{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,11]],"date-time":"2025-11-11T13:33:13Z","timestamp":1762867993366},"reference-count":24,"publisher":"EDP Sciences","license":[{"start":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T00:00:00Z","timestamp":1576540800000},"content-version":"vor","delay-in-days":350,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MATEC Web Conf."],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:p>The Industry 4.0 movement is driving innovation in manufacturing through the application of digital technologies, leading to solid performance improvements. In this context, this paper introduces a real-time analytical framework based on predictive, simulation and optimization technologies applied to decision support in manufacturing systems, enabled by an underlying reference implementation of an open Industrial Internet of Things (IIoT) platform. This architecture integrates critical equipment, manufacturing and corporate systems through a Unified IIoT Cloud Platform. A real case study on the aeronautic industry demonstrates the proposal feasibility of this architecture to enhance productivity, predict equipment failures and bring agility to react to unexpected events. In this case study, the monitoring tool displays the current status of the critical resources and the predictive tool calculates a probability of failure. When this probability reaches a certain threshold, the simulation tool is triggered to evaluate the impact of the disruption in the system\u2019s productivity. Results from the tools are displayed online through an alert system so that each stakeholder is informed timely and in a contextualized way.<\/jats:p>","DOI":"10.1051\/matecconf\/201930404004","type":"journal-article","created":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T09:26:30Z","timestamp":1576574790000},"page":"04004","source":"Crossref","is-referenced-by-count":2,"title":["An IIoT-based architecture for decision support in the aeronautic industry"],"prefix":"10.1051","volume":"304","author":[{"given":"Roberto","family":"Vita","sequence":"first","affiliation":[]},{"given":"Narciso","family":"Caldas","sequence":"additional","affiliation":[]},{"given":"Jo\u00e3o","family":"Basto","sequence":"additional","affiliation":[]},{"given":"Symone","family":"Alcal\u00e1","sequence":"additional","affiliation":[]},{"given":"Flavio","family":"Diniz","sequence":"additional","affiliation":[]}],"member":"250","published-online":{"date-parts":[[2019,12,17]]},"reference":[{"key":"R1","doi-asserted-by":"crossref","unstructured":"Frank A.G.,\nDalenogare L.S. and\nAyala N. 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