In this chapter, the importance of conceptual process design during the develop­

ment of innovative process configurations is analyzed. The utilization of some useful tools for process design is highlighted, such as mathematical modeling and simulation. The key role played by process synthesis methodologies is empha­sized. The two major strategies for accomplishing process synthesis are discussed. Main trends in knowledge-based process synthesis are briefly presented as well as the main approach to carrying out optimization-based process synthesis.

2.1 CONCEPTUAL PROCESS DESIGN

Process systems engineering deals with the development of procedures, techniques, and tools to undertake the generic problems of design, operation, and control of productive processes related to the different sector of process and chemical indus­try (Perkins, 2002). As part of process systems engineering, process design plays a fundamental role during the development of efficient technologies, especially in technoeconomic and environmental terms, in order to produce a wide range of industrial products. In this way, its main objective consists of the selection and def­inition of a process configuration that makes possible the conversion of feedstocks into the end product. This should be done in such a way that the products meet given specifications and that the configuration performance is superior to existing ones, or nonexisting ones in the case of a new product introduced into the market. In general, process design can be accomplished from the perspective of sequential engineering, concurrent engineering, reverse engineering, or reengineering.

From the viewpoint of the life cycle of an industrial process, the sequential engineering in its classical version involves all the steps presented in Table 2.1 in a sequential manner. Reverse engineering is based on obtaining technical infor­mation of a product in order to determine what it is made of, what makes it work, and how it was constructed. This approach is particularly useful in the case of pharmaceuticals production, especially during the production of generic drugs. For ethanol, this approach is not applicable because its chemical structure and ways of production are relatively well known. Reengineering looks for the radi­cal change of process design through its fundamental revision to achieve decisive improvements in terms of quality, costs, celerity, flexibility, customer satisfac­tion, etc., all of them simultaneously. Reengineering does not look for incremental improvements, but drastic changes that allow reaching the predefined targets. On the other hand, concurrent engineering proposes the creation of a design environ­ment where all the actors involved in the development of a product participate,

TABLE 2.1

Steps Involved in the Development of an Industrial Process during its life Cycle

not only the designers. In this way, processing features and market demands will be taken into account during early stages of design, when the changes are easier and less expensive to implement. Therefore, the problems, conflicts, and change needs can be detected in time to carry out the necessary modifications with sub­stantially less effort than by means of sequential engineering. In this framework, concurrent engineering applied to design implies the integration of all life cycle steps of a process in the early stages, attaining the achievements of several goals. Thus, the research and development activities and conceptual design have to con­sider not only the building of a plant, its operation, control, and maintenance, but also the achievement of technoeconomic, market, environmental, and even social objectives. Practically, and for the case of commodities, the three first stages of the process life cycle are accomplished in a concurrent (simultaneous) way. If the synthesis pathways for a given product are already known, as in the case of fuel
ethanol, process design procedures are focused on the second and third stages in Table 2.1.

In this book, these two steps are analyzed for fuel ethanol production empha­sizing the related integrated processes. In fact, concurrent engineering elements are considered when taking into account as evaluation criteria not only technical indexes (yield, productivity, energy consumption), but also financial and envi­ronmental indicators in the framework of process intensification. Financial and environmental criteria correspond to the macro and mega scale levels of analysis (plant and unit integration and interaction between market conditions and envi­ronmental impact, respectively), as reported by Li and Kraslawski (2004). Just these two levels of analysis have been developed with more intensity in the past 15 years as a result of the globalization of the economy and worsening environment. On the other hand, process and apparatus integration corresponds to the micro scale level of analysis. At this level, process intensification through integrated and hybrid processes with higher efficiency and less size has become the most important development trend. This forced the change of the old paradigm of a chemical process made up of a series of unit operations where the processes and apparatus are coupled (meso scale). Finally, the nano scale (molecular design and new materials) has become crucial for designing processes to obtain very high value-added products.

The task of defining an appropriate process configuration requires the genera­tion and evaluation of many technological schemes (process flowsheets) in order to find those exhibiting better performance indicators. This task is called process synthesis. In a process synthesis problem, system inputs (type, composition, con­ditions, and flowrates of raw materials) and outputs (product flowrate and speci­fications, effluent streams constraints) are given and the task consists of defining the configuration of the process flowsheet or, in other words, the topology of the technological scheme, which allows the synthesis of the product from the feed­stocks entering the process. For this, at least one comparison criterion should be established with the aim of evaluating different alternative process flowsheets proposed in order to choose that with the better performance.

The configuration comprises the type and amount of unit processes and opera­tions required by the overall process as well as their interconnection (intermedi­ate, recycle, and purge streams) and the parameters of that configuration (mostly those ones related to operating conditions: flowrates, temperatures, pressure, compositions). Process synthesis procedures can be applied not only to the con­ceptual design of new processes, but also to the retrofitting of existing ones. Some approaches for process synthesis involve and apply fundamental concepts of ther­modynamics as the starting point for generating new alternative process configu­rations. Thus, energy consumption (calculated by enthalpy balances) of different flowsheets can be helpful for selection of the best alternatives. In a similar way, the concept of useful energy or exergy (widely employed in mechanical engineer­ing) can also be employed as a criterion for selection of alternatives. Recently, more global concepts from the ecology field, such as emergy, have been used for choosing the best configuration of a process (see Section 2.2.5).

During the next step of the life cycle of an industrial process, process analy­sis, the structure of the selected technological scheme is established in order to improve the global process through its more comprehensive insight. The type of problems undertaken by process analysis is summarized as follows: given the process inputs and once determined the technological configuration of the pro­cess that includes each one of the unit operations and processes involved, as well as their parameters, find the system outputs. The analysis is aimed at predicting how the given process behaves. It involves the process decomposition into its con­stituent elements for the individual study of each unit performance. The detailed features of the process (flowrates, pressures, temperatures, compositions) are pre­dicted by using mathematical models, empiric correlations, and computer-aided process simulation. Moreover, experimental methods are employed to study the system behavior as well as validate the theoretical approach used for its descrip­tion. It could be considered that the conceptual design stage corresponds to pro­cess synthesis activities and the development stage to process analysis activities, although there is no clear boundary between these two activities of process sys­tem engineering.

Though process synthesis is carried out prior to process analysis, both tasks interact with each other in order to achieve their goals. Thus, for evaluating the performance of an alternative technological configuration during process synthe­sis, mathematical models are required in order to predict the behavior of process units. This involves a distinctive task of process analysis. Usually, aggregated models are employed in process synthesis. Such models simplify the synthe­sis problem in a considerable way through the representation of one aspect or objective that tends to dominate the problem. Furthermore, short-cut models are utilized as well. In this kind of model, the description of the units involved in each proposed design is done through relatively simple nonlinear models with the aim of reducing the computational costs or exploiting the algebraic structure of the equations. During process analysis, more rigorous and complex models are involved to predict the performance of the different units, which make up part of a technological scheme (Grossmann et al., 2000). On the other hand, process opti­mization plays a very important role during process design. Once the structure with the best performance (this can, in turn, imply the employment of optimiza­tion tools) is defined, and knowing the structure of the system components that allow the prediction of its behavior, the optimization of the technological scheme can be accomplished in order to find the optimal operating parameters making possible the maximization or minimization of an objective function that evaluates the performance of the overall system based on one or more criteria (technical, economic, environmental).