The paper is concerned about the neural-mathematical model for the analysis and rationalization of fixtures, suitable for clamping of thin-wall products likely to undergo deformation due to clamping and cutting forces during machining. The force analysis model has a built-in local optimization routine that can determine the clamping and locating forces of more reasonable magnitudes. It is suitable for the analysis of modular fixtures intended for clamping of prismatic and rotational products. The presented model takes into considerations the friction forces occurring between the workpiece and the fixture components. Due to the use of artificial neural network (ANN) the duration of the optimization routine is very short. The described procedure ensures reduction of the time of fixture planning and prevention of defects and deformation during the machining process. A programme FIXAN has also been made for the evaluation of fixturing scheme, for calculation of the optimum positioning of clamping forces, required to enable the workpiece to be safely clamped during machining.
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The study gives examples of the cast functional accessories operating in furnaces for the heat treatment of metals and alloys. The described design solutions of castings and their respective assemblies are used for charge preparation and handling. They were put in systematic order depending on furnace design and the technological purpose of heat treatment. Basic grades of austenitic cast steel, used for castings of this type, were enumerated, and examples of general guidelines formulated for their use were stated. The functional accessories described in this study were designed and made by the Foundry Research Laboratory of West Pomeranian University of Technology.
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