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Linking theory and practice is essential to promote these competencies. To achieve this, a cyber-physical system is presented that enables this through the innovative approach of \u201cdeep-linking keywords.\u201d A heuristic scoring function determines a fulfillment score for each keyword. Based on the assessment, scenario-based training is adapted, enabling necessary individualization. Compared to existing systems, the prototype generates a coherent dataset that bridges knowledge work and scenario-based training, allowing for comprehensive scenario adaptation. The cyber-physical system consists of a computer-based training system built on the Django framework, a Basic Instrument Training Device, and flight simulator software, integrated via an application programming interface. After each evidence-based training session, performance data are processed through structured analysis pipelines to extract and evaluate scenario-linked feature vectors. This enables iterative parameter optimization for adaptive scenario control. Building on the prototype and the proven effectiveness of the heuristic scoring function, a large dataset will be compiled, and the rule-based method will be replaced by machine learning to enhance safety, effectiveness, and efficiency in aviation through highly individualized training enabled by an AI-based cyber-physical system.<\/jats:p>","DOI":"10.1007\/s13272-025-00870-x","type":"journal-article","created":{"date-parts":[[2025,8,29]],"date-time":"2025-08-29T09:50:02Z","timestamp":1756461002000},"page":"855-868","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["CPS prototype development for AI-based scenario adaptation in flight simulator training"],"prefix":"10.1007","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7057-508X","authenticated-orcid":false,"given":"H.","family":"Lilla","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"O.","family":"Niggemann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"T.","family":"Netzel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,8,29]]},"reference":[{"key":"870_CR1","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1007\/978-3-662-58528-3_73","volume-title":"Handbuch Industrie 40: Band 2: Automatisierung","author":"Niggemann Oliver","year":"2024","unstructured":"Oliver, Niggemann, Biswas, Gautam Kinnebrew, John, S., Nemanja, Hranisavljevic, Andreas, Bunte: Konzeptualisierung als Kernfrage des Maschinellen lernens in der Produktion. 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