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Eureka SMART Dynamic SALSA

Reference number
Coordinator Kungliga Tekniska Högskolan - Kungliga Tekniska Högskolan Inst för produktionsutveckling
Funding from Vinnova SEK 4 100 000
Project duration April 2023 - March 2026
Status Ongoing
Venture Eureka Cluster within sustainable development

Purpose and goal

Dynamic SALSA (Dynamic Scheduling of Assembly and Logistics Systems using AI) aims to develop AI solutions and practical software applications for dynamic scheduling in smart assembly and logistics including new digital services based on ICT for the automotive sector. The Swedish consortium of Dynamic SALSA focuses on applying digital technology in material handling to realize smart product-service-software systems that enable value creation through monitoring, control, optimization and autonomous material handling services.

Expected effects and result

The main results of this project include development of: theories, algorithms and demonstrators from university environments in Sweden and South Korea; ICT features, modules and offerings within SMEs; as well as applications for factory environments and demonstrators for larger manufacturing companies. Long-term effects of Dynamic SALSA are to contribute to realising the vision of a smart and sustainable factory including connected technology, data collection and analysis, and automated predictive and prescriptive actions.

Planned approach and implementation

The project consortium includes manufacturers from the automotive sector (Scania from Sweden and Woojin from South Korea), SMEs specialized in ICT (SIB Solutions from Sweden and Corners from South Korea) and universities from Sweden (KTH) and South Korea (SKKU and SNU) with expertise in the use of AI and digital twins in smart assembly and logistics. The project follows a classic development process, with phases of concept development, design and implementation. The development is in two areas, assembly and material handling, with responsibilities among partners.

External links

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 4 November 2024

Reference number 2022-02413