Tesla

Battery Cell DFR Engineer

Tesla

April 28, 2021


Role:
This role follows the reliability lifecycle of Tesla battery cells from concept to design, development, manufacturing, field operation, and field returns to design-in, confirm and grow exceptional reliability at every stage.
Responsibilities:
  • Facilitate Design FMEA sessions in order to drive reliable design choices and improve validation test planning and assemblies.
  • Design and conduct DOE studies to discover, understand, quantify underlying failure physics and governing stress-life relationship and acceleration factor model.
  • Conduct systematic statistical analysis of internal cell testing data and make meaningful inference for decision making and engineering improvement.
  • Establish cell level reliability data library.
  • Analyze usage and environmental conditions from the field in order to improve requirement setting and testing methods.
  • Apply reliability failure physics to design accelerated test methods to failure modes exploration and reliability growth.
  • Spec out reliability validation plans for components and subsystems.
  • Facilitate failure analysis to understand root cause and drive resolution for failures originating in testing and from the field.
  • Work with manufacturing quality, service engineering, supplier quality and design teams to facilitate field failure resolution (aka Weibull) in order to support all investigations.
  • Design ongoing reliability test (ORT), reliability stress screening, and monitoring mechanism to assure consistent outgoing reliability.
  • Provide reliability design guidelines and apply reliability lessons learned to enable continuous improvement.

Desired Skills:
  • Experience working with lithium ion cells and cell components.
  • Working knowledge of applied statistics and experience with statistical software such as JMP, Minitab, SAS, ReliaSoft Synthesis Platform (including Weibull++, BlockSim, ALTA, RGA, and xFMEA), or equivalent.
  • Knowledge of reliability warranty analysis and reliability prediction methods.
  • Working knowledge of failure analysis techniques such as optical microscopy, SEM, CSAM,
  • X-ray, cross-sectioning and EDX.
  • Knowledge of database structures and practical understanding and use of SQL. Experience
  • in working with large data sets. Experience with Tableau for big data analytics.
  • Working knowledge of applied statistics and experience with statistical software.
  • Understanding of fleet reliability monitoring metrics and reliability KPIs.
  • ASQ Certified Reliability Engineer preferred.

Requirements:
  • BS, MS, or Ph.D. in Materials Science, Chemical Engineering, Mechanical Engineering, or Physics and one or more years of industry experience on reliability of lithium ion cells.