Reducing treatment machine downtime with a preventative MLC maintenance procedure

Agnew, Christina; Esteve, Sergio; Whitten, Glenn; Little, William C.

doi:10.1016/j.ejmp.2021.04.012

Cited by 5 publications

(7 citation statements)

References 11 publications

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“…This would keep the MLC in optimal conditions and would also avoid the occurrence of this type of interlocks. Agnew et al 26 recently published an article in which they showed how regular cleaning and maintenance of each MLC leaf reduces downtime of the accelerator. By using our method, this maintenance could be optimized by determining when and which leaf needs an intervention.…”

Section: Discussionmentioning

confidence: 99%

MLC performance prognosis using a degradation model based on trajectory log data from a daily test

et al. 2022

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Purpose This paper investigates the feasibility of implementing a predictive maintenance program for a multileaf collimator (MLC) based on data collected in trajectory logs (TLs) obtained by conducting a simple daily test, with the aim of minimizing unscheduled downtime. Methods A dynamic field test was designed, and the TLs generated in the course of daily administration in a linear accelerator were collected to evaluate trajectory deviations of the MLC leaves as well as interlocks (COL 420219/20, COL 420207/08) reported by the machine. During this evaluation, we observed that the trajectory deviations of some leaves increased up to a threshold value beyond which certain interlocks began to appear in treatment fields in those leaves. An exponential degradation model was therefore developed to predict this drift and determine each leaf's remaining useful life (RUL). Once the applicability of the model was confirmed, we added a second accelerator equipped with an MLC with the same configuration to validate the model. Results The model was able to predict certain COL 420219/20 interlocks resulting from primary readout/expected position discrepancies and to estimate each leaf's RUL. In total, 11 cases (8 interlocks + 3 potential interlocks avoided due to service interventions [27.3% of the total]) were detected over 7 days in advance, with no false positive results. Scheduling of service interventions several days prior to MLC failure would therefore be possible. When these types of interlocks were not predicted by the model, they were always generated by leaf motor failure. Consequently, intervention time could also be optimized by directly replacing the motor. During the study period, for these types of interlocks, our approach would have reduced downtime from 35.25 to 4.00 h (88.7%) and from 34.75 to 22.83 h (34.3%) for each accelerator, respectively. For COL 420207/08 interlocks, which are generated by primary/secondary readout discrepancies, no correlation with leaf trajectory deviation increases recorded in the TLs was found. Throughout the study period, these types of interlocks requiring service intervention, also mainly for motor replacement, represented a downtime of 9.50 h for the first accelerator (21.2% of total downtime) and by 4.33 h (11.1% of total downtime) for the second accelerator. Conclusion This study demonstrates that by applying a predictive MLC maintenance program based on information collected in TLs, it is possible to predict certain interlocks and therefore schedule preemptive interventions to avoid their occurrence. This could optimize health‐care delivery performance and minimize the loss of treatment sessions.

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Section: Discussionmentioning

confidence: 99%

MLC performance prognosis using a degradation model based on trajectory log data from a daily test

et al. 2022

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“…Of the facilities that did provide their QA procedures, most were either an hour in the morning or several hours (between 2 and 5) on a weekend, but exact details were not recorded. The benefits of PMI are well documented for HICs 18,19 ; however there is not enough data to draw any meaningful conclusions about the effect of QA and PMI on LINAC breakdowns in LMICs. As such, we treat the QA procedures as consistent across facilities and study the breakdowns occurring in spite of operators best efforts in these measures.…”

Section: Collection Of Indonesian Hospital Datamentioning

confidence: 99%

Failure modes and downtime of radiotherapy LINACs and multileaf collimators in Indonesia

Pawiro

Kasim

et al. 2022

J Applied Clin Med Phys

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Background and purpose The lack of equitable access to radiotherapy (RA) linear accelerators (LINACs) is a substantial barrier to cancer care in low‐ and middle‐income countries (LMICs). These nations are expected to bear up to 75% of cancer‐related deaths globally by 2030. State‐of‐the‐art LINACs in LMICs experience major issues in terms of robustness, with mechanical and electrical breakdowns resulting in downtimes ranging from days to months. While existing research has identified the higher failure frequency and downtimes between LMICs (Nigeria, Botswana) compared to high‐income countries (HICs, the UK), there has been a need for additional data and study particularly relating to multileaf collimators (MLCs). Materials and methods This study presents for the first time the analysis of data gathered through a dedicated survey and workshop including participants from 14 Indonesian hospitals, representing a total of 19 LINACs. We show the pathways to failure of radiotherapy LINACs and frequency of breakdowns with a focus on the MLC subsystem. Results This dataset shows that LINACs throughout Indonesia are out of operation for seven times longer than HICs, and the mean time between failures of a LINAC in Indonesia is 341.58 h or about 14 days. Furthermore, of the LINACs with an MLC fitted, % of all mechanical faults are due to the MLC, and % of cases requiring a replacement component are related to the MLC. Conclusion These results highlight the pressing need to improve robustness of RT technology for use in LMICs, highlighting the MLC as a particularly problematic component. This work motivates a reassessment of the current generation of RT LINACs and demonstrates the need for dedicated efforts toward a future where cancer treatment technology is robust for use in all environments where it is needed.

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“…This issue has been solved quite clearly in companies where the maintenance problem is implemented in one of the so-called maintenance shifts. A similar approach was presented in another work [ 30 ], where the authors conducted analyses on the impact of a preventive procedure on the reduction of downtime in the case of the Multi-Leaf Collimators machine (MLC).…”

Section: Literature Reviewmentioning

confidence: 99%

Applying Sensor-Based Information Systems to Identify Unplanned Downtime in Mining Machinery Operation

Brodny

2022

Sensors

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Underground mining belongs to immensely complex processes and depends on many natural, technical and organizational factors. The main factor that hinders this process is the environmental conditions in which it is carried out. One of the problems associated with the use of increasingly modern machines in such conditions is the issue of unplanned downtime during their operation. This paper presents the developed methodology and IT system for recording breaks in the operation of mining machines and identifies their causes. The basis of this methodology is a sensor-based information system used to register mining machinery parameters, based on which interruptions in their operation can be determined. In order to register these parameters, an industrial automation system (together with a SCADA system supervising the process) was used, which is practically independent from the operator and enables continuous registration of these parameters. In order to identify the reasons for the recorded breaks, an IT tool was developed in the form of an application in the module of the integrated mining enterprise management support system (ERP system). This application enables (with a continuously updated database) the identification of the causes in question. Thus, the developed solution enables the objective registration of machine downtime and, for most cases, the identification of causes. The acquired knowledge, so far largely undisclosed, has created opportunities to improve the utilization level of machinery exploited in the mining production process. The paper discusses the methodology, together with the IT system, for identifying the causes of machine downtime and presents an example of its application for a shearer loader, which is the basic machine of a mechanized longwall system. The results indicate great potential for the application of the developed system to improve the efficiency of machinery utilization and the whole process of mining production.

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Reducing treatment machine downtime with a preventative MLC maintenance procedure

Cited by 5 publications

References 11 publications

MLC performance prognosis using a degradation model based on trajectory log data from a daily test

MLC performance prognosis using a degradation model based on trajectory log data from a daily test

Failure modes and downtime of radiotherapy LINACs and multileaf collimators in Indonesia

Applying Sensor-Based Information Systems to Identify Unplanned Downtime in Mining Machinery Operation

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