A quantitative ERP-driven framework for the circular economy: development and simulation-based validation for sustainable manufacturing

Abstract

To address the significant fragmentation in Circular Economy (CE) assessment models and the gap in their deployment within digital enterprise platforms. This research presents the Quantitative ERP-Driven CE (Q-EDCE) Framework to bridge the divide between sustainability theory and manufacturing Information Technology. The study develops a multi-layered architecture that includes a Strategic Layer for establishing Value Retention Processes (VRPs), an Operational Layer that links these to functional ERP modules (such as Reverse Logistics and SCM), and a Measurement Layer that defines six specific Sustainability KPIs.PIs (S-KPIs). This conceptual model integrates Industry 4.0 technologies like IoT and Big Data, along with real-time MES data flows. The framework is validated through a Python-based numerical simulation using an industrial detergent manufacturing dataset. The simulation demonstrates that the architecture effectively transforms a linear “As-Is” baseline into a circular model, resulting in a 69.7% increase in the Material Circulating Rate (MCR) and a 50% increase in the Waste Recovery Rate (WRR). Additionally, the conceptual integration enables a shift from retrospective, static reporting to dynamic, proactive decision-making and real-time resource optimization. This work redefines ERP systems from simple transactional tools to powerful digital infrastructures that enable circularity. It provides a unique, systematic roadmap for integrating circular performance directly into organizational data flows, transforming sustainability from an abstract goal into a tangible corporate advantage.