Gast ::
000989765 001__ 989765 000989765 005__ 20260303094726.0 000989765 0247_ $$2doi$$a10.48694/INGGRID.3827 000989765 037__ $$aRWTH-2024-06971 000989765 041__ $$aEnglish 000989765 1001_ $$aSchnur, Christopher$$b0$$eCorresponding author 000989765 245__ $$aPIA - A Concept for a Personal Information Assistant for Data Analysis and Machine Learning of Time-Continuous Data in Industrial Applicationsing.grid$$honline 000989765 260__ $$bUniversitäts- und Landesbibliothek Darmstadt$$c2023 000989765 3367_ $$010$$2EndNote$$aReport 000989765 3367_ $$0PUB:(DE-HGF)29$$2PUB:(DE-HGF)$$aReport$$breport$$mreport$$s1721913653_762073 000989765 3367_ $$2BibTeX$$aTECHREPORT 000989765 3367_ $$2DRIVER$$areport 000989765 3367_ $$2DataCite$$aOutput Types/Report 000989765 3367_ $$2ORCID$$aREPORT 000989765 500__ $$aA database with high-quality data must be given to fully use the potential of Artificial Intelligence (AI). Especially in small and medium-sized companies with little experience with AI, the underlying database quality is often insufficient. This results in an increased manual effort to process the data before using AI. In this contribution, the authors developed a concept to enable inexperienced users to perform a first data analysis project with machine learning and record data with high quality. The concept comprises three modules: accessibility of (meta)data and knowledge, measurement and data planning, and data analysis. Furthermore, the concept was implemented as a front-end demonstrator on the example of an assembly station and published on the GitHub platform for potential users to test and review the concept. 000989765 536__ $$0G:(GEPRIS)442146713-ALEX$$aNFDI4ING Alex - Bespoke experiments with high variability of setups (442146713-ALEX)$$c442146713-ALEX$$x0 000989765 536__ $$0G:(GEPRIS)442146713$$aDFG project G:(GEPRIS)442146713 - NFDI4ING – Nationale Forschungsdateninfrastruktur für die Ingenieurwissenschaften (442146713)$$c442146713$$x1 000989765 588__ $$aDataset connected to DataCite 000989765 591__ $$aGermany 000989765 650_7 $$2Other$$adata analysis 000989765 650_7 $$2Other$$amachine learning 000989765 650_7 $$2Other$$ameasurement and data planning 000989765 7001_ $$aDorst, Tanja$$b1 000989765 7001_ $$aDeshmukh, Kapil Sajjan$$b2 000989765 7001_ $$aZimmer, Sarah$$b3 000989765 7001_ $$aLitzenburger, Philipp$$b4 000989765 7001_ $$aSchneider, Tizian$$b5 000989765 7001_ $$aMargies, Lennard$$b6 000989765 7001_ $$aMüller, Rainer$$b7 000989765 7001_ $$aSchütze, Andreas$$b8 000989765 9141_ $$y2023 000989765 961__ $$c2024-07-25T15:21:05.706424$$x2024-07-25T15:15:50.140169$$z2024-07-25 000989765 9801_ $$aEXTERN4COORD 000989765 980__ $$aI:(DE-HGF)0 000989765 980__ $$aUNRESTRICTED 000989765 980__ $$areport