
ASSOCIATE PROFESSOR DR. NORASHID AZIZ
Qualifications: B.Eng. (USM), Ph.D. (Bradford)
Expertise: Batch Reactors, Modelling, Dynamic Optimisation, Process Control, Neural Network Technique
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- A. Azmi and N. Aziz, 2017, Comparison study of model based industrial low-density polyethylene production in tubular reactor, Chemical Engineering Transactions, 56, 751-756.
- S.A. Zulkeflee, S.A. Sata and N. Aziz, 2017, Auto-regressive with exogenous input model predictive controller for water activity in esterification, Chemical Engineering Transactions, 56, 217-222.
- M.N. Rosli and N. Aziz, 2016, Simulation of ethane steam cracking with severity evaluation, Materials Science and Engineering, 162, pp. 012017.
- N. Mohd and N. Aziz, 2016, Performance and robustness evaluation of Nonlinear Autoregressive with Exogenous input Model Predictive Control in controlling industrial fermentation process, Journal of Cleaner Production, 136, pp.42-50.
- F. S. Rohman, S.Abdul Sata and N. Aziz, 2016, Application of online dynamic cascaded-conditional based optimization for handling model uncertainty in semi batch autocatalytic esterification process, ARPN Journal of Engineering and Applied Sciences, 11 (10), pp. 6541-6548.
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- Optimization and Control of Ethylene Steam Cracking Furnace or any other chemical processes.
- Model Based Control for Isopropyl Myristate in Semibatch Reactive Column or any other chemical processes.
- Modeling and optimization study for Water Treatment Plant or any other chemical process
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- Online Dynamic Optimization Studies of Catalyzed Esterification of Propionic Anhydride With 2-Butanol in the Presence Disturbance and Uncertainty
- Nonlinear Model Predictive Control (NMPC) for Industrial Low Density Polyethylene (LDPE) Tubular Reactor
- Real-Time Implementation of Nonlinear Autoregressive with Exogenous Input Model Predictive Control Strategy for Batch Esterification Reactor
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- Simulation and Optimization of Biodiesel Production from Dimenthyl Carbonate in Batch Reactor
- Development of Inferential Model for Predicting Ethylene Steam Cracking Furnace Product using Artificial Neural Network
- Nonlinear Model Predictive Control for Bioethanol Fermentation Process