Qualitative Industrial Statistics

Authors

Gonzalo R. Longas

Abstract

Content

1.1.
The conventional statistical methods, today in use in our industrial plants, give the mathematical basis for solving gaussians distribution models only or similar. This means that only about 5 % of the our modern industrial problems can be solved by these methods.
1.2.
The Qualitative Industrial Statistic (Q.I.S),that we present, covers the statistical needs, of our industrial plants providing a mathematic-thecnological system with the following characteristics:
1. 1.2.1.
  It makes possible the correct evaluation of eigthy different models of industrial distribution curves (right and left skewed, rectangular, with upper,lower and both extremes limitation, stable, unstable, with tendency, ciclical, etc.)
2. 1.2.2.
  This method allows us to solve the statistical machine solution of process and lot capability, statistical determination of tolerances in all cases regarding any distribution form whether distribution form is gaussian or not, in accordance with preestablished level of P.P.M.
3. 1.2.3.
  It makes possible the determination of limits for continuous control charts, adjusted to preestablished level of P.P.M. in order that if they conform the limitis that guaranty the process will make products at that preestablished quality level. The mathematical formulaes in use today, used in a indiscriminated way for calculating these control limitis, are fixed at ± 3 σ and they admit 2700 P.P.M. when process consistenly acomplish at these limits.

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Citation: Longas, G., "Qualitative Industrial Statistics," SAE Technical Paper 911707, 1991, https://doi.org/10.4271/911707.

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