ISO 16337:2021 Application of statistical and related methods to new technology and product development process — Robust tolerance design (RTD)

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Application of statistical and related methods to new technology and product development process — Robust tolerance design (RTD)是ISO于2021-04发布的ISO标准，适用于全球。

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INTERNATIONAL STANDARD ISO 16337:2021(E)

Application of statistical and related methods to new technology and product development process — Robust tolerance design (RTD)

1 Scope

This document specifies guidelines for applying the robust tolerance design (RTD) provided by the Taguchi methods to a product in order to finalize the design of the product.

NOTE 1 RTD is applied to the target product to set the optimum tolerances of the design parameters around the nominal values. RTD identifies the effects of errors in the controllable design parameters on product output and estimates the total variance of the product output if the tolerances are changed. Hence, RTD achieves the target variance of the output from the viewpoints of robustness, performance, and cost.

NOTE 2 The tolerance expresses a maximum allowable error in the value of a design parameter in the manufacturing process. In a perfect world, the parts or elements of every product have the designed nominal values of the design parameters. However, actual manufacturing does not reproduce the exact designed nominal values of the design parameters for all products. The actual products have errors in the values of their parts or elements. These errors are supposed to be within the designed tolerances.

2 Normative references

The following documents are referred to in the text in such a way that some or all of their content constitutes requirements of this document. For dated references, only the edition cited applies. For undated references, the latest edition of the referenced document (including any amendments) applies.

ISO 16336, Applications of statistical and related methods to new technology and product development process — Robust parameter design (RPD)

3 Terms a nd definiti ons

For the purposes of this document, the terms and definitions given in ISO 16336 apply.

ISO and IEC maintain terminological databases for use in standardization at the following addresses:

— ISO Online browsing platform: available at https://w ww. iso. org/o bp

— IEC Electropedia: available at http://w ww.e lectropedia .org/ 3.1

tolerance

difference between the upper specification limits and lower specification limits

3.2

robust tolerance design

RTD

method of setting optimum tolerances from the viewpoints of robustness, performance, and cost

ISO 16337:2021(E)

4 Robust tolerance design

4.1 General

A company’s product design section normally gives the specifications of a product, that is, the nominal values and tolerances of the design parameters, to the manufacturing section. The manufacturing section uses the designed specifications in manufacturing the product. When specifications specify the limits of a design parameter as m±Δ , the parameter value x in the manufacturing process should satisfy the following restriction:

mx−≤ΔΔ≤+m , (1)

where m and Δ denote a nominal value and its permissible difference, respectively. Only the symmetric (±Δ ) case is discussed in this document. In the symmetric case, the tolerance is 2Δ, and the permissible difference Δ is half the tolerance.

If the absolute error of a design parameter is larger than the specified permissible difference Δ, the variability in the product output cannot meet the designed performance and specifications.

RTD is used by the design section to set the optimum tolerance for each design parameter to achieve the designed performance, which is evaluated based on the total variance of the product output. The permissible difference of a design parameter is the maximum allowable error around the nominal value in the manufacturing process, and it is closely related to the cost of manufacturing.

The optimum nominal values of the design parameters can be identified by robust parameter design [1]

(RPD) through robustness measure, signal-to-noise ratio . The selection of a robust product by setting the nominal values as the optimum values using RPD prior to RTD is highly recommended. RPD can optimize the target product by choosing the optimum combination of design parameter nominal values [2]

from the viewpoint of the variability of the product output without increasing the cost .

If RPD cannot achieve a target variability, RTD is used to identify possible tolerances for achieving the target variability even at a higher cost. Smaller tolerances result in smaller variability, but this requires upgrading the parts or elements of the product, which leads to higher manufacturing cost. RTD is used to investigate the balance between product quality and improvement cost.

Even if RPD achieves the target variance, RTD is used, in some cases, to identify larger tolerances than those considered in RPD. Larger tolerances mean larger variability, but if the increased variability satisfies the target variability, the larger tolerances are applicable as they lead to reduced cost of manufacturing the designed product.

The purpose of RTD is to achieve the target variability by setting optimum tolerances from the viewpoints of robustness, performance, and cost. For this purpose, RTD estimates the total variance of the output of the designed product if the tolerance of a design parameter is changed. The total variance can be estimated based on the results of analysis of variance (ANOVA).

Assume that a value x of design parameter F has a linear effect on output y of the product, as shown in Figure 1 a). If the present permissible difference of x in F is Δ = Δ, the error distribution of F affects P

output y with a magnitude of βΔ. If the permissible difference Δ of F is reduced to new permissible difference Δ = λΔ [λ<1 in Figure 1 a)], the effect of changing Δ in F on the output is reduced to λβΔ, N and the variance in y due to changing Δ in F is reduced from the present variance V to new variance FP

2

V = λ V . As a result, the total output variance is reduced from V to V [Figure 1 b)].

FN FP TP TN

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