Answers are grounded in this paper and cite their sources.
Manufacturing systems must simultaneously reduce resource intensity and maintain operational continuity under disruption, yet most real-time control architectures do not incorporate circular-economy and resilience objectives within production decision making. This study develops and evaluates a Digital Twin (DT) framework that functions as a decision engine for Industry 5.0 production systems rather than as a monitoring-only representation. In this framework, the DT remains synchronized with the physical line through live IoT data, a credibility gate that suspends prescriptive actions when synchronization error exceeds acceptable bounds, a provenance ledger that records material recovery events, and a multi-objective scheduler that balances energy consumption, waste generation, and delivery delay under human approval. Circularity is operationalized as the share of material recovered through reuse or recycling, whereas resilience is quantified as normalized recovery performance following a disruption. Using a design science approach, the framework was implemented for six months on an operating electronics manufacturing line in Riyadh, Saudi Arabia, covering 3,048 production lots. The evaluation combined a two-month baseline, a four-month intervention period, and disruption scenarios for supplier delay, machine breakdown, and quality shift events. The intervention reduced energy intensity by 14.4%, decreased weekly downtime by 23.9%, and increased overall equipment effectiveness by 5.0% while maintaining product quality. The circularity rate increased from 0.23 to 0.33, with larger gains for packaging and casings than for printed circuit boards because of component-specific reuse constraints. Resilience scores increased from 0.71 to 0.82, indicating faster recovery from supply and equipment disruptions. These findings show that a traceable, credibility-gated, human-supervised DT can align shop-floor decisions with circularity and resilience objectives, although the reported gains should be interpreted in light of the single-line pilot context.
No takes yet. Share an insight, caveat, or question.
Ragu Prasadh Rajendran (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: