Today small metal parts are mass-produced as for example rollers in cylinder bearings. At high velocity cutting the metal is cut with a great force in a scissor-like device. Both precision and repeatability is important to be able to guarantee good quality, but from an economical point of view it is also important to keep a great manufacturing capacity. The part of the process that is most time consuming is when the metal bar, that is about to be cut, is fed to the right position. Therefore it is interesting to examine if the time used for positioning can be reduced. This thesis examines if more advanced automatic control can be used to speed up the process while maintaining the precision. In order to test and evaluate different theories, two different mathematical models have been developed. The models where implemented in the simulation program SIMULINK in MATLAB and they where compared to and adapted to data measured on the physical machine. One model is developed from physical relationships and mostly used for simulations while the other one, a condition state model, has been used for regulator design. The first question to answer was if it is at all possible to control the process any faster. When a theoretical limit was found the next step was to design a regulator to show that the theory of automatic control does not imply too great limitations. The design that was chosen was condition state feedback where the states were appraised with an observer. A faster system will raise the demands on cycle times and precision. To make sure that the hardware isn’t the limiting factor, design requirements have been set up. A small list of what hardware is available has also been put together (and shows that it is possible to implement such a system). The conclusion is that it is, theoretically, possible to radically increase the manufacturing capacity. The assumptions for this to be accomplished is especially that the uncertainty of the model is minimizedand that hardware with enough capacity can be found.

<p>Today small metal parts are mass-produced as for example rollers in cylinder bearings. At high velocity cutting the metal is cut with a great force in a scissor-like device. Both precision and repeatability is important to be able to guarantee good quality, but from an economical point of view it is also important to keep a great manufacturing capacity. The part of the process that is most time consuming is when the metal bar, that is about to be cut, is fed to the right position. Therefore it is interesting to examine if the time used for positioning can be reduced. This thesis examines if more advanced automatic control can be used to speed up the process while maintaining the precision. In order to test and evaluate different theories, two different mathematical models have been developed. The models where implemented in the simulation program SIMULINK in MATLAB and they where compared to and adapted to data measured on the physical machine. One model is developed from physical relationships and mostly used for simulations while the other one, a condition state model, has been used for regulator design. The first question to answer was if it is at all possible to control the process any faster. When a theoretical limit was found the next step was to design a regulator to show that the theory of automatic control does not imply too great limitations. The design that was chosen was condition state feedback where the states were appraised with an observer. </p><p>A faster system will raise the demands on cycle times and precision. To make sure that the hardware isn’t the limiting factor, design requirements have been set up. A small list of what hardware is available has also been put together (and shows that it is possible to implement such a system). </p><p>The conclusion is that it is, theoretically, possible to radically increase the manufacturing capacity. The assumptions for this to be accomplished is especially that the uncertainty of the model is minimizedand that hardware with enough capacity can be found.</p>