Oscar A. Iribarren

Optimal design of protein production plants with time and size factor process models

In this work we propose an optimization model for the design of a biotechnological multiproduct batch plant. A first level of detail posynomial model is constructed for each unit, as well as decisions regarding the structural optimization of the plant. A particular feature of this model is that it contains composite units in which semicontinuous items operate on the material contained by batch items. This occurs in the purification steps, in particular with the microfilters operating between retentate and permeate vessels, and with the homogenizer and ultrafilters operating on the material contained in a batch holding vessel. Also, the unit models rely on batch operating time expressions that depend on both the batch size and the size of semicontinuous items. The model takes into account all of the available options to increase the efficiency of the batch plant design: unit duplication in‐phase and out‐of‐phase and intermediate storage tanks. The resulting mathematical model for the minimization of the plant capital cost is a mixed integer non‐linear program (MINLP), which is solved to global optimality with an implementation of the outer approximation/ equality relaxation/ augmented penalty (OA/ER/AP) method. A plant that produces four recombinant proteins in eight processing stages is used to illustrate the proposed approach. An interesting feature of this example is that it represents an attempt to standardize a plant for the production of both therapeutic and nontherapeutic proteins; the model applied is generic and can thus be applied to any such modular plant. Results indicate that the best solution in terms of minimal capital cost contains no units in parallel and with intermediate storage tank allocation.

Strategies for the simultaneous optimization of the structure and the process variables of a protein production plant

Abstract Process performance models for a multiproduct batch protein plant are used to exploit alternative strategies in the optimization of both the process variables and the structure of the plant. Simple process performance models are used to describe the unit operations, which renders explicit expressions for the size and time factor model in the design of batch plants. In the proposed approach the process variables are optimized regardless the plant structure constraints, which are left as a posterior decision. This optimization is done in a single product-free intermediate storage (SP-FIS) scenario, unbiased with any plant structure. The approach is compared to the case of recipe values for the process variables and to the best optimal solution for the nonconvex mixed integer nonlinear program (MINLP), which arises when simultaneously optimizing the structure and the process variables. This last optimization model is hard to solve and its global solution remains as an open problem. The proposed approach generates solutions very close to the ones obtained from nonconvex MINLP and is quite superior than simply resorting to recipes. We also study the role of process variables in this approach. It is found that they behave as in continuous processes by trading off cost components, with a smooth dependence on the overall cost. Moreover, for feasible designs that include the size and time constraints that correspond to the plant structure, the process variables accommodate the size and time factors to reduce idle times and equipment under-occupancy.

Dynamic simulations in the design of batch processes

Abstract This paper presents a conceptual procedure for the modeling of batch plants with posynomial expressions, and a resolution strategy for the optimization of the process decision variables, where dynamic simulation provides the parameters for the analytical posynomial expressions. With this resolution sequence, the optimization of the process decision variables remains affordable and trouble-free.

Multiperiod optimization for the design and planning of multiproduct batch plants

Abstract This paper presents a general multiperiod optimization model, which simultaneously solves the design and planning decisions in multiproduct batch plants. Therefore, the trade-offs between both problems are taken into account as well as variations due to seasonal effects, demand patterns, etc. From the design point of view, the model is formulated considering batch and semicontinuous units, the allocation of intermediate storage, and structural decisions. Following the usual procurement policy, equipment is provided using discrete sizes. From the planning point of view, the formulation takes into account both products and raw materials inventories, product demands and raw materials supplies that vary seasonally in a multiperiod approach. The objective is the maximization of an economic function, which considers incomes, and both investment and operation costs. A plant that produces five oleoresins in seven stages is used to illustrate this approach.

SELECTION OF MULTICOMPONENT BATCH DISTILLATION SEQUENCES

As in continuous distillation systems, the design of batch distillation begins with the selection of a sequence of separations. This paper considers the usual case where the column processes multicom-ponent mixtures with the recycle of intermediate cuts. It is proved that this cyclic operation does converge to a “steady state” balance. This permits to model batch distillation with recycle as a function of the steady state variables, i.e. without the need of successive simulations to obtain the steady state. Furthermore, we use simplified analytical models which permit a quick approximation to the optimal design of a given sequence, thus aiding the designer in the screening of alternative separation sequences, to preselect one, or a small set of good sequences.

A Simulation Approach to the Design and Operation of Multiproduct Batch Plants

This paper presents a strategy for the design of multiproduct batch plants that permits the use of detailed dynamic models to represent the stages involved in the process. The use of base case simulations at the decoupled solution of the modules into which the plant is decomposed yields a strategy that iterates on dynamic simulations and optimization steps. The merits of such a strategy are robustness, reliability, reuse and full exploitation of already developed technologies. The results obtained so far are encouraging. It is possible to handle rigorous models that take into account the tradeoffs among the different decision variables, the stages and the products. This makes it possible to arrive at conclusions and to evaluate alternatives not approached in the past. Different scenarios and applications of this approach are analysed.

Modeling and optimization of biological sequential batch reactors

Abstract This work deals with modeling and operation optimization of biological sequential batch reactors (SBR). The SBR is a fill-and-draw biological sludge system for wastewater treatment. In this system, wastewater is added to a single batch reactor, treated to remove undesirable components, and then, discharged. In this paper, a global model of a gas-solid-liquid SBR is presented to investigate and optimize operational strategies. The model can address the differences between aerated and anaerobic systems by assigning adequate parameter values related to the aeration and reaction systems. Fluctuating operation conditions during cycles such as disturbances in the organic loading rate, stirring rate and cycle time, result in strong numerical discontinuities that can be included in the simulation schedules. An existing set of experimental data is used to show a model application based on an anaerobic SBR. A good agreement was obtained between experimental and predicted values. Optimization results are based on minimizing the reaction time/total cycle time ratio subjected to path pH constraints and interior- and end-point constraints related to the pollutant removal efficiency and settling conditions. A decrease of 22% in the total cycle time, i.e. an increase in the organic loading rate from 787 to 985 mg dm−3 d−1 is reached without modifying the quality of effluent.

Optimal Process synthesis for the production of multiple recombinant proteins

This work presents an optimization model for the synthesis of bioprocesses that contain batch and semi-continuous items that can be duplicated and operated either in or out of phase. The model minimizes the overall plant cost and is composed of sizing and cycle time constraints, multiple-choice constraints for host and stage selection as well as production targets for each product are enforced in the model. Results on a 15-stage plant that processes four products under four different hosts show that the nature of the problem greatly affects host selection, plant structure and selection of unit operations.

Performance analysis of fermentation batch processes by decoupled dynamic simulations

Abstract This paper presents a performance analysis of a typical fermentation batch process by applying the method of Decoupled Dynamic Simulations to integrate the models that describe the behavior of the stages with the overall plant design and optimization. This kind of analysis allows the determination of the optimal value for some decision variables which have an important economic impact on the performance of the process. By implementing a complete case study, typical trade-off variables are illustrated. A better insight on the trade-off involved and on how the process variables affect different components of the performance index is obtained as a result of the analysis. The simulation of whole batch processes is a formidable task but the Decoupled Dynamic Simulations methodology greatly simplifies the computational burden and makes it affordable.

A new strategy for process simulation with the sequential modular approach

Abstract The “sequential modular” approach is the most often used approach for process simulation. However, it shows certain pitfalls such as the large computation time required by the resolution and some difficulties to approach design and optimization problems. In order to overcome these difficulties a new resolution strategy has been incorporated to the process simulator simbad . Here, the resolution of modules is not exclusively based on the streams that physically enter it but other stream combinations are considered valid as far as the resolution of the system of equations is feasible. This method has helped solving different examples with a noticeable decrease in the required computation time.