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BiBTeX citation export for MOPHA141: Dynamic System Reliability Modelling of SLAC’s Radiation Safety Systems

@InProceedings{tao:icalepcs2019-mopha141,
  author       = {F. Tao and K.W. Belt},
  title        = {{Dynamic System Reliability Modelling of SLAC’s Radiation Safety Systems}},
  booktitle    = {Proc. ICALEPCS'19},
  pages        = {558--561},
  paper        = {MOPHA141},
  language     = {english},
  keywords     = {controls, PLC, operation, electron, experiment},
  venue        = {New York, NY, USA},
  series       = {International Conference on Accelerator and Large Experimental Physics Control Systems},
  number       = {17},
  publisher    = {JACoW Publishing, Geneva, Switzerland},
  month        = {08},
  year         = {2020},
  issn         = {2226-0358},
  isbn         = {978-3-95450-209-7},
  doi          = {10.18429/JACoW-ICALEPCS2019-MOPHA141},
  url          = {https://jacow.org/icalepcs2019/papers/mopha141.pdf},
  note         = {https://doi.org/10.18429/JACoW-ICALEPCS2019-MOPHA141},
  abstract     = {When the LCLS-II project is complete, there will be three major Department of Energy (DOE) beam programs occupying the same 2-mile long accelerator tunnel, e.g. LCLS, LCLS-II and FACET-II. In addition to the geographical overlap, the number of beam loss monitors of all types has been also significantly expanded to detect power beam loss from all sources. All these factors contribute to highly complex Radiation Safety Systems (RSS) at SLAC. As RSS are subject to rigorous configuration control, and their outputs are permits directly related to beam production, even small faults can cause a long down time. As all beam programs at SLAC have the 95% beam availability target, the complex RSS’s contribution to overall beam availability and maintainability is an important subject worth detailed analysis. In this paper, we apply the dynamic system reliability engineering techniques to create the RSS reliability model for all three beam programs. Both qualitative and semi-quantitative approaches are used to identify the most critical common causes, the most vulnerable subsystem as well as the areas that require future design improvement for better maintainability.},
}