ISO/TS 16355-6:2019

TECHNICAL ISO/TS
SPECIFICATION 16355-6
First edition
2019-12
Applications of statistical and related
methods to new technology and
product development process —
Part 6:
Guidance for QFD-related approaches
to optimization
Application des méthodes statistiques et des méthodes liées aux
nouvelles technologies et de développement de produit —
Partie 6: Lignes directrices pour QFD et approches reliées pour
l'optimisation
Reference number
©
ISO 2019
© ISO 2019
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ii © ISO 2019 – All rights reserved

Contents Page
Foreword .v
Introduction .vi
1 Scope . 1
2 Normative references . 1
3 Terms and definitions . 1
4 Basic concepts of QFD . 1
5 Integration of QFD and robust parameter design . 2
5.1 Quality engineering . 2
5.1.1 General. 2
5.1.2 Loss function . 2
5.1.3 Types of factors which affect variability . 3
5.2 When to use quality engineering . 4
5.3 Robust parameter design, QFD, and TRIZ . 4
6 Types of QFD and robust design projects . 5
7 QFD and robust parameter design team membership . 6
7.1 QFD uses cross-functional teams . 6
7.2 Core team membership . 6
7.3 Subject matter experts . 6
7.4 QFD team leadership . 6
8 Robust parameter design . 6
8.1 General . 6
8.2 Signal-to-noise ratio . 6
8.2.1 General. 6
8.2.2 Signal . 6
8.2.3 Noise . 7
8.2.4 Three types of SN ratios . 7
8.3 Assessing robustness . 8
8.4 Two-step optimization . 8
8.4.1 General. 8
8.4.2 Design of experiments (DOE) . 8
8.5 Steps to robust parameter designed experiments . 8
8.5.1 General. 8
8.5.2 Step 1. Clarify the system’s ideal function . 9
8.5.3 Step 2. Select signal factor and its range . 9
8.5.4 Step 3. Select measurement method of output response . 9
8.5.5 Step 4. Develop a noise strategy, and select noise factors and levels . 9
8.5.6 Step 5. Select control factors and their levels from design parameters .10
8.5.7 Step 6. Assign experimental factors to inner or outer array .10
8.5.8 Step 7. Conduct experiment and collect data .10
8.5.9 Step 8. Calculate the SN ratio (η) and sensitivity (S) .10
8.5.10 Step 9. Generate factorial effect diagrams on SN ratio and sensitivity .10
8.5.11 Step 10. Select the optimum condition .11
8.5.12 Step 11. Estimate the improvement in robustness by the gain .11
8.5.13 Step 12. Conduct a confirmation experiment and check the gain and
reproducibility .11
8.5.14 Conclusions.11
8.6 Case studies in robust parameter design .11
Annex A (informative) Integration of robust parameter design (RPD) with quality function
deployment (QFD) and theory of inventive problem solving (TRIZ) .12
Annex B (informative) Other optimization methods .13
Bibliography .14
iv © ISO 2019 – All rights reserved

Foreword
ISO (the International Organization for Standardization) is a worldwide federation of national standards
bodies (ISO member bodies). The work of preparing International Standards is normally carried out
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ISO collaborates closely with the International Electrotechnical Commission (IEC) on all matters of
electrotechnical standardization.
The procedures used to develop this document and those intended for its further maintenance are
described in the ISO/IEC Directives, Part 1. In particular the different approval criteria needed for the
different types of ISO documents should be noted. This document was drafted in accordance with the
editorial rules of the ISO/IEC Directives, Part 2 (see www .iso .org/ directives).
Attention is drawn to the possibility that some of the elements of this document may be the subject of
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iso/ foreword .html.
This document 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.
A list of all parts in the ISO 16355 series can be found on the ISO website.
Any feedback or questions on this document should be directed to the user’s national standards body. A
complete listing of these bodies can be found at www .iso .org/ members .html.
Introduction
Quality function deployment (QFD) is a method to assure customer or stakeholder satisfaction and
value with new and existing products by designing in, from different levels and different perspectives,
the requirements that are most important to the customer or stakeholder, and ensuring their quality
throughout the downstream activities of design, development, supply, building, commercializing,
support and retiring from the market. These requirements are well understood through the use
of quantitative and non-quantitative tools and methods to improve confidence of the design and
development phases that they are working on the right things. In addition to satisfaction with the
product, robust parameter design improves the process by which new products are developed and
produced.
Reported results of using QFD include improved customer satisfaction with products at time of launch,
improved cross-functional communication, systematic and traceable design decisions, efficient use of
resources, reduced rework, reduced time-to-market, lower life cycle cost, improved reputation of the
organization among its customers or stakeholders.
This document demonstrates the dynamic nature of a customer-driven approach. Since its inception
in 1966, QFD has broadened and deepened its methods and tools to respond to the changing business
conditions of QFD users, their management, their customers, and their products. Those who have used
older QFD models will find these improvements make QFD easier and faster to use. The methods and
tools shown and described represent decades of improvements to QFD; the list is neither exhaustive nor
exclusive. Users should consider the applicable methods and tools as suggestions.
Robustness assessment is 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 includes
all costs incurred during not only the production stage, but also the disposal stages. When a product
is not robust, the product causes many environme
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