Real-Time-Oriented Decision-Making for Computer Numerical Control Machine Selection Under Uncertain Evidence

Computer Numerical Control (CNC) machining centers are critical assets in discrete manufacturing, yet many shop floors still rely on periodic expert judgment for machine selection and workload allocation. This practice is unsuitable for high-mix production because machine condition and risk can change rapidly due to tool wear, thermal drift, coolant variation, and alarms. Moreover, decision evidence is fragmented and often incomplete across controller and programmable logic controller signals, production records, and inspection results, making manual evaluation time-consuming and prone to misjudgment. Static rankings can also break down under unforeseen shop-floor disruptions, requiring rapid event-driven re-prioritization and rescheduling. To address these challenges, this research proposes a shop-floor decision intelligence pipeline that executes a rolling-window, uncertainty-aware ranking-and-dispatch loop directly on the shop floor. The industrial compute node continuously collects multi-source operational evidence, normalizes it into a unified event representation, and aggregates rolling-window indicators for each machine. A mapping structure then converts these indicators into neutrosophic triplets that separate performance from evidence credibility. Using this representation, a shop-floor decision procedure continuously updates machine priority scores using a TOPSIS procedure, which are further translated into workload allocation and persistence-confirmed protective action requests. A case study demonstrates end-to-end operation. It shows that the top-ranked machines remain stable under risk-aversion and weight-uncertainty analyses, while the protective logic prevents unsafe dispatching when reject-level conditions persist under reliable evidence. Overall, the proposed pipeline reframes CNC machine selection as a rolling-window, evidence-driven decision process and provides a pathway toward near-real-time and safety-aware shop-floor coordination.