During recent years, there has been a trend towards the miniaturization of the products and of the tools necessary in the industrial processes, including those for micromanipulation. For micromanipulation, the best devices are microgrippers built such as the compliant mechanisms. In this paper, a modular structure for a micromanipulation cell is proposed. The cell has three main modules: a base platform for the working area, a micro-positioning system, and a micromanipulation system. Each module has different design variants which can be combined for specific applications, the FE (finite elements). The analysis and experimental results validate the prototype proposed for this study. In the end, an application of the SiMFlex manipulation cell for an optical microscope is proposed.

The revolutionary economic potential of micro and nanotechnology is already recognized. Micro and nano-scale technologies that use electrical, magnetic, optical, mechanical, and thermal phenomena separately or in combination are either already in the industrial phase or approaching it. The products of micro and nanotechnology are made of small quantities of material but have high functionality and added value. This paper presents such a product: a system with micro-tweezers for biomedical applications—a micromanipulator with optimized constructive characteristics, including optimal centering, consumption, and minimum size, for handling micro-particles and constructive micro components. The advantage of the proposed structure consists mainly in obtaining a large working area combined with a good working resolution due to the double actuation principle: electromagnetic and piezoelectric.

This paper aims at solving difficult optimization problems arising in many engineering areas. To this end, two recently developed optimization method will be introduced: the heuristic Kalman algorithms (HKA) and the quasi geometric programming (QGP) problems. The principle of HKA is to consider the optimization problem as a measurement process intended to give an estimate of the optimum. A specific procedure, based on the Kalman estimator, is developed to improve the quality of the estimate obtained through a measurement process. A significant advantage of HKA against other stochastic methods lies mainly in the small number of parameters which have to be set by the user. In this paper we also introduce an extension of standard geometric programming (GP) problems which we call quasi geometric programming (QGP) problems. The consideration of this particular kind of nonlinear and possibly non smooth optimization problem is motivated by the fact that many engineering problems can be formulated as a QGP. To solve this kind of problems (QGP), an algorithm is proposed which is based on the resolution of a succession of standard GP. An interesting feature of the proposed approach is that it does not need to develop specific program solver and works well with any existing solver able to solve conventional GP. In the last part of the paper, it is to shown that HKA and QGP can be efficiently used to solve difficult non-convex optimization problems. In particular, we have addressed the problem of robust structured control and on-ship spiral inductor design. Numerical experiments exemplify the resolution of this kind of problems.