Optimization of process operations

In this section we provide four illustrations of optimization in practice. that is, optimization of process operations and design. These examples will help illustrate the general features of optimization problems, a topic treated in more, detail in Section 1.5. 

Optimization in Industriai Practice Optimization of Process Operations... 

The discussion presented in the previous sections assumes that a process model is available. However, optimization of process operation is also possible when process models are not available. In this case, one must rely on available experimental process data and/or empirical modeling approaches. For instance, the process performance can be mapped within the experimental region of interest with the help of experimental design techniques. Experiments are performed in accordance with the proposed experimental design and empirical cubic models (or other types of empirical models) are fitted to the obtained experimental data. Then, the empirical models can be used to provide the searched optima. This type of experimental design-based optimization procedure was performed to optimize the operation of fermentors used for production of bacterial polyesters (177], as it is very difficult to develop a fundamental model for bacterial polymerizations. In this particular case, the medium composition was manipulated to allow for maximization of polymer production and rninirnization of the batch time. 

Chapter Modeling and Advanced Control for Sustainable Process Systems starts with the inclusion of sustainability in process systems engineering by integrating process control with sustainability assessment tools for the simultaneous evaluation and optimization of process operations. The sustainability evaluation results provide information on whether the implementation of control systems is moving process performance toward a more sustainable operation. 

Modeling of polymer processing has more than a 60-year history. Computational methods gave many possihUities for optimization of processing operations. The chapter by Mitsotdis ( Computational Polymer Processing ) provides a comprehensive review of simulations and computational efforts for a majority of polymer processing operations and also forecasts the future development in this important part of polymer industry. 

While process design and equipment specification are usually performed prior to the implementation of the process, optimization of operating conditions is carried out monthly, weekly, daily, hourly, or even eveiy minute. Optimization of plant operations determines the set points for each unit at the temperatures, pressures, and flow rates that are the best in some sense. For example, the selection of the percentage of excess air in a process heater is quite critical and involves a balance on the fuel-air ratio to assure complete combustion and at the same time make the maximum use of the Heating potential of the fuel. Typical day-to-day optimization in a plant minimizes steam consumption or cooling water consumption, optimizes the reflux ratio in a distillation column, or allocates raw materials on an economic basis [Latour, Hydro Proc., 58(6), 73, 1979, and Hydro. Proc., 58(7), 219, 1979]. 

The complexity and reduced time constants of modern processes imply the adoption of high performance programmable controllers. This requires not only higher processing speed but also more advanced control algorithms that can optimize the process operation in real time. 

Continuous and detailed knowledge of process conditions is necessary for the control and optimization of bioprocessing operations. Because of containment and contamination problems, this knowledge must often be obtained without sampling the process stream. At present, conditions such as temperatme, pressure, and acidity (pH) can be measured rapidly and accurately. It is more difficult to monitor the concentrations of the chemical species in the reaction medium, to say nothing of monitoring the cell density and intracellular concentrations of hundreds of compounds. 

Like any businesses, bioanalytical laboratories perform operations that transform starting materials (samples and supplies) into products of higher value (quality reports continuing accurate sample concentration data). To maximize productivity and stay ahead of competition, bioanalytical scientists continuously invent, reinvent, and implement processes and techniques that generate more accurate and better quality reports with fewer resources (labor, time, capital, energy, and consumable goods). These continuous optimizations of laboratory operations drove the bioanalytical laboratories to begin... 

Process synthesis is a task of formulating the process configuration for a purpose by defining which operations or equipment are used and how they are connected together. There are two basic approaches for process synthesis 1) classical process synthesis, analysis and evaluation, and 2) optimization of process structure by using a suitable objective function. 

Backx, T. O. Bosgra and W. Marguardt. Integration of Model Predictive Control and Optimization of Processes. ADCHEM Proceedings, pp. 249-259, Pisa, Italy (2000). Baker, T. E. An Integrated Approach to Planning and Scheduling. In Foundations of Computer Aided Process Operations (FOCAPO), D. W. T. Rippin J. C. Hale and J. F. Davis, eds. CACHE Corporation, Austin, TX (1993), pp. 237-252. 

S. Garcia-Munoz, J.F. MacGregor, D. Neogi, B.F. Latshaw and S. Mehta, Optimization of batch operating policies. Part n. Incorporating process constraints and industrial applications, Ind. Eng. Chem. Res., 47(12), 4202-4208... 

Volumetric productivity is a good performance index in what concerns the optimization of bioreactor operation. It can be used in process improvement at a defined scale and also for process scale-up, since it is a dimensionless variable. Therefore bioreactor operation and scale-up for CLP and VLP production will be addressed as the identification of the operational conditions that result in the best volumetric productivity. 

For a highly concentrated product, a large system hold-up volume increases the potential for product loss. For concentration/diafiltration operations, scale-up may require re-optimization of process parameters, especially if membrane capacities are changed. However, every effort should be made to keep recirculation flux constant with similar inlet and outlet pressures. 

It should be quite clear now that time and money spent designing a robust process (where all of the critical process factors have been defined and their impact well documented) has the potential to save time and money later on, especially during the time leading up to, and immediately after, product launch. Designing an optimal process also has great benefit in the training of process operators so that they become well informed about the critical constraints of that process. 

PAC is done is much more complex, and is difficult to generalize. Many of those who work in this field continually discover new ways to glean information that allows for optimization of processing parameters and better control of the process. Better control is the prime goal as it will improve product quality, result in less waste, increase the safety of operations, and thus increase profitability. 

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