<![CDATA[Background. Manufacturing firms face increasing pressure to reconcile operational efficiency with resource circularity, yet conventional production planning rarely integrates real-time system behavior with circular economy criteria. Purpose. This study aimed to develop and evaluate a digital twin–based decision-support system for sustainable production planning that balances economic, environmental, operational, and circularity objectives. Method. A design science approach was applied using 226 daily observations from an electromechanical manufacturing facility, combining virtual production modelling, multi-objective optimization, scenario analysis, and case-based validation. Results. Compared to conventional planning, the system reduced daily production costs by 8.13%, energy consumption by 12.40%, carbon emissions by 14.96%, virgin-material use by 18.23%, and waste generation by 21.05%. Additionally, recovered-material utilization increased by 42.39%, component recovery improved by 15.80 percentage points, and service level rose from 91.60% to 95.80%, while output remained stable. Conclusion. Digital twins can effectively operationalize circular economy principles by turning real-time production and recovery data into balanced, resource-efficient planning decisions without compromising delivery reliability.for OCF strategies.]]>
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