Set and communicate reliability requirements and targets for site, product, subsystem, and components
Create Fault Trees and reliability block diagrams to assess system reliability and warranty analysis Facilitate Design FMEA sessions to drive reliable design choices and improve validation test programs
Analyze usage and environmental conditions from the field to improve requirement setting and testing methods
Apply statistical analysis to test (accelerated life) and field (life) data to inform reliability physics modeling/analyses and associated corrective actions. Work closely with Design and Reliability Data engineers to create/interpret/validate numeric models of fielded and in-test products
Specify reliability validation plans for components and subsystems using physics of failure. Provide guidance on sample size requirements and durations for reliability testing using lifetime models and reliability statistics
Drive reliability assessments in product design reviews and clearly communicate risk at each phase of product development and for released products
Facilitate failure analysis to understand root cause and drive resolution of failures occurring during product development
Research failure mechanisms to build more robust validation plans and influence design choices
Influence supplier selection for higher reliability and provide clear guidance on reliability requirements and demonstration to suppliers. Provide reliability design guidelines and apply reliability lessons learned to enable continuous improvement
Answer complex questions on fleet usage and behavior to enable proactive health monitoring, grow reliability, and minimize field failures
What You’ll Bring
Solid Power Electronics fundamentals
Understanding of accelerated testing methods, governing equations, and physics of failure for different failure mechanisms
Understanding of applied statistics and reliability statistics (Weibull distribution, Maximum Likelihood Estimation, Bayesian methods, Monte Carlo analysis, etc.)
Working knowledge of failure analysis techniques such as optical microscopy, SEM, CSAM, X-ray, cross-sectioning and EDX
Knowledge of the ReliaSoft Synthesis Platform, including Weibull++, BlockSim, ALTA, RGA, and xFMEA
Knowledge of methods to design-in reliability for electronics, including electronic computer-aided design and mechanical computer-aided engineering (CAE) data into 3D finite element models (e.g. using Sherlock)
Working knowledge of programming languages, preferably Python
Knowledge of reliability growth techniques, such as Crow-AMSAA and Crow Extended is a plus
Knowledge of reliability warranty analysis and reliability prediction methods
Bachelor of Science in Engineering or equivalent experience