REAP UP - Resource Efficiency & Assessment Process for Used Parts

Important results from the project

The project objectives are met and we highlight early identification of component health as crucial for value creation, enabling automation and AI-based decision support. Hur AI can be used and the opportunities and challenges it brings have been identified in the project, as well as the need for stakeholder collaboration and the incremental and disruptive innovations required for sustainable take-back processes. The ability to develop innovation ecosystems for "reuse" is Circular Intelligence.

Expected long term effects

Early quality review improves efficiency in reverse logistics, reduces costs and provides increased stability in the supply chain by enabling better planning and lower inventory requirements. It supports higher production predictability and capacity utilization while improving environmental performance through increased reuse. Strategically, it strengthens data-driven capabilities, customer satisfaction and circular business models, which form the basis for long-term competitive advantages.

Approach and implementation

The work packages were implemented according to a revised plan. We have had pulse meetings every two weeks throughout the period when each partner reported on activities and we have reasoned about the consequences of them and how it affects demonstrators. We have also carried out planned workshops and have had special planning and follow-up meetings. Our agile and goal-oriented approach has worked well but also taken more resources from the companies than was initially planned.