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<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.3390/eng6090227</dc:identifier><dc:language>eng</dc:language><dc:creator>Val, Sonia</dc:creator><dc:creator>García, Iván</dc:creator><dc:title>Overall Equipment Effectiveness for Elevators (OEEE) in Industry 4.0: Conceptual Framework and Indicators</dc:title><dc:identifier>ART-2025-146275</dc:identifier><dc:description>In the context of Industry 4.0 and the proliferation of smart buildings, elevators represent critical assets whose performance is often inadequately measured by traditional indicators that overlook energy consumption. This study addresses the need for a more holistic Key Performance Indicator (KPI) by developing the Overall Equipment Effectiveness for Elevators (OEEE), an index designed to integrate operational effectiveness with energy efficiency. The methodology involves adapting the classical OEE framework through a comprehensive literature review and an analysis of elevator energy standards. This leads to a novel structure that incorporates a dedicated energy efficiency dimension alongside the traditional pillars of availability, performance, and quality. The framework further refines the performance and energy efficiency dimensions, resulting in six distinct sub-indicators that specifically measure operational uptime, speed adherence, electromechanical conversion, fault-free cycles (as a proxy for operational quality), and energy use during both movement and standby modes. The primary result is the complete mathematical formulation of the OEEE, a single, integrated KPI derived from these six metrics and designed for implementation using data from modern IoT-enabled elevators. The study concludes that the OEEE provides a more accurate and comprehensive tool for asset management, enabling data-driven decisions to enhance reliability, optimise energy consumption, and reduce operational costs in smart vertical transportation systems.</dc:description><dc:date>2025</dc:date><dc:source>http://zaguan.unizar.es/record/164024</dc:source><dc:doi>10.3390/eng6090227</dc:doi><dc:identifier>http://zaguan.unizar.es/record/164024</dc:identifier><dc:identifier>oai:zaguan.unizar.es:164024</dc:identifier><dc:identifier.citation>Eng 6, 9 (2025), 227 [25 pp.]</dc:identifier.citation><dc:rights>by</dc:rights><dc:rights>https://creativecommons.org/licenses/by/4.0/deed.es</dc:rights><dc:rights>info:eu-repo/semantics/openAccess</dc:rights></dc:dc>

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