Conformity and statistical tolerancing
Statistical tolerancing was first proposed by Shewhart (Economic Control of Quality of Manufactured Product, (1931) reprinted 1980 by ASQC), in spite of this long history, its use remains moderate. One of the probable reasons for this low utilization is undoubtedly the difficulty for designers to an...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2018-01-01
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| Series: | International Journal of Metrology and Quality Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1051/ijmqe/2017023 |
| _version_ | 1818903989570240512 |
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| author | Leblond Laurent Pillet Maurice |
| author_facet | Leblond Laurent Pillet Maurice |
| author_sort | Leblond Laurent |
| collection | DOAJ |
| description | Statistical tolerancing was first proposed by Shewhart (Economic Control of Quality of Manufactured Product, (1931) reprinted 1980 by ASQC), in spite of this long history, its use remains moderate. One of the probable reasons for this low utilization is undoubtedly the difficulty for designers to anticipate the risks of this approach. The arithmetic tolerance (worst case) allows a simple interpretation: conformity is defined by the presence of the characteristic in an interval. Statistical tolerancing is more complex in its definition. An interval is not sufficient to define the conformance. To justify the statistical tolerancing formula used by designers, a tolerance interval should be interpreted as the interval where most of the parts produced should probably be located. This tolerance is justified by considering a conformity criterion of the parts guaranteeing low offsets on the latter characteristics. Unlike traditional arithmetic tolerancing, statistical tolerancing requires a sustained exchange of information between design and manufacture to be used safely. This paper proposes a formal definition of the conformity, which we apply successively to the quadratic and arithmetic tolerancing. We introduce a concept of concavity, which helps us to demonstrate the link between tolerancing approach and conformity. We use this concept to demonstrate the various acceptable propositions of statistical tolerancing (in the space decentring, dispersion). |
| first_indexed | 2024-12-19T21:00:18Z |
| format | Article |
| id | doaj.art-1264110ff1e34f6fb3bac1557bfff3ef |
| institution | Directory Open Access Journal |
| issn | 2107-6847 |
| language | English |
| last_indexed | 2024-12-19T21:00:18Z |
| publishDate | 2018-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | International Journal of Metrology and Quality Engineering |
| spelling | doaj.art-1264110ff1e34f6fb3bac1557bfff3ef2022-12-21T20:05:49ZengEDP SciencesInternational Journal of Metrology and Quality Engineering2107-68472018-01-019110.1051/ijmqe/2017023ijmqe170032Conformity and statistical tolerancingLeblond LaurentPillet MauriceStatistical tolerancing was first proposed by Shewhart (Economic Control of Quality of Manufactured Product, (1931) reprinted 1980 by ASQC), in spite of this long history, its use remains moderate. One of the probable reasons for this low utilization is undoubtedly the difficulty for designers to anticipate the risks of this approach. The arithmetic tolerance (worst case) allows a simple interpretation: conformity is defined by the presence of the characteristic in an interval. Statistical tolerancing is more complex in its definition. An interval is not sufficient to define the conformance. To justify the statistical tolerancing formula used by designers, a tolerance interval should be interpreted as the interval where most of the parts produced should probably be located. This tolerance is justified by considering a conformity criterion of the parts guaranteeing low offsets on the latter characteristics. Unlike traditional arithmetic tolerancing, statistical tolerancing requires a sustained exchange of information between design and manufacture to be used safely. This paper proposes a formal definition of the conformity, which we apply successively to the quadratic and arithmetic tolerancing. We introduce a concept of concavity, which helps us to demonstrate the link between tolerancing approach and conformity. We use this concept to demonstrate the various acceptable propositions of statistical tolerancing (in the space decentring, dispersion).https://doi.org/10.1051/ijmqe/2017023conformity principlestatistical tolerancingrobust engineering |
| spellingShingle | Leblond Laurent Pillet Maurice Conformity and statistical tolerancing International Journal of Metrology and Quality Engineering conformity principle statistical tolerancing robust engineering |
| title | Conformity and statistical tolerancing |
| title_full | Conformity and statistical tolerancing |
| title_fullStr | Conformity and statistical tolerancing |
| title_full_unstemmed | Conformity and statistical tolerancing |
| title_short | Conformity and statistical tolerancing |
| title_sort | conformity and statistical tolerancing |
| topic | conformity principle statistical tolerancing robust engineering |
| url | https://doi.org/10.1051/ijmqe/2017023 |
| work_keys_str_mv | AT leblondlaurent conformityandstatisticaltolerancing AT pilletmaurice conformityandstatisticaltolerancing |