Reliability Data Analysis: Apply advanced numerical and statistical analysis methods to assess accelerated test and field data, including Weibull, Lognormal, and Exponential distributions, to predict field failure rates and inform warranty risk management.
Cross-Functional Leadership: Lead cross-functional teams, collaborate with ODMs and participate on internal teams to negotiate design options and ensure hardware adheres to reliability standards.
Accelerated & Environmental Stress Testing: Design and oversee accelerated and environmental stress testing protocols, including thermal/stress testing, HALT (Highly Accelerated Life Testing), and HASS (Highly Accelerated Stress Screening) to validate supplier and vendor reliability claims.
Required Technical Expertise
The successful candidate must demonstrate mastery in the following areas:
Life Modeling & Physics of Failure: Expertise in life modeling using Arrhenius (thermal stress), Coffin-Manson (thermal fatigue). and other models to predict product longevity.
Design of Experiments (DOE): Advanced proficiency in statistical design of experiments, specifically Taguchi methods, to optimize design robustness and minimize variance.
Statistical Validation: Ability to conduct Confidence Interval testing and Regression Analysis to validate reliability claims and performance data.
PC Stressors: Deep familiarity with PC-specific environmental stressors and test procedures, including mechanical shock, temperature, vibration, humidity, foreign contamination, and electromagnetic interference (EMI).
Education and Experience
Education: Bachelor's or Master's degree in Reliability Engineering, Materials Engineering, Electrical Engineering, Mechanical Engineering, or a related STEM field.
Experience: Typically 10+ years of experience in reliability modeling, hardware validation, or product engineering.
Proven track record of delivering high-volume consumer or commercial electronics.
Preferred Experience: Experience in establishing and revising reliability standards and procedures. Process creation and documentation experience is highly valued.
Preferred Certifications: ASQ Certified Reliability Engineer (CRE) is highly preferred.
Knowledge and Skills
Analytical Tools: Proficiency in reliability data analysis software (e.g., ReliaSoft, JMP, Minitab, etc.,) and electrical design/simulation tools.
Hardware Mastery: Deep understanding of integrated circuitry, power management, thermal management, and mechanical items prone to wear (e.g., hinges, finishes, etc.,) in mobile and desktop form factors.
Leadership: Ability to lead cross-functional programs and projects to improve standardize reliability and manufacturing processes.
Communication: Ability to translate complex failure modes and statistical analysis results into concise business risks for exe
Additional Information
Principal Reliability Engineer for Personal Systems
Description -
At HP, quality & reliability are part of the HP Way and our promise to our customers, partners, and stakeholders. As part of our journey to lead the Future of Work, the HP Personal Systems and Advanced Compute Solutions (ACS) organizations are undergoing a transformative change so that HP quality is a value add that our customers recognize.
We are seeking a highly analytical and experienced Principal Reliability Engineer to join our growing engineering team. In this role, you will be the primary architect, driving the reliability strategy, standards development, and testing of our compute portfolio. This is a highly-collaborative role, working with teams from early R&D through manufacturing to product end-of-life. You will apply advanced Design for Reliability (DFR) methodologies, life modeling, and reliability testing to ensure our products meet the quality expectations and reliability standards required by global customers, as well as understanding and quantifying design margin. You will work cross-functionally with engineering, procurement, supply chain, and Original Design Manufacturer (ODM) teams to identify potential failure modes early and drive implementation of your data-driven solutions through rigorous risk assessment and statistical analysis.
Hp · Spring, TX