Estimating quantiles in acceptance criteria for structural components

The probabilistic foundations of methods to control the characteristic properties of structural materials, expressed as p-quantiles, are discussed. We argue that the acceptance criteria in the quality control should be based on quantile estimators complying with the definition of the quantile. We introduce the distribution-free concept of definition-based quantile estimator. For normal distribution, an application of different types of estimators, as well as some attribute methods and mixed methods presently used, are illustrated by operating characteristic curves. We recommend the prediction method by which the subjective limit values of the mixed methods are eliminated, information from the sample will be used more effectively than in the attribute methods, and the questions about the proper confidence level or a “known” variation coefficient need not be considered. However, the direct application of the prediction method results in stricter quality control than that presently used. Therefore, we recommend adopting p’ > p in such a way that if the predicted p’-quantile estimate is equal to or higher than the lower lilmit L, the required value of the p-quantile, the lot is accepted in the quality control. If the present quality level is appropriate, the value of p’ can be chosen in such a way that the present level is maintained. If not, necessary modifications are possible simply by adjusting p’.

Authors

Institutions

Publication Details

Journal
Rakenteiden Mekaniikka
Published
2024-10-17
DOI
https://doi.org/10.23998/rm.144320
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimating quantiles in acceptance criteria for structural components

Matti Pajari, Lasse Makkonen
Rakenteiden Mekaniikka
Manufacturing Process and Optimization
article

Estimating quantiles in acceptance criteria for structural components

Matti Pajari, Lasse Makkonen
article en

Abstract

The probabilistic foundations of methods to control the characteristic properties of structural materials, expressed as p-quantiles, are discussed. We argue that the acceptance criteria in the quality control should be based on quantile estimators complying with the definition of the quantile. We introduce the distribution-free concept of definition-based quantile estimator. For normal distribution, an application of different types of estimators, as well as some attribute methods and mixed methods presently used, are illustrated by operating characteristic curves. We recommend the prediction method by which the subjective limit values of the mixed methods are eliminated, information from the sample will be used more effectively than in the attribute methods, and the questions about the proper confidence level or a “known” variation coefficient need not be considered. However, the direct application of the prediction method results in stricter quality control than that presently used. Therefore, we recommend adopting p’ > p in such a way that if the predicted p’-quantile estimate is equal to or higher than the lower lilmit L, the required value of the p-quantile, the lot is accepted in the quality control. If the present quality level is appropriate, the value of p’ can be chosen in such a way that the present level is maintained. If not, necessary modifications are possible simply by adjusting p’.

Rakenteiden MekaniikkaVol. 57(3)
VTT Technical Research Centre of Finland (FI)
Openalex Percentile: Top 74%
Manufacturing Process and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Estimating quantiles in acceptance criteria for structural components — Matti Pajari, Lasse Makkonen · Rakenteiden Mekaniikka (2024) | TGRS Research Map | TGRS