A Master thesis on Strategic Framework for Human-AI collaboration in Digital Manufacturing: A Human-Centric Approach to Decision-Making, Operational Performance, and System Resilience
Translated title
A Master thesis on Strategic Framework for Human-AI collaboration in Digital Manufacturing at Varsun Aerospace Technologies Pvt Ltd
Author
Palyamkota, Ashok Srikanth
Term
4. semester
Publication year
2026
Submitted on
2026-06-01
Pages
68
Abstract
This master’s thesis examines how people and AI can work together in digital manufacturing to improve decisions, day-to-day operations, and system resilience. The study focuses on Varsun Aerospace Technologies, a high-precision aerospace manufacturer undergoing digital transformation. It is guided by augmented intelligence theory and the automation-augmentation paradox, which emphasize that AI should support and extend human decision-making rather than replace it. The research uses a qualitative single-case study with semi-structured interviews, internal documents, and on-site observations. This approach provides detailed, real-world insights into how AI tools interact with human expertise in daily operations and management processes. The findings show that combining data-driven insights from AI with human judgment improves the quality of decisions and increases operational flexibility and responsiveness. At the same time, human oversight remains essential to manage uncertainty, system limitations, and unexpected disruptions. Based on these insights, the thesis proposes a human-centric AI integration framework with four elements: task allocation (who does what), decision authority (who decides and when), trust calibration (how much to rely on AI in different situations), and continuous learning (ongoing improvement for people and systems). The framework offers a practical way to balance automation and human expertise in manufacturing and contributes a context-specific model for implementing sustainable human-AI collaboration in digital production.
Denne kandidatafhandling undersøger, hvordan mennesker og AI kan samarbejde i digital produktion for at forbedre beslutninger, den daglige drift og systemers modstandsdygtighed. Studiet fokuserer på Varsun Aerospace Technologies, en højpræcisionsproducent i rumfartsindustrien, der er i gang med en digital transformation. Arbejdet bygger på teorien om augmenteret intelligens og på automations-augmenteringsparadokset, som understreger, at AI skal supplere og styrke menneskelig beslutningstagning frem for at erstatte den. Forskningen anvender en kvalitativ enkeltcase med semistrukturerede interviews, interne dokumenter og observationer på stedet. Denne tilgang giver detaljeret indsigt i, hvordan AI-værktøjer spiller sammen med menneskelig ekspertise i den daglige drift og i ledelsesprocesser. Resultaterne viser, at data-drevne indsigter fra AI kombineret med menneskelig dømmekraft forbedrer kvaliteten af beslutninger og øger driftens fleksibilitet og reaktionsevne. Samtidig er menneskelig kontrol afgørende for at håndtere usikkerhed, systembegrænsninger og uventede hændelser. På den baggrund foreslår afhandlingen en menneskecentreret ramme for AI-integration med fire elementer: opgavefordeling (hvem gør hvad), beslutningskompetence (hvem beslutter og hvornår), tillidskalibrering (hvor meget man bør stole på AI i forskellige situationer) og løbende læring (kontinuerlige forbedringer for mennesker og systemer). Rammen giver en praktisk måde at balancere automation og menneskelig ekspertise i produktion og bidrager med en kontekstspecifik model for bæredygtigt menneske-AI-samarbejde i digital produktion.
[This apstract has been rewritten with the help of AI based on the project's original abstract]
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