Concept for a data-based approach to support decision-making in tactical tasks for planning disassembly systems

Emissions-driven climate change and increasing amounts of waste highlight the need to transition to a circular economy characterized by closed-loop material flows. Of central importance is the expansion of the end-of-life (EOL) product disassembly, where companies must be supported in the selection of parts and the design of the disassembly system. A critical aspect is the relationship between the disassembly depth - the extent to which an EOL product is disassembled - and the design of disassembly systems. While an increased disassembly depth can improve product value and circularity, it also affects the needed disassembly process, potentially requiring adjustments to the disassembly system design. Due to this interaction and the flexible choice of the disassembly depth per product, numerous possible disassembly scenarios with different profits must be evaluated and compared. This contribution proposes an approach to support disassembly planning by enabling the data-based comparison of these scenarios. Using simulation and process mining, this approach generates comprehensive process data and facilitates the comparison of a multitude of combinations. The development of the proposed approach is described in detail, and future research opportunities are identified, such as the Design of Experiments needed to efficiently simulate various scenarios.