Abstract - "Process Tolerancing: A Solution to the Dilemma of Worst-Case Versus Statistical Tolerancing"

PROCESS TOLERANCING:
A SOLUTION TO THE DILEMMA OF
WORST-CASE VERSUS STATISTICAL TOLERANCING

When solving tolerancing problems, one must choose between worst-case tolerancing and statistical tolerancing. Both of these methods have their pros and cons. If worst-case tolerancing is used, all tolerances must be specified as worst-case tolerances. If statistical tolerancing is used, all tolerances must be specified as statistical tolerances. In reality, the behavior of certain inputs is best described using worst-case tolerances while the behavior of other inputs is best described by statistical tolerances. Still other inputs are not adequately represented by either type of tolerance. This article reviews the two current methods of tolerancing along with their pros and cons. It then introduces a new method of tolerancing, called process tolerancing, which solves many of the problems associated with the current approaches. Process tolerancing represents a unified approach to tolerancing that encompasses both of the previous approaches. Using process tolerancing, worst-case tolerances and statistical tolerances can be combined into the same analysis. The flexibility provided by process tolerancing results in solutions to such common problems as multiple components from the same lot and off-center processes.

KEY WORDS: Statistical Tolerance, Worst-Case Tolerance, Process Tolerance, Variation Transmission Analysis, Propagation of Error, and Six Sigma Quality.

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Presented at Fall Technical Conference, 1995