https://www.mdu.se/

Despite successful AI system deployments in manufacturing, methodological support for developing and integrating AI systems into manufacturing processes remains underdeveloped. This paper aims to identify gaps in the methodological support for the early design phase of AI system development in manufacturing. The study reveals the thinking-level challenges that design participants face in the early design phase and identifies remedies for those challenges, which are only superficially addressed in current manufacturing literature. The paper contributes to uncovering the current knowledge gap in developing an actionable methodology for AI system development in manufacturing contexts.