In mass production, the customer defines the constraints of assembled products by
functional and quality requirements. The functional requirements are expressed by the
designer through the chosen dimensions, which are linked by linear equations in the case
of a simple stack-up or non-linear equations in a more complex case. The customer quality
requirements are defined by the maximum allowable number of out-of-tolerance assemblies.
The aim of this paper is to prove that quality requirements can be accurately predicted in
the design stage thanks to a better knowledge of the statistical characteristics of the
process. The authors propose an approach named Advanced Probability based Tolerance
Analysis (APTA), assessing the defect probability (called PD)
that the assembled product has of not conforming to the functional requirements. This
probability depends on the requirements (nominal value, tolerance, capability levels) set
by the designer for each part of the product and on the knowledge of production devices
that will produce batches with variable statistical characteristics (mean value, standard
deviation). The interest of the proposed methodology is shown for linear and non-linear
equations related to industrial products manufactured by the RADIALL SA Company.