Abstract
Purpose: Predictive maintenance programs employ non‐invasive methods to monitor the performance of systems to determine when preemptive intervention is required to maintain high quality performance. The focus of this study is to evaluate the effectiveness of a modified calculation method for the control limits of process control charts (PCC) that will reduce false positive alarms but detect clinically relevant changes in beam uniformity (flatness and symmetry). Methods: Steering coil currents (SCC) for the transverse and radial planes are adjusted such that a reproducibly useful photon or electron beam is available. Performing controlled experiments varying a single SCC, we were able to determine the magnitude of change required to produce a 1% change in beam uniformity. The average and range (Xbar/R) control chart limit calculation was reformulated incorporating a scaling factor (Cm). After monitoring the SCC of 3 accelerators for several months, without detecting any PCC alarms, we intentionally changed the transverse angle and position SCC independently until the beam symmetry differed by ∼1.1% from baseline as confirmed by computerized beam profile scan in water using an ion chamber. These experimental SCC values were plotted in the PCC to determine if they would exceed the modified control limits. Results: The experimental SCC value exceeded the PCC limit for each of the steering coils. Additionally, the capability of the new control limit calculation method was confirmed when an anomaly was detected in the operation of an accelerator in clinical use. Instability in the operation of the 18 MV photon beam was predicted by SPC analysis prior to it being confirmed by service and daily check devices. If the analysis had been performed using the original methodology, a number of false positives would have been reported. Conclusion: Reformulated X‐bar/R chart control limits of SCC can provide an effective predictive maintenance tool for accelerator beam uniformity. This project is supported by a grant from Varian Medical Systems.
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