Diamanti, EleftheriaIriarte, EnekoOblak, EvaDominguez-Meister, SantiagoIbañez, IñigoBraceras, IñigoBerger, Andreas2021-03Diamanti , E , Iriarte , E , Oblak , E , Dominguez-Meister , S , Ibañez , I , Braceras , I & Berger , A 2021 , ' Use of smartphones as optical metrology tools for surface wear detection ' , The International Journal of Advanced Manufacturing Technology , vol. 114 , no. 1-2 , pp. 231-240 . https://doi.org/10.1007/s00170-021-06840-x1433-3015researchoutputwizard: 11556/1094Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.Proper wear level information and early wear detection are crucial goals in many engineering applications and industrial components in order to improve efficiency and reduce production, maintenance, or replacements costs. Furthermore, this should ideally be achieved with a user-friendly, low-cost, and easy to implement methodology for wear level monitoring and detection. In this work, we present the design of a new approach to accomplish early wear detection that is implemented by means of a stand-alone smartphone device and application providing real-time online metrology. The online monitoring is done by means of optical measurements and image processing based on the advanced smartphone vision system technology currently available in commercial devices. The developed mobile App works in continuous mode without interrupting the wear process. Specifically, it traces surface changes and monitors the progression of wear enabling just-in-time warning alarms for “significant wear” and “critical wear” detection. We demonstrate that critical wear of a surface prior to fatal rupture can be detected, which is the main objective in many industrial applications.101346462enginfo:eu-repo/semantics/restrictedAccessjournal article10.1007/s00170-021-06840-xAlgorithm designWear recognition algorithmImage processingSmartphone vision systemOnline wear data engineeringUser-friendly portable tribology testingAlgorithm designWear recognition algorithmImage processingSmartphone vision systemOnline wear data engineeringUser-friendly portable tribology testingControl and Systems EngineeringSoftwareMechanical EngineeringComputer Science ApplicationsIndustrial and Manufacturing EngineeringFunding InfoThis research was supported by the Basque Government with Elkartek 2017 under project no. KK-2017/00012, IFVMPCO Grant 2018 under project no. 2018. Work at CIC nanoGUNE was also supported by the Spanish Ministry of Science and Innovation under the Maria de Maeztu Units of Excellence Programme (MDM-2016-0618).This research was supported by the Basque Government with Elkartek 2017 under project no. KK-2017/00012, IFVMPCO Grant 2018 under project no. 2018. Work at CIC nanoGUNE was also supported by the Spanish Ministry of Science and Innovation under the Maria de Maeztu Units of Excellence Programme (MDM-2016-0618).http://www.scopus.com/inward/record.url?scp=85102420650&partnerID=8YFLogxK