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BS ISO 22514-8:2014

BS ISO 22514-8:2014

$189.07

Statistical methods in process management. Capability and performance – Machine performance of a multi-state production process

Published By Publication Date Number of Pages
BSI 2014 48
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This part of ISO 22514 aims to define the evaluation method to quantify the short-term capability of a production process (capacity of the production tool, widely termed capability), i.e. the machine performance index, to ensure compliance to a toleranced measurable product characteristic, when said process does not feature any kind of sorting system.

If the production process integrates a sorting system, then this one (clearing away nonconforming parts) should be analysed independently.

This part of ISO 22514 does not aim to define evaluation methods of the capability of a production process that is gauged through long-term observation (capability process or performance process indices).

This part of ISO 22514 defines

  • the principles guiding the development of indicators for quantifying capability, and

  • the statistical methods to be employed.

The characteristics used to evaluate production process capability have statistical distributions, and it is presumed, a priori, that at least one of these distributions is multi-modal. A distribution is presumed to be multimodal if it results from the marked effect of at least one cause inducing a significant difference between the produced items.

This part of ISO 22514 applies, for example, to characteristics generated by processes such as the following:

  • multi-cavity casting: simultaneously producing several identical parts from a mould featuring several cavities.

    Since each cavity has its own geometry and its own position in the mould architecture, it can create a systemic difference on the output result;

  • multi-fixture machining: a part produced at the same time, but the produced parts are positioned in relation to the production tool by different fixture systems.

    Since each fixture has its own geometry, mount clamps, etc., it can create a systematic difference on the output result;

  • batch load treatments: heat treatment applied at the same time on a set of identical parts (the batch load), distributed within a pre-defined space of furnace. The position of an item of the batch relative to the furnace can influence the output result.

Each cavity, fixture, or position in the batch load corresponds to a different state. The multi-state process can be understood as the result of the combination of different states within the same process (e.g. cavity, fixture, position in the batch load).

NOTE It needs to be ensured that such systematic differences, if any, constitute only a very small proportion of permissible error so that their impact is harmless and do not affect the capabilities of the process.

PDF Catalog

PDF Pages PDF Title
6 Foreword
7 Introduction
9 Section sec_1
1 Scope
10 Section sec_2
Section sec_3
Section sec_3.1
Section sec_3.2
Section sec_3.3
Section sec_3.4
Section sec_3.5
2 Normative references
3 Terms and definitions
11 Section sec_3.6
Section sec_3.7
Section sec_3.8
Section sec_3.9
12 Figure fig_1
Section sec_3.10
Figure fig_2
Section sec_3.11
13 Section sec_3.12
Section sec_3.13
Section sec_3.14
Section sec_4
4 Symbols and abbreviations
14 Section sec_5
Section sec_5.1
Section sec_5.2
5 Preliminary technical analysis of the process
5.1 General
5.2 Identification of intrinsic factors
15 Section sec_5.3
Section sec_6
Section sec_6.1
5.3 Determination of process-specific states
6 Preliminary verifications before calculating the machine performance indices
6.1 Measurement system
16 Section sec_6.2
Section sec_7
Section sec_7.1
6.2 Definition of the sampling plan for estimating global intrinsic dispersion
7 Estimation of global intrinsic dispersion and calculation of machine performance indices
7.1 General
17 Figure fig_3
Section sec_7.2
7.2 Verification on the absence of outliers in the set of made measurement results
18 Section sec_7.3
Figure fig_4
7.3 Determination of the widths of local intrinsic dispersions
19 Section sec_7.4
7.4 Determination of the locations of local intrinsic dispersions
20 Section sec_7.5
Figure fig_5
7.5 Global intrinsic dispersion: type and estimation
21 Table tab_1
22 Section sec_7.6
Table tab_2
7.6 Calculation of capability indices Pm and Pmk
23 Section sec_7.7
7.7 Acceptance thresholds for the machine performance indices
24 Annex sec_A
Annex sec_A.1
Annex sec_A.1.1
Table tab_b
Figure fig_A.1
Annex sec_A.1.2
Annex A
(informative)

States qualifying a processing process

25 Annex sec_A.1.3
Annex sec_A.1.4
Annex sec_A.1.5
Annex sec_A.1.6
Table tab_A.1
26 Annex sec_A.1.7
Annex sec_A.1.7.1
Annex sec_A.1.7.2
Table tab_A.2
27 Figure fig_A.2
Annex sec_A.1.7.3
Annex sec_A.2
28 Annex sec_A.2.1
Table tab_c
Figure fig_A.3
Annex sec_A.2.2
Annex sec_A.2.3
29 Table tab_d
Figure fig_A.4
Annex sec_A.2.4
30 Annex sec_A.2.5
Annex sec_A.2.6
Annex sec_A.2.6.1
Table tab_A.3
Annex sec_A.2.7
Table tab_A.4
31 Annex sec_A.2.8
Annex sec_A.2.8.1
Table tab_A.5
32 Annex sec_A.2.8.2
Table tab_A.6
33 Table tab_A.7
34 Annex sec_A.2.9
Table tab_A.8
Annex sec_A.3
Annex sec_A.3.1
35 Table tab_e
Figure fig_A.5
Annex sec_A.3.2
36 Figure fig_A.6
Annex sec_A.3.3
37 Annex sec_A.3.4
Table tab_A.9
38 Annex sec_A.3.5
Table tab_A.10
Table tab_A.11
39 Annex sec_A.3.6
40 Annex sec_B
Annex sec_B.1
Table tab_B.1
Annex B
(normative)

Statistical tests

41 Annex sec_B.2
42 Table tab_B.2
Table tab_B.3
Table tab_B.4
43 Annex sec_B.3
Annex sec_B.3.1
45 Reference ref_1
Reference ref_2
Bibliography

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BS ISO 22514-8:2014
$189.07