Mohd Kamaruddin Abd Hamid | Universiti Teknologi Malaysia - UTM (original) (raw)

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Papers by Mohd Kamaruddin Abd Hamid

Research paper thumbnail of Integration of process design and controller design for chemical processes using model-based methodology

Computers & Chemical Engineering, 2010

In this paper, a novel systematic model-based methodology for performing integrated process desig... more In this paper, a novel systematic model-based methodology for performing integrated process design and controller design (IPDC) for chemical processes is presented. The methodology uses a decomposition method to solve the IPDC typically formulated as a mathematical ...

Research paper thumbnail of A Model-Based Methodology for Simultaneous Design and Control of a Bioethanol Production Process

In this work a model-based methodology to solve an integrated process design and control (IPDC) p... more In this work a model-based methodology to solve an integrated process design and control (IPDC) problem for a bioethanol production process is presented. The IPDC problem is formulated and solved such that the economic performance is optimized in terms of a cost effective design and controllable process. The concepts of attainable region (AR) and driving force (DF) are used within this methodology, to determine the optimal design-control of the process as well as to generate feasible alternatives. Based on this methodology, the optimal solution to the design-control problem is found by locating the maximum value of AR and DF for reactor and separator, respectively. The use of DF and AR concepts are shown to provide an optimal design with respect to energy consumption for the downstream separation units and with respect to controllability for the simultaneous saccharification and fermentation (SSF) bioreactor unit, respectively, used in the bioethanol production process.

Research paper thumbnail of A model-based methodology for simultaneous design and control of a bioethanol production process

Computers & Chemical Engineering, 2010

In this work a model-based methodology to solve an integrated process design and control (IPDC) p... more In this work a model-based methodology to solve an integrated process design and control (IPDC) problem for a bioethanol production process is presented. The IPDC problem is formulated and solved such that the economic performance is optimized in terms of a cost effective design and controllable process. The concepts of attainable region (AR) and driving force (DF) are used within this methodology, to determine the optimal design-control of the process as well as to generate feasible alternatives. Based on this methodology, the optimal solution to the design-control problem is found by locating the maximum value of AR and DF for reactor and separator, respectively. The use of DF and AR concepts are shown to provide an optimal design with respect to energy consumption for the downstream separation units and with respect to controllability for the simultaneous saccharification and fermentation (SSF) bioreactor unit, respectively, used in the bioethanol production process.

Research paper thumbnail of Problem-based Learning in Facilities Planning: A Pilot Implementation

Research paper thumbnail of Product Optimization of a Fed-batch Fermentation Process

This paper discusses the development of constrained optimization strategies for a fedbatch penici... more This paper discusses the development of constrained optimization strategies for a fedbatch penicillin fermentation process. To facilitate the study, a mathematical model of the system is developed based on published materials, and simulated using MATLAB software. Good agreement is obtained when the results are validated against published work. To provide on-line estimates of the difficult to measure penicillin concentration, Partial Least Squares model is employed. Using these estimates, good control of product concentration is established thus enabling it to be implemented as part of product concentration control loop. Further improvements are introduced using dynamic optimization aiming at increasing the achievable product concentration while satisfying all process constraints. Two strategies are considered. These are optimal control policy using direct-shooting algorithm and unconstrained Dynamic Matrix Control (DMC). From this two optimization approaches, it is possible to estimate the optimal operating conditions as substrate feed rate so that the systems presents high performance within threshold value limit. The result also revealed that the use of DMC approach is superior the direct shooting method in term of the penicillin concentration as well as penicillin purity. Results obtained in this study have exposed the potentials of dynamic optimization schemes in improving the product purity in a fed-batch fermentation process.

Research paper thumbnail of Neural Networks for Process Monitoring, Control and Fault Detection: Application to Tennessee Eastman Plant

This paper discusses the application of artificial neural networks in the area of process monitor... more This paper discusses the application of artificial neural networks in the area of process monitoring, process control and fault detection. Since chemical process plants are getting more complex and complicated, the need of schemes that can improve process operations is highly demanded. Artificial neural network can provide a generic, non-linear solution, and dynamic relationship between cause and effect variables for complex and non-linear processes. This paper will describe the application of neural network for monitoring reactor temperature, estimation and inferential control of a fatty acid composition in a palm oil fractionation process and detection of reactor sensor failures in the Tennessee Eastman Plant (TEP). The potential for the application of neural network technology in the process industries is great. Its ability to capture and model process dynamics and severe process non-linearities makes it powerful tools for process monitoring, control and fault detection.

Research paper thumbnail of Methodology Development for Designing Energy Efficient Distillation Column Systems

Distillation is the primary separation process widely used in the industrial chemical processing.... more Distillation is the primary separation process widely used in the industrial chemical processing. Although it has many advantages, the main drawback is its large energy requirement, which can significantly influence the overall plant profitability. However, the large energy requirement of these processes can be systematically reduced by using driving force and energy integration methods. This paper presents a methodology development for designing energy efficient distillation column systems based on those two methods. Accordingly, the proposed methodology consists of four hierarchical steps. In the first step, the systems of distillation column for multicomponent separation is designed based on the conventional distillation column design method. Then, the conventional distillation columns systems design is improved in terms of energy saving by using driving force method in the second step. It is expected in the third step that the distillation columns systems design can be further improved in terms of energy saving by using energy integration method. Finally, the distillation column systems design is evaluated in in terms of economic performance. By applying the proposed methodology, it is possible to make an early assumption on type of distillation column systems design that is the best in terms of energy saving and cost.

Research paper thumbnail of Integration of process design and controller design for chemical processes using model-based methodology

Computers & Chemical Engineering, 2010

In this paper, a novel systematic model-based methodology for performing integrated process desig... more In this paper, a novel systematic model-based methodology for performing integrated process design and controller design (IPDC) for chemical processes is presented. The methodology uses a decomposition method to solve the IPDC typically formulated as a mathematical ...

Research paper thumbnail of A Model-Based Methodology for Simultaneous Design and Control of a Bioethanol Production Process

In this work a model-based methodology to solve an integrated process design and control (IPDC) p... more In this work a model-based methodology to solve an integrated process design and control (IPDC) problem for a bioethanol production process is presented. The IPDC problem is formulated and solved such that the economic performance is optimized in terms of a cost effective design and controllable process. The concepts of attainable region (AR) and driving force (DF) are used within this methodology, to determine the optimal design-control of the process as well as to generate feasible alternatives. Based on this methodology, the optimal solution to the design-control problem is found by locating the maximum value of AR and DF for reactor and separator, respectively. The use of DF and AR concepts are shown to provide an optimal design with respect to energy consumption for the downstream separation units and with respect to controllability for the simultaneous saccharification and fermentation (SSF) bioreactor unit, respectively, used in the bioethanol production process.

Research paper thumbnail of A model-based methodology for simultaneous design and control of a bioethanol production process

Computers & Chemical Engineering, 2010

In this work a model-based methodology to solve an integrated process design and control (IPDC) p... more In this work a model-based methodology to solve an integrated process design and control (IPDC) problem for a bioethanol production process is presented. The IPDC problem is formulated and solved such that the economic performance is optimized in terms of a cost effective design and controllable process. The concepts of attainable region (AR) and driving force (DF) are used within this methodology, to determine the optimal design-control of the process as well as to generate feasible alternatives. Based on this methodology, the optimal solution to the design-control problem is found by locating the maximum value of AR and DF for reactor and separator, respectively. The use of DF and AR concepts are shown to provide an optimal design with respect to energy consumption for the downstream separation units and with respect to controllability for the simultaneous saccharification and fermentation (SSF) bioreactor unit, respectively, used in the bioethanol production process.

Research paper thumbnail of Problem-based Learning in Facilities Planning: A Pilot Implementation

Research paper thumbnail of Product Optimization of a Fed-batch Fermentation Process

This paper discusses the development of constrained optimization strategies for a fedbatch penici... more This paper discusses the development of constrained optimization strategies for a fedbatch penicillin fermentation process. To facilitate the study, a mathematical model of the system is developed based on published materials, and simulated using MATLAB software. Good agreement is obtained when the results are validated against published work. To provide on-line estimates of the difficult to measure penicillin concentration, Partial Least Squares model is employed. Using these estimates, good control of product concentration is established thus enabling it to be implemented as part of product concentration control loop. Further improvements are introduced using dynamic optimization aiming at increasing the achievable product concentration while satisfying all process constraints. Two strategies are considered. These are optimal control policy using direct-shooting algorithm and unconstrained Dynamic Matrix Control (DMC). From this two optimization approaches, it is possible to estimate the optimal operating conditions as substrate feed rate so that the systems presents high performance within threshold value limit. The result also revealed that the use of DMC approach is superior the direct shooting method in term of the penicillin concentration as well as penicillin purity. Results obtained in this study have exposed the potentials of dynamic optimization schemes in improving the product purity in a fed-batch fermentation process.

Research paper thumbnail of Neural Networks for Process Monitoring, Control and Fault Detection: Application to Tennessee Eastman Plant

This paper discusses the application of artificial neural networks in the area of process monitor... more This paper discusses the application of artificial neural networks in the area of process monitoring, process control and fault detection. Since chemical process plants are getting more complex and complicated, the need of schemes that can improve process operations is highly demanded. Artificial neural network can provide a generic, non-linear solution, and dynamic relationship between cause and effect variables for complex and non-linear processes. This paper will describe the application of neural network for monitoring reactor temperature, estimation and inferential control of a fatty acid composition in a palm oil fractionation process and detection of reactor sensor failures in the Tennessee Eastman Plant (TEP). The potential for the application of neural network technology in the process industries is great. Its ability to capture and model process dynamics and severe process non-linearities makes it powerful tools for process monitoring, control and fault detection.

Research paper thumbnail of Methodology Development for Designing Energy Efficient Distillation Column Systems

Distillation is the primary separation process widely used in the industrial chemical processing.... more Distillation is the primary separation process widely used in the industrial chemical processing. Although it has many advantages, the main drawback is its large energy requirement, which can significantly influence the overall plant profitability. However, the large energy requirement of these processes can be systematically reduced by using driving force and energy integration methods. This paper presents a methodology development for designing energy efficient distillation column systems based on those two methods. Accordingly, the proposed methodology consists of four hierarchical steps. In the first step, the systems of distillation column for multicomponent separation is designed based on the conventional distillation column design method. Then, the conventional distillation columns systems design is improved in terms of energy saving by using driving force method in the second step. It is expected in the third step that the distillation columns systems design can be further improved in terms of energy saving by using energy integration method. Finally, the distillation column systems design is evaluated in in terms of economic performance. By applying the proposed methodology, it is possible to make an early assumption on type of distillation column systems design that is the best in terms of energy saving and cost.