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Lessons learned from the test-to-test variability of different types of wear data

Contrary to the established principles of the scientific method, a surprising number of experimentally-based papers submitted to tribology journals and conferences report only one test result for each material pair or set of applied conditions. However, like hardness, yield strength, fatigue life, a...

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Autor principal: Blau, P.J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier B.V. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125812/
https://www.ncbi.nlm.nih.gov/pubmed/32287451
http://dx.doi.org/10.1016/j.wear.2016.11.012
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author_facet Blau, P.J.
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description Contrary to the established principles of the scientific method, a surprising number of experimentally-based papers submitted to tribology journals and conferences report only one test result for each material pair or set of applied conditions. However, like hardness, yield strength, fatigue life, and other material properties, wear data exhibit varying degrees of repeatability and reproducibility (R/R). Repeatability concerns the replication of experiments within the same laboratory using the same equipment and materials. Reproducibility concerns testing on different equipment, usually at a different location, but using the same lot of specimens and procedures. An important question is: How many replicate measurements are needed to validate trends in wear behavior or to relatively rank materials, surface treatments, or lubricants? Without repeatability information, it is virtually impossible to establish whether reported material rankings or the effects of variables are real or fall within normal data scatter. The purpose of this paper is to characterize and analyze the R/R of wear data that result from a variety of sources, including material homogeneity, choice of units of measure, and choice of experimental variables. Case studies compare R/R for different forms of wear and their test methods, including ASTM standards. Lessons learned are presented for five forms of wear: (1) cavitation erosion, (2) three-body abrasion, (3) solid particle erosion, (4) dry sliding wear, and (5) fuel lubricity using the ball-on-cylinder (BOCLE) test. Wear transitions can also affect R/R. These examples provide insights for validating wear models, deciding how many repeated tests to make, and when ranking wear-resistance.
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spelling pubmed-71258122020-04-08 Lessons learned from the test-to-test variability of different types of wear data Blau, P.J. Wear Article Contrary to the established principles of the scientific method, a surprising number of experimentally-based papers submitted to tribology journals and conferences report only one test result for each material pair or set of applied conditions. However, like hardness, yield strength, fatigue life, and other material properties, wear data exhibit varying degrees of repeatability and reproducibility (R/R). Repeatability concerns the replication of experiments within the same laboratory using the same equipment and materials. Reproducibility concerns testing on different equipment, usually at a different location, but using the same lot of specimens and procedures. An important question is: How many replicate measurements are needed to validate trends in wear behavior or to relatively rank materials, surface treatments, or lubricants? Without repeatability information, it is virtually impossible to establish whether reported material rankings or the effects of variables are real or fall within normal data scatter. The purpose of this paper is to characterize and analyze the R/R of wear data that result from a variety of sources, including material homogeneity, choice of units of measure, and choice of experimental variables. Case studies compare R/R for different forms of wear and their test methods, including ASTM standards. Lessons learned are presented for five forms of wear: (1) cavitation erosion, (2) three-body abrasion, (3) solid particle erosion, (4) dry sliding wear, and (5) fuel lubricity using the ball-on-cylinder (BOCLE) test. Wear transitions can also affect R/R. These examples provide insights for validating wear models, deciding how many repeated tests to make, and when ranking wear-resistance. Published by Elsevier B.V. 2017-04-15 2016-11-22 /pmc/articles/PMC7125812/ /pubmed/32287451 http://dx.doi.org/10.1016/j.wear.2016.11.012 Text en © 2017 Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Blau, P.J.
Lessons learned from the test-to-test variability of different types of wear data
title Lessons learned from the test-to-test variability of different types of wear data
title_full Lessons learned from the test-to-test variability of different types of wear data
title_fullStr Lessons learned from the test-to-test variability of different types of wear data
title_full_unstemmed Lessons learned from the test-to-test variability of different types of wear data
title_short Lessons learned from the test-to-test variability of different types of wear data
title_sort lessons learned from the test-to-test variability of different types of wear data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125812/
https://www.ncbi.nlm.nih.gov/pubmed/32287451
http://dx.doi.org/10.1016/j.wear.2016.11.012
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