PEC12-25 CAPEC-PROCESS Industrial Consortium ... - DTU Orbit
PEC12-25 CAPEC-PROCESS Industrial Consortium ... - DTU Orbit
PEC12-25 CAPEC-PROCESS Industrial Consortium ... - DTU Orbit
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Figure 5.1: Multiscale nature of product-process design problems<br />
To manage the complexity, a systems approach would develop a framework (the<br />
architecture of the software) for handling the diverse set of methods and tools needed to<br />
solve a wide range of problems, for a potential computer-aided system. Such systems need<br />
to have a knowledge base of data (for example, of the active ingredients, solvents,<br />
polymers, etc.); a library of models (for example, models to predict properties – in case data<br />
is not available - of active ingredients, solvents, polymers, etc.; models to predict the<br />
controlled release from the microcapsule; models to predict the behaviour of the mixing<br />
process); a design method (for example, guiding the engineer/scientist through the sequence<br />
of steps needed to identify the best solution); and, other associated methods-tools (such as a<br />
tool to analyze data; a tool to create the missing model; a tool to screen feasible<br />
alternatives). The principal idea here is to decompose a complex problem into a set of subproblems<br />
that are easier to solve and identify those that can be solved through model-based<br />
solution approaches. Solving these sub-problems according to a pre-determined sequence<br />
helps to reduce the search space through each subsequent sub-problem solution, until a subproblem<br />
cannot be solved with models anymore. At this point, the experiment-based trial<br />
and error approach takes over to determine the final solution. The advantage of this<br />
combined hybrid (systems approach) is that during the early stages, where enough data and<br />
models are available (or could be easily generated), the search space is rapidly reduced. In<br />
the later stages, where quantitative values become important and data/models become more<br />
unreliable, the experimental resources are employed, sometimes only to evaluate a few<br />
feasible alternatives to identify the truly innovative and best solution. Several examples of<br />
such computer aided systems can be found at <strong>CAPEC</strong> and current research is expanding on<br />
this approach through the development of a collection of methods and tools.<br />
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