INFLUENCE OF DEGREE OF THICKNESS REDUCTION RATIO ON DEVELOPMENT OF STRUCTURE IN THE STEEL 1 . 5710
Intensity of structural changes during forging is usually determined in dependence on the forging ratio. Forging ratio at elongation is most often calculated with use of simple relations, which are based on the change of cross-section of the forged pieces. The intensity of structure development is influenced not only by the simple change of cross-sections, but also by relative length of the stroke, magnitude of deformation in individual passes, manner of edging, temperature, friction and shape of anvils. The paper gives an analysis of influence of the relative length of the stroke on the forging ratio.
Grain size prediction during open die forging processes
One of the most important target parameters during open die forging is the microstructure, respectively the grain size. This paper details different semi-empiric models that ultimately help to predict the microstructure properties of a forged block. As a first step, trials in industrial scale were performed by Buderus Edelstahl GmbH and attended by SMS Meer GmbH. The collected process data was used by the Institute of Metal Forming (IBF) for the numerical analysis of the open die forging process and to validate the microstructure prediction module STRUCSIM. The numerical prediction of the grain size shows a good agreement with the results obtained from the metallography. In a second step models for the core fibre of a forged block were developed at the IBF. The models use data from the online process measurement and simplified plastomechanical interrelations for the calculation of equivalent strain and the temperature in the core of the forged part during the process. With their results the microstructure in the core fibre of the workpiece can be predicted online. The models are still in development and the most recent results will be presented in this paper.
An intelligent control system for ventilators.
This study reports on a ventilator system that consists of several intelligent modules for controlling ventilator operation. These modules are software programs in two controllers. One controller is a personal computer used for diagnoses, determining settings and checking the effects of settings. The other controller is a single-chip microprocessor in a ventilator that controls the ventilator's settings in accordance with the computer settings. After setting up the system, an artificial lung model simulating a patient's lung is used to test the system. The result of test run indicated that it always responds to a patient's lung condition in a stable manner. Thus, the proposed system with its intelligent modules may assist clinicians in caring for patients and managing ventilator operation.