Process integration sequential design approach

In short, the traditional design approach adopts a sequential design approach. In contrast, the process integration methodology for process design takes a different approach in that process design aspects in the inner part of the onion diagram are... 

The gasoline synthesis involves three sequential steps (Fig. 2). Thus, when a process is to be designed, two different approaches can be used. Each step in the synthesis can be treated either as a rather independent plant, or process integration can be attempted. 

Product-process design are linked and in specific cases, there is an advantage to look at integrated solution approaches rather than sequential approaches. 

In many cases, the conversion at the reactor is low and the unreacted species need to be recycled. Duran and Grossmann [19] proved that we can improve the conversion of the recycled systems by simultaneous optimization and heat integration if the conversion of the reaction is variable compared to sequential approaches. Recently, this concept was used in the design of biodiesel production processes where methanol or ethanol was used in excess in the transesterification reaction to move the equilibrium toward biodiesel, which needs to be recycled. The recovery of the alcohol determines the energy consumption of the process and thus the operating conditions at the reactor must be adjusted to reduce the energy needed in the recovery of the alcohol. The optimal operating conditions at the reactor differ from the ones reported where the reactor is evaluated alone [20,21]. 

Finally, a new concern has focused the attention of many researchers— water consumption. The main problem with water consumption is that, in general, the cost is low and thus the economic evaluation does not provide water consumption minimization apart from the sequential approach consisting of the development of water networks for the treatment and reuse of water after process design [24]. Currently, a simultaneous process design with heat and water integration is being developed based on the targeting methods [25]. 

In this chapter, the integrated design and control of bioprocesses was considered as a multi-objective optimization problem subject to non-linear differential-algebraic constraints. This formulation has a number of advantages over the traditional sequential approach, not only because it takes into account the process dynamics associated to a particular design, but also it provides a set of possible solutions from which the engineer can choose the most appropriate to his/her requirements. However, these problems are usually challenging to solve due to their non-convexity, which causes the failure of procedures based on local (e.g. SQP) NLP solvers. 

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