Jorge M. Montagna

Optimal design for sustainable bioethanol supply chain considering detailed plant performance model

Abstract The always increasing energy demand combined with the declining availability of fossil fuels is driving forces for the investigation of renewable energy sources. In this context, bioethanol is considered as one of the most appropriate solutions for short term gasoline substitution. Then, the motivation of this work is to propose a MINLP optimization model for a sustainable design and behavior analysis of sugar/ethanol supply chain (SC). A detailed model for ethanol plant design is embedded in the SC model, and therefore plant and SC designs are simultaneously obtained. Yeast production and residue recycles are taken into account in order to assess the environmental impact. The inclusion of sustainability issues in the model produces both economic and operative changes in SC and plant designs. The simultaneous optimization of these elements allows the evaluation of several compromises among design and process variables. These issues are highlighted throughout the evaluated studied cases.

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.

The optimal retrofit of multiproduct batch plants

This paper presents new alternatives in the retrofit model of multiproduct batch plants. Besides the duplication of the batch units implemented in previous works, the model considers the inclusion of intermediate storage tanks. These tanks can be plainly added or replace existing units that can be sold. The allocation of intermediate storage tanks is not considered in the previous retrofit works, even if this alternative is not new in the design of multiproduct batch plants. This option allows getting more efficient and real world solutions, although it requires working with a more complex model.

Alternatives in the optimal allocation of intermediate storage tank in multiproduct batch plants

Optimal allocation of intermediate storage tanks is an important issue in a batch plant to reduce its cost. In this work the design of multiproduct batch plant is analyzed. The proposed model considers simultaneously the possibility of having parallel units and intermediate storage tanks. The location of the storage tanks can be variable for each product. The problem is modeled as a MINLP (Mixed Integer Non Linear Program). This approach is compared to the one proposed by Ravemark (1995) where the intermediate storage tank location is the same for every product in the batch plant. Finally the results obtained in the execution of several examples are presented.

Mathematical modeling for simultaneous design of plants and supply chain in the batch process industry

Most supply chain design models have focused on the integration problem, where links among nodes must be settled in order to allow an efficient operation of the whole system. At this level, all the problem elements are modeled like black boxes, and the optimal solution determines the nodes allocation and their capacity, and links among nodes. In this work, a new approach is proposed where decisions about plant design are simultaneously made with operational and planning decisions on the supply chain. Thus, tradeoffs between the plant structure and the network design are assessed. The model considers unit duplications and the allocation of storage tanks for plant design. Using different sets of discrete sizes for batch units and tanks, a mixed integer linear programming model (MILP) is attained. The proposed formulation is compared with other non-integrated approaches in order to illustrate the advantages of the presented simultaneous approach.

A multiperiod model for production planning and design in a multiproduct batch environment

A general multiperiod model to optimize simultaneously production planning and design decisions applied to multiproduct batch plants is proposed. This model includes deterministic seasonal variations of costs, prices, demands and supplies. The overall problem is formulated as a mixed-integer linear programming model by applying appropriate linearizations of non-linear terms. The performance criterion is to maximize the net present value of the profit, which comprises sales, investment, inventories, waste disposal and resources costs, and a penalty term accounting for late deliveries. A noteworthy feature of this approach is the selection of unit dimensions from the available discrete sizes, following the usual procurement policy in this area. The model simultaneously calculates the plant structure (parallel units in every stage, and allocation of intermediate storage tanks), and unit sizes, as well as the production planning decisions in each period (stocks of both product and raw materials, production plans, policies of sales and procurement, etc.).

Simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production

Abstract The interest on renewable fuels has greatly increased in the last years. Particularly, ethanol production arises as a good solution to many current economic-environmental problems. Yeast production from the ethanol residuals constitutes a sustainable alternative. Usually, this kind of plants is designed using single product campaigns. However, since yeast degradation is fast and a continuous supply must be assured, the mixed product campaign policy is the most appropriate. Besides, a stable context can be assumed to justify this approach that takes advantage of the special structure of the plant. Therefore, in this paper, a mixed integer linear programming model is formulated for simultaneous design and scheduling of a semicontinuous/batch plant for ethanol and derivatives production. The optimal plant configuration, unit sizes, number of batches of each product in the campaign and its sequencing is obtained in order to fulfill the ethanol and yeast demands minimizing the investment cost.