Data Automation and Retrieval Technology (DART)

Purpose and goal:

DART addresses the critical challenge of efficiently managing and utilizing the diverse data formats prevalent in industrial settings, which currently lead to significant inefficiencies in product development and production processes. DART´s use of Retrieval-Augmented Generation (RAG) for comprehensive data analysis and management directly supports the program´s ambition to develop advanced, interoperable digital solutions.

The aim of the project is to highlight possible opportunities and potential challenges for eventual commercialization strategies. Expected results and effects:

Demographic trends, combined with structural skills mismatches and insufficient education and training, are leading to shortages of appropriately skilled worker. Based on this, it is evident that systems are needed to support the generational shift, where experienced workers and engineers are soon retiring, and a new generation must take up the work and swiftly digest company specific knowledge.

A system like DART will support the transition of knowledge from one generation to another, by simplifying knowledge access, retrieval and presenting it in a manner suitable for the user. Approach and implementation:

The project is managed through biannual steering group meetings with representatives from LiU and partners, ensuring adherence to the project plan. An agile methodology is employed, facilitating flexibility and iterative development. This collaborative structure is designed to enhance knowledge transfer and co-creation, aiming to produce innovative solutions in technology development.