Keynote Speakers
Prof. Dr. Gade Pandu Rangaiah
Prof. Dr. Gade Pandu Rangaiah joined the Department of Chemical and Biomolecular Engineering at the National University of Singapore (NUS) in 1982, where he is currently Emeritus Professor. He received his Bachelor, Masters and Doctoral degrees in chemical engineering, from Andhra University, IIT Kanpur and Monash University, respectively. Prior to his Doctoral study, he worked in Engineers India Limited for two years. Prof. Rangaiah received many teaching awards including the Annual Teaching Excellence Awards from NUS.
He supervised 26 PhD theses, 25 Masters theses, and published 212 journal papers on modeling, optimization and control of chemical and related processes. Prof. Rangaiah co-authored a book entitled “Reference Manual on Energy Recovery and Reuse (Under Singapore Certified Energy Manager Programme)” and co-edited 8 books on process optimization and control. In particular, he studied multi-objective optimization and its applications in the last two decades, edited the first book on multi-objective optimization in chemical engineering published in 2009 and its second edition published in 2017. For more details, browse https://blog.nus.edu.sg/rangaiah.
Topic Keynote Session 1: Multi-Objective Optimization and Multi-Criteria Decision Making for Achieving Sustainable Processes
Optimization for single objective is established with numerous applications in both academia and industrial practice, and many programs are available for single-objective optimization. On the other hand, many applications have more than one objective, particularly for achieving sustainable processes. Such applications require multi-objective optimization (MOO) and multi-criteria decision making (MCDM). Over the last two decades, there has been significant progress in MOO and its applications. After the formulation of the optimization problem, its solution consists of two main steps: (a) generation of Pareto-optimal (non-dominated) solutions using a suitable method (MOO), and (b) selection of one of the Pareto-optimal solutions (MCDM). Methods and programs are available for solving MOO problems and for MCDM. This keynote presentation provides an overview of both MOO and MCDM for achieving sustainable processes. First, MOO, Pareto-optimal solutions and MCDM are introduced. Then, MOO methods, procedure and applications in chemical engineering as well as objectives for sustainable processes are reviewed. MS Excel programs for MOO and MCDM, and their use are outlined. Finally, current challenges for further development of MOO and MCDM for sustainable processes are identified.
Dr SHAHRUL AZMAN ZAINAL ABIDIN
Dr Shahrul Azman Zainal Abidin (CEng FIChemE) is a Head of Process Control & Optimization (PCO) cum Custodian Engineer in the area of Process Control and Optimization at PETRONAS Group Technical Solutions. He graduated as a Chemical Engineer from California State University, Long Beach, USA in 1998 and received an MSc Gas Engineering degree from University of Technology Malaysia in 1996. He received her PhD in Chemical and Process Engineering Technology from Universiti Kebangsaan Malaysia in 2020. He is a Fellow of IChemE and Senior Member of AIChE with more than twenty years of experience in project & engineering management and specializing in process modelling and optimization of oil & gas facilities. Apart from developing PETRONAS owned process simulation software, iCON, he has developed and patented an Integrated Separation System Sep-iSYS for Slug handling, Sand, Inlet Heating and 3 Phase Separation technologies that are installed particularly suited for upstream oil & gas production facilities.
Topic Keynote Session 2: Hybrid First-Principle with Operational Data for Optimization of an Industrial Reactor Unit.
In the effort to maximize revenue and cash generation, it is crucial to identify and manage major pain point contributor(s) in the hydrocarbon value chain. To maximize production of propane value chain by addressing the run length limitation due to increasing rate of coking in endothermic reactor unit was studied. Hybrid of first principle and plant historical operation data were combined and used to model the proprietary reactor. Several high impact influential variables were identified and incorporated into model i.e. hydrocarbon throughput, hydrogen-to-hydrocarbon ratio, reactor inlet temperature and days-on-stream. Hybrid modelling approach is used to find optimum start-of-run operating condition within the licensor operating envelope, to control coke formation rate in the presence of variations in operating conditions throughout the run length and also to manoeuvre the intermediate operating strategies to achieve the desired run length. The current operation with implementation of new operating strategies derived from the model shows coke formation reduction up to 70% compared to the historical trending, on-track to achieve the desired run length equivalent to the catalyst expected life, which has never been achieved since in operation. The delta pressure profile across the screen can be predicted through utilizing first principle model combined with analysis from historical data. This model enables the user to run the possible operational conditions and evaluate the estimated/predicted DP profile, which is known to be the primary constraint in the reactor system, due to inevitable coke formation. The model can be further improved by incorporating the ability to predict the desired product yield with optimum influential variables set points with time.