«Grading the quality of manufacturing technologies of machine parts based on the assessment of the corrected variance»


Production of quality mechanical engineering products is ensured by quality technologies.
Therefore, the issue of technology assessment is relevant and requires scientific development. When
manufacturing machine parts, one of the main quality criteria is the accuracy of the linear size. Reliability and durability of machines depend on the accuracy of the size of the parts produced.
Processing technologies can be different (different machines, different modes, etc.). This in itself
means different quality of the parts produced and, in turn, different prime cost of production. High
quality tends to always be accompanied by increased costs, which in a competitive market is not
always suitable for manufacturers.
Depending on the needs of the market, it becomes necessary to use exactly the technology
that provides the desired quality. The previously created gradation of technology quality as an
assessment tool is based on the use of probabilistic and statistical model of size distribution. This
model has the parameters of the upper and lower limits of size, the modal value, which is expressed
by the formula for dividing the segment, and the shape parameter.
Using graphs, it is shown that this model has three different forms of distribution density
with the same theoretical range of size values and with the same number of measurements of part
sizes. According to the graph of the distribution density, you can determine the quality of
technology in accordance with the proposed gradation.
The calculation of numerical characteristics of the sample of size values, namely the
corrected variance, which is an unbiased estimate of the theoretical variance, is proposed. By
observing the change in its value, the quality of the technological process can be assessed according
to the proposed gradation.
The proposed calculation formulas make it possible to assess and predict the accuracy of the
technological process and manage quality in mechanical engineering. 

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