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These architectures allow previously incompatible environments to interoperate. And they support life-cycle modeling and collaborative engineering.
The ever-increasing use of mathematical models in all aspects of process development, design, and operation, as well documented in several recent studies such as Ref. 1, is being matched by a significant growth in the supply of ever-more-sophisticated modeling software from a variety of sources, including process-engineering software companies, automation system vendors, and academic institutions, as well as in-house developments within operating companies.
Some of this software aims at a narrow, well-- defined function, such as the computation of physical properties, the simulation of a particular unit operation, or the numerical solution of certain types of mathematical problems arising in process simulation or optimization. Other software tools, however, essentially are environments that support the construction of a process model either from first principles or libraries of existing models, or both. They then allow the user to perform a variety of different tasks, such as process simulation or optimization, using this single model of the process (2). The second category of process tools incorporates or relies on several software tools of the first category. The distinction between these two kinds of software, albeit in practice not always as clear as described above, is particularly important for the purposes of this article. We, henceforth, shall call them process modeling components (PMCs) and process modeling environments (PMEs), respectively.
The abundance of process engineering software is clearly a positive factor for the chemical process industries (CPI), and already has resulted in major benefits. Recent industrial experience has revealed some interesting technical and commercial factors worth noting:
The need of integrated process modeling. There is an increasing recognition of the need for adopting a more integrated view of the process one that takes into account all important interactions. This, in turn, implies that individual PMCs in isolation are of relatively limited applicability. For example, consider a specialized reactor that forms the heart of a certain plant. Although the availability of a software package implementing an accurate model for the reactor certainly would be very useful, it would be even more desirable to be able to couple this model with models of the separation part of the plant, thereby permitting an analysis of the...