ISO 16336:2014

DRAFT INTERNATIONAL STANDARD ISO/DIS 16336
ISO/TC 69/SC 8 Secretariat: JISC
Voting begins on Voting terminates on

2013-02-16 2013-05-16
INTERNATIONAL ORGANIZATION FOR STANDARDIZATION  •  МЕЖДУНАРОДНАЯ ОРГАНИЗАЦИЯ ПО СТАНДАРТИЗАЦИИ  •  ORGANISATION INTERNATIONALE DE NORMALISATION

Robust parameter design (RPD)
Plan paramètre robuste (RPD)
ICS 03.120.30
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©  International Organization for Standardization, 2013

ISO/DIS 16336
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ISO/DIS 16336
Contents Page
Foreword . iv
Introduction . v
1 Scope . 1
2 Normative references . 2
3 Terms and definitions . 2
4 Parameter Design for Robust Products — Overview . 4
4.1 Parameter Design for Robust Products — Requirements . 4
4.2 Assessing the robustness (SN ratio) of a system . 4
4.3 Utilization of robustness assessment . 5
4.4 An efficient method for assessing technical ideas — parameter design . 6
4.5 Two-step optimization (Strategy for parameter design) . 7
4.6 Determination of optimum design . 9
5 Assessment of robustness by SN ratio . 9
5.1 Concepts of SN ratio . 9
5.2 Types of SN ratio . 10
5.3 Procedure of the assessment and quantification of robustness . 10
5.4 Formulation of SN ratio: Computation using decomposition of total sum of squares . 11
5.4.1 Zero-point proportional equation ideal function (Dynamic characteristic) . 11
5.4.2 Linear equation ideal function (Dynamic characteristic) . 13
5.4.3 Reference point proportional ideal function (Dynamic characteristic) . 15
5.4.4 Nominal-the-best response (Static/non-dynamic characteristic) . 15
5.4.5 Smaller-the-better response (Static/non-dynamic characteristic) . 16
5.4.6 Larger-the-better response (Static/non-dynamic characteristic) . 16
5.4.7 SN ratio for digital characteristics . 17
5.5 Some topics of SN ratio . 17
5.5.1 Using SN ratios to compare systems . 17
5.5.2 Nonlinear signal and output response cases . 18
5.5.3 SN ratios of static/non-dynamic characteristics . 18
6 Procedure of parameter design . 18
7 Case study - Parameter design of a lamp cooling system . 28
Annex A (informative) Comparison of system robustness by SN ratio . 38
Annex B (informative) Examples and SN ratio in various technical fields . 45
Bibliography . 70

ISO/DIS 16336
Foreword
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ISO 16336 was prepared by Technical Committee ISO/TC 69, Applications of statistical methods,
Subcommittee SC 8, Application of statistical and related methodology for new technology and product
development.
iv © ISO 2002 – All rights reserved

ISO/DIS 16336
Introduction
Parameter design can be applied in product design stage to identify optimum nominal values of design
parameters based on assessment of robustness of its function. Robustness assessment should be
performed as a consideration of overall loss during the product’s life cycle. The overall loss is composed of
costs and losses at each stage of the product's life. It should include all the costs incurred during not only its
production stage, but also its disposal stages.
When a product is not robust, the product causes many environmental and social economic losses (including
losses to the manufacturer and users) due to its poor quality caused by functional variability throughout its
usable lifetime from shipping to final disposal. Product suppliers should have responsibilities and obligations to
supply robust products to the market to avert losses and damages resulting from defects in the products.
At product development and design stages, the product suppliers should therefore anticipate the defects and
failures of products in the market by applying preventative measures, and also should design robust products
by optimizing their design from the point of view of robustness.
At manufacturing stage, the product suppliers should manufacture their products that meet the product
specifications. One can optimize manufacturing processes to produce the products that meet the
specifications. However, robustness against customer’s environment and products’ aging can only be
addressed by product design.
Parameter design methodology provides effective methods for achieving robustness through its design of
specification determination, and it is a preventive counter measure against various losses in the market.
Parameter Design for Robust Products, this document, is directly targeted at losses incurred in the usage
stage. Where possible, losses at other stages are also investigated so that the results of parameter design
can be used to perform optimum product design for the whole of the product's life cycle.
DRAFT INTERNATIONAL STANDARD                                    ISO/D,6 16336

Parameter Design for Robust Products
1 Scope
This document gives a guidance of applying the optimization method of parameter design, an effective
methodology for optimization based on Taguchi Methods, to achieve robust products.
Aim of applying parameter design in product design is to prevent defects, failures and quality problems that
may occur during the usage of the product, and to minimize the loss in the market. Robust product, output of
parameter design, is a product which is designed such a way to minimize the user’s loss caused by defects,
failures and quality problems. One should note that defects, failures and quality problems are caused by
functional variability of non-robust product. In the parameter design, optimum nominal values of product’s
design parameters can be selected by treating product’s design parameters as control factors and by
assessing robustness under noise factors. The use of parameter design at the development and design
stages makes it possible to determine the optimum product design and specification so that the product is
more robust in the market. Choice of noise factors strongly depends on the market of the product.
This document prescribes signal-to-noise ratio (hereafter SN ratio) as a measure of robustness and the
procedures of parameter design to design robust products utilizing this measure. The word “robust” in this
document means minimized variability of product’s function under various noise conditions, that is,
insensitivity of the product’s function to the changes in the level of noises. For robust product, its response
should be sensitive to signal, and insensitive to noises.
The robustness of a product should essentially be quantified in terms of the economical losses caused by
variability of product’s function at the usage stage. Accordingly, when the robustness of a product is
estimated at the development and design stages, the designer should forecast and calculate the future
economical losses in the market where the product will be used. However, it is often difficult to perform
concrete evaluation of future losses at the development and design stages.
In practice, many product’s defects and failures occur mainly due to the product’s characteristics that deviate
from or vary around the designed target values due to the change in usage environment and deterioration, i.e.
noise conditions. The variability of product’s response should be used as a measure of robustness, because
market losses increase in proportion to the magnitude of variability of product’s characteristics due to noise
effects. The variability due to noises includes the deviation from the designed target value and the variation
around the designed target value in market. SN ratio, corresponding to the inverse of the variation measure,
should be used as a measure of goodness in robustness. In other words, the inverse of SN ratio is
proportional to the market losses.
For the experimental plan of parameter design, direct product of inner array and outer arrays is proposed.
Control factors should be assigned to inner array, and signal and noise factors should be assigned to outer
array. By using a direct product plan, all the first level interactions between control factors and noise factors
can be assessed and can be utilized to select the optimum level of control factors from the point of view of
robustness.
Assessing robustness through SN ratio is a key of parameter design. Outer array is for evaluating SN ratio,
robustness, for each combination of levels of control factors indicated by the inner array. Inner array is for
comparing SN ratios and selecting optimum combination of system’s design parameters. While experimental
layout for inner array may have many variations, orthogonal array L is strongly recommended and then only
the application of orthogonal array
...