Medical Test Strips made from plastics provide cheap and reliable analysis of body liquids. The underlying microsystem contains structured microchannels to adjust the filling time as an important parameter for chemical reactions. Columns or pins of some μm dimensons are being placed in the channel to define the fluidic resistance, which is influenced by the distance between these structure elements as well as by their geometry. As no analytic solution exists to describe the microfluidic interaction, the authors have been following approaches based on discrete partial differential equations and behavioural descriptions to obtain a simulation model. Model-based optimization has been performed to get useful sets of parameters to be handed to the industrial partner for manufacturing and therefore verification of the calculated results.
In cooperation with the industrial partner STEAG microParts GmbH and the Karlsruhe Research Center, the authors at the University of Bremen have created a behavioral model for the microsystem 'medical test strips'. As there is no complete theory for the underlying system yet, with capillary interaction between up to three different materials in the microfluidical/micromechanical world, the flow of liquids in such an application cannot be described analytically. Medical test strips made from plastics are an innovative approach toward cheap and therefore seminal one-way diagnostic systems and can be considered as step towards the long discussed 'lab on a chip' as well. The modeling is based on simulation results from the Finite Volume Method (FVM), yielding partial information for the investigated structures by solving partial differential equations. As this numerical approach cannot provide results for a complete channel, due to calculation efforts, a behavioral model for optimization purpose has been created on a higher abstraction level.
The application of optimization algorithms is especially interesting in areas, where the design process needs several iterations, every single one costing time and money. This is particularly the case with the design of Microsystems. The disadvantage in practice is usually the construction of the quality function, with which the quality of the optimal design is measured. This holds especially true whenever more than one optimization goal is pursued, because every goal needs to be quantified as part of an overall quality function. Especially the user of the optimization system is often at a loss when asked to specify and quantify the single goals' contributions to the overall quality function. This paper demonstrates the problem using a radiometric sensor as an example and examines several computer assisted quality function approaches to transform the multi criteria optimization problem into a single goal problem.
The way of how an efficient and reliable design strategy for Microsystems should be set up is discussed and put into practice. Within this design strategy automatic design optimization plays a decisive role. The model based design optimization system MODOS is presented which has especially been developed for the development of Microsystems. Finally, the proposed design strategy is utilized to optimize a micro mechanical pressure sensor with integrated readout circuitry.
A fundamental approach to a coherent design strategy for microsystems is presented in this paper. Establishing such a concept can provide undeniable advantages concerning manpower, technical resources and development time. Prevalent design steps are discussed in detail, referring to the suggested ideas. Several microsystem applications and software tools are taken into account to illustrate the main aspects of a consistent design flow. The approach of behavioral physical modeling in combination with model based design optimization applying efficient and robust numeric methods in both fields allows pre-production optimization. Thus, overall development and redevelopment effort can be reduced significantly.
Manufacturing test structures of microsensors and microactuators is very expensive in terms of time and materials. In a conventional design process, this limits the number of design variants to be considered. For this reason, computer-supported design techniques are becoming more and more important in microsystems technologies. In this paper, a system model of an IR gas sensor is presented. This model allows designs to be optimized, e.g. for use of the analysis chamber also to detect other gases with different absorption characteristics.
Due to the ongoing growth of microsystems' complexity, there is an urgent need for automatic optimization. In order to include it seamlessly in the customary design process, the algorithms have to be fast and robust. Calculations of the quality function call for at least one FEM-, netlist based or behavioral simulation. Thus the optimization process is a very time consuming task. This paper presents a methodology for enhancing the convergence characteristics of heuristic search methodologies.
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