Reliability Engineer

1 week ago


Brno, South Moravian, Czech Republic Garrett Advancing Motion Full time 60,000 - 120,000 per year

Reliability engineer is responsible for development of the test strategy, reliability monitoring through the development and validation phases. Provide statistical analysis of field data to identify or mitigate any field risks. Reliability engineer as subject matter expert is responsible for the communication of the analysis results to the upper managements and providing necessary trainings to the other engineering teams.

Responsibilities:

Responsibility to provide reliability analysis and simulations through all product development phases.

In an early phases of the product development define reliability targets, failure mode allocation and support preliminary system simulation to assess the design reliability. Identify weak areas for improvements, monitor design updates and reliability growth.

Devise and communicate test plans needed to demonstrate reliability targets. Design testing (DoE, HALT) to assess design weaknesses with limited amount of testing. Determine sample sizes and/or equivalent test times needed for reliability demonstration on tests with few or no failures.

Expand or developed reliability and statistical tools to complex situations involving minimal information and data (Bayesian Statistics, etc..)

Routinely and effectively communicate with teams and upper management launch readiness and potential risk of each product

Analyze in-vehicle duty cycle and on-engine test cycle data using statistical and graphical technique to assess the severity.

Conduct univariate and bivariate warranty data analyses including failure forecasting and warranty term limit trade-offs.

Apply competing risk and mixed mode distribution models where appropriate.

Utilize appropriate parametric and non-parametric models when analyzing data.

Develop the life representative testing profile for e-validation and hardware validation

Develop and deliver the trainings to the engineering and management teams on reliability methods, techniques and best practice.

Develop and implement predictive reliability tools and statistical models to enable analytical risk calculations in late phases of Validation phase.

Enhance and cascade reliability lessons learned process utilizing key quality history and field experience data.

Qualifications:

Bachelor degree or above in Mechanical, Electrical or Software Engineering

Master degree or PhD in Reliability Engineering, Applied Mathematics or equivalent experience

Green Belt six sigma certification a Plus

Certified Reliability Engineer a Plus.

Experience with statistical modeling (e.g. Monte Carlo simulation, regression analysis, Statistical inference) preferred.

Experience with HALT, ALT, HASS/HASA and degradation testing techniques preferred.

Familiarity with reliability and statistics software packages (Reliasoft- Lambda Predict, Weibull++, Minitab, Python, Ansys-Mediny, Sherlock) preferred.

Automotive (E-motors, Gearbox, Invertors) experience preferred.

Conduct reliability analysis on regular basis (Weibull analysis, Regression analysis, DoE, RBD, etc.)

Ability to adapt new statistical tools to complex situations involving minimal information and data inputs

Define reliability requirements and testing plan

Identify weak areas and provide solutions based on the data analysis

Monitor reliability growth throughout development cycle

Use various software (Weibull++, Lambda Predict, Minitab, Python, Medini, Sherlock Ansys, etc.)



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