<?xml version='1.0' encoding='UTF-8'?><?xml-stylesheet href='static/style.xsl' type='text/xsl'?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-21T12:56:08Z</responseDate><request verb="GetRecord" identifier="oai:ebiltegia.mondragon.edu:20.500.11984/1477" metadataPrefix="mods">https://ebiltegia.mondragon.edu/oai/request</request><GetRecord><record><header><identifier>oai:ebiltegia.mondragon.edu:20.500.11984/1477</identifier><datestamp>2025-06-12T14:11:58Z</datestamp><setSpec>com_20.500.11984_1234</setSpec><setSpec>col_20.500.11984_1239</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
   <mods:name>
      <mods:namePart>Duo, Aitor</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Basagoiti, Rosa</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>ARRAZOLA, PEDRO JOSE</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>Aperribay Zubia, Javier</mods:namePart>
   </mods:name>
   <mods:name>
      <mods:namePart>CUESTA ZABALAJAUREGUI, MIKEL</mods:namePart>
   </mods:name>
   <mods:extension>
      <mods:dateAvailable encoding="iso8601">2019-07-24T10:54:07Z</mods:dateAvailable>
   </mods:extension>
   <mods:extension>
      <mods:dateAccessioned encoding="iso8601">2019-07-24T10:54:07Z</mods:dateAccessioned>
   </mods:extension>
   <mods:originInfo>
      <mods:dateIssued encoding="iso8601">2019</mods:dateIssued>
   </mods:originInfo>
   <mods:identifier type="uri">https://hdl.handle.net/20.500.11984/1477</mods:identifier>
   <mods:abstract>This directory contains the raw data acquired by Mondragon Unibertsitatea during the execution of drilling tests. These data were used to obtain the results presented in the article "The capacity of statistical features extracted from multiple signals to predict tool wear in the drilling process" published in International Journal of Advanced Manufacturing Technology on January 2019. &#xd;
Drilling is one of the most critical processes in the machining sector. This process is carried out in the last phases of the machining of a part, therefore, an almost finished part could be destroyed if the proper conditions are not met. Tool wear is one of the biggest problems in machining processes having an increasingly negative impact on the machined part. In order to carry out a study on the effect that tool wear has on the different signals acquired during the process and identify the sensitivity of each of the signals with respect to the others, drilling tests were carried out at different levels of tool wear. This document details the acquired signals and their organization in this directory.</mods:abstract>
   <mods:language>
      <mods:languageTerm>eng</mods:languageTerm>
   </mods:language>
   <mods:accessCondition type="useAndReproduction">Attribution 4.0 International</mods:accessCondition>
   <mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by/4.0/</mods:accessCondition>
   <mods:accessCondition type="useAndReproduction">© Mondragon Goi Eskola Politeknikoa</mods:accessCondition>
   <mods:titleInfo>
      <mods:title>Drilling test data from new and worn bits</mods:title>
   </mods:titleInfo>
   <mods:genre>http://purl.org/coar/resource_type/c_ddb1</mods:genre>
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