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BS ISO 16336:2014

BS ISO 16336:2014

$215.11

Applications of statistical and related methods to new technology and product development process. Robust parameter design (RPD)

Published By Publication Date Number of Pages
BSI 2014 84
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This International Standard gives guidelines for applying the optimization method of robust parameter design, also called as parameter design, an effective methodology for optimization based on Taguchi Methods, to achieve robust products.

This International Standard 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 International Standard means minimized variability of product’s function under various noise conditions, that is, insensitivity of the product’s function to the changes in the levels of noises. For robust products, their responses are sensitive to signal and insensitive to noises.

The approach of this International Standard can be applied to any products that are designed and manufactured, including machines, chemical products, electronics, foods, consumer goods, software, new materials, and services. Manufacturing technologies are also regarded as products that are used by manufacturing processes.

PDF Catalog

PDF Pages PDF Title
6 Foreword
7 Introduction
9 Section sec_1
Section sec_2
Section sec_3
Section sec_3.1
Section sec_3.1.1
Section sec_3.1.2
1 Scope
2 Normative references
3 Terms and definitions and symbols
3.1 Term and definitions
10 Section sec_3.1.3
Section sec_3.1.4
Section sec_3.1.5
Section sec_3.1.6
Section sec_3.1.7
11 Section sec_3.1.8
Section sec_3.1.9
Section sec_3.1.10
Section sec_3.2
3.2 Symbols
12 Section sec_4
Section sec_4.1
Section sec_4.2
4 Robust parameter design — Overview
4.1 Requirements
4.2 Assessing the robustness of a system
14 Figure fig_1
Figure fig_2
Section sec_4.3
4.3 Robustness assessment through SN ratio
15 Section sec_4.4
4.4 An efficient method for assessing technical ideas — Parameter design
16 Section sec_4.5
Figure fig_3
4.5 Two-step optimization (Strategy of parameter design)
17 Figure fig_4
Figure fig_5
18 Section sec_4.6
Section sec_5
Section sec_5.1
4.6 Determination of the optimum design
5 Assessment of robustness by SN ratio
5.1 Concepts of SN ratio
19 Section sec_5.2
Section sec_5.3
5.2 Types of SN ratio
5.3 Procedure of the quantification of robustness
21 Section sec_5.4
Section sec_5.4.1
Table tab_1
5.4 Formulation of SN ratio: Calculation using decomposition of total sum of squares
22 Section sec_5.4.2
23 Table tab_2
24 Section sec_5.4.3
Section sec_5.4.4
25 Table tab_3
Section sec_5.4.5
26 Section sec_5.4.6
Section sec_5.4.7
27 Table tab_4
Section sec_5.5
Section sec_5.5.1
5.5 Some topics of SN ratio
28 Section sec_5.5.2
Section sec_5.5.3
Section sec_6
Section sec_6.1
Section sec_6.2
6 Procedure of a parameter design experiment
6.1 General
6.2 (Step 1) Clarify the system’s ideal function
29 Section sec_6.3
Section sec_6.4
Section sec_6.5
6.3 (Step 2) Select a signal factor and its range
6.4 (Step 3) Select measurement method of output response
6.5 (Step 4) Develop noise strategy and select noise factors and their levels
30 Section sec_6.6
Section sec_6.7
Table tab_5
6.6 (Step 5) Select control factors and their levels from design parameters
6.7 (Step 6) Assign experimental factors to inner or outer array
31 Section sec_6.8
Table tab_6
Section sec_6.9
6.8 (Step 7) Conduct experiment and collect data
6.9 (Step 8) Calculate SN ratio, η, and sensitivity, S
33 Table tab_7
34 Table tab_8
Section sec_6.10
6.10 (Step 9) Generate factorial effect diagrams on SN ratio and sensitivity
35 Figure fig_6
36 Section sec_6.11
Section sec_6.12
6.11 (Step 10) Select the optimum condition
6.12 (Step 11) Estimate the improvement in robustness by the gain
37 Section sec_6.13
Table tab_9
6.13 (Step 12) Conduct a confirmation experiment and check the gain and “reproducibility”
38 Section sec_7
Figure fig_7
7 Case study — Parameter design of a lamp cooling system
39 Table tab_10
Table tab_11
Table tab_12
40 Table tab_13
41 Table tab_14
43 Table tab_15
44 Table tab_16
Figure fig_8
46 Table tab_17
Figure fig_9
47 Figure fig_10
48 Annex sec_A
Annex sec_A.1
Annex sec_A.1.1
Annex sec_A.1.2
Annex A
(informative)

Comparison of a system’s robustness using SN ratio

49 Table tab_A.1
Figure fig_A.1
51 Table tab_A.2
Annex sec_A.1.3
52 Table tab_A.3
53 Table tab_A.4
54 Annex sec_A.2
55 Annex sec_B
Annex sec_B.1
Annex sec_B.1.1
Annex B
(informative)

Case studies and SN ratio in various technical fields

56 Figure fig_B.1
Table tab_B.1
57 Figure fig_B.2
Table tab_B.2
58 Table tab_B.3
Table tab_B.4
59 Table tab_B.5
60 Table tab_B.6
Table tab_B.7
61 Figure fig_B.3
62 Table tab_B.8
63 Figure fig_B.4
Annex sec_B.1.2
64 Figure fig_B.5
65 Table tab_B.9
Table tab_B.10
66 Table tab_B.11
Table tab_B.12
67 Table tab_B.13
68 Table tab_B.14
69 Table tab_B.15
70 Figure fig_B.6
71 Table tab_B.16
72 Annex sec_B.2
Annex sec_B.2.1
Table tab_B.17
Table tab_B.18
73 Annex sec_B.2.2
74 Table tab_B.19
Annex sec_B.2.3
Table tab_B.20
75 Annex sec_B.3
Table tab_B.21
76 Table tab_B.22
Annex sec_B.4
Table tab_B.23
78 Table tab_B.24
80 Reference ref_1
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Bibliography
81 Reference ref_21
Reference ref_22
Reference ref_23
Reference ref_24
Reference ref_25

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BS ISO 16336:2014
$215.11