empirical Modeling, Data Mining, Statistical Process Control, Design of Experiments, and Process Modeling & Simulation. He has trained over 600 engineers, managers and operators in statistical methodology and software and Six Sigma. Dr. Sriram has significant expertise in CGMP (Current Good Manufacturing Practices) and Internal Auditing. He is the author of several publications in US technical journals.

Research Interest

Data Reconciliation & Gross Error Detection A chemical engineering plant contains a complex network of flow channels and storage units. For reasons of cost control, optimal operation, regulations, and safety, it is important and necessary to ensure material and energy accountability. The occurrence of measurement errors (fixed and random), as well as physical leaks, can hinder the accountability. Thus, our team is focused on finding ways to ensure accountability, with reasonable accuracy, in the presence of the obscuring factors. Techniques involving a combination of fundamental concepts of chemical engineering combined with statistical methods, are used to achieve the objectives, for various common scenarios: steady state processes, transient (dynamic) processes, and processes in which measurements of process parameters manifest serial correlation (due to the establishment of an engineering process control system, or due to other reasons). Other efforts include application of multivariate statistical methods to model predictive relationships useful in a chemical engineering context (one specific application is to detect the occurrence of adulteration of diesel). Plastics Reclamation and Conversion The rapidly growing consumption rate, combined with lack of adequate techniques & practices for recycling, indicates a vast opportunity for technology intervention aimed at plastics reclamation and conversion to virgin monomers or virgin polymers. Our group works on low cost technology alternatives for this purpose - specifically selective dissolution & reprecipitation and pyrolytic gasification. We also study intensified methods for separation and dissolution, such as with ultrasonics. Groundwater Transport Studies aimed at mathematical representation of transport phenomena assume importance in numerous applications. We are currently focused on hydrogeological transport, especially in the context of specific types of groundwater formations - seen in conjunction with soil properties, vegetation, and climatic conditions.