| Summary: | An important task of modern mathematical statistics with its methods based on the theory of probability is a scientific estimate of measurement results. There are certain costs under control, and under ineffective control when a customer has got defective products these costs are significantly higher because of parts recall.When machining the parts, under the influence of errors a range scatter of part dimensions is offset towards the tolerance limit. To improve a processing accuracy and avoid defective products involves reducing components of error in machining, i.e. to improve the accuracy of machine and tool, tool life, rigidity of the system, accuracy of the adjustment. In a given time it is also necessary to adapt machine.To improve an accuracy and a machining rate there, currently become extensively popular various the in-process gaging devices and controlled machining that uses adaptive control systems for the process monitoring. Improving the accuracy in this case is compensation of a majority of technological errors. The in-cycle measuring sensors (sensors of active control) allow processing accuracy improvement by one or two quality and provide a capability for simultaneous operation of several machines.Efficient use of in-cycle measuring sensors requires development of methods to control the accuracy through providing the appropriate adjustments. Methods based on the moving average, appear to be the most promising for accuracy control since they include data on the change in some last measured values of the parameter under control.
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