Digital product passport enabled production control in the context of circular economy

Abstract

Digital Product Passports (DPP) are seen as a key technology to overcome the lack of transparency of products in context of circular economy and allow a simplified derivation of quality conditions. In this paper, a production control model is presented, that generates remanufacturing, recycle and reuse strategies within a linear production system based on information from the DPP. The quality condition, derived from the DPP, and the system utilization serve as the basis for the reinforcement learning (RL) model, which optimally integrates used parts into the linear production flow. In addition to optimizing throughput, the aim of the model is also to save material and energy, which can be achieved by reusing or remanufacturing used products. The integration of used products into the linear production was tested using a production system from the water meter industry. It was shown by simulation that with the developed RL model the material consumption of the production of water meters could be significantly reduced by finding optimal circular strategies.