Engineer / Principal Systems Engineer - Prognostics / Phm

Northrop Grumman Northrop Grumman · Aerospace · Melbourne, FL +1 · Systems/Architecture/Test

Engineer/Principal Systems Engineer for Prognostics/PHM at Northrop Grumman. Focuses on developing and implementing algorithms for predicting system health and failures using flight/sensor data, physics of failure models, and anomaly detection. Involves data analysis, requirement decomposition, and integration of inputs from multiple systems. Requires a STEM degree, experience in HM/PHM/R&M, data analysis, and anomaly detection, with a Secret clearance.

What you'd actually do

  1. Analyze various types of flight/fault logs, assign Fault Identification (FID) codes, and host customer BIT Review Boards (BRB)
  2. Coordinate with stakeholders, suppliers, and customers, internally and externally, in support of improving Built-In-Test (BIT) Fault Detection, Fault Isolation and BIT False Alarm performance metrics
  3. Develop models and scalable algorithms derived from both data and underlying physics of failure models to evaluate the condition of Mission and Air Vehicle systems
  4. Create predictive models of physical degradation, failures, and data-driven prognostics algorithms to assess the health and performance of critical components
  5. Formulate health monitoring strategies to detect anomalies/outliers in real flight data

Skills

Required

  • Bachelor’s Degree in a Science, Technology, Engineering, or Mathematics (STEM) field
  • Experience within Health Management, Prognostics, Diagnostics, and/or Reliability & Maintainability Engineering disciplines
  • Previous experience, including academic research, directly related to the development of Prognostics Health Management (PHM) or Condition Based Maintenance Plus (CBM+) technologies, or analysis and simulation of complex electrical or mechanical systems
  • Working knowledge in data analysis (algorithms, data structures, and architectures), probability, statistics, signal processing, and predictive modeling
  • Experience with anomaly/outlier detection in time series data
  • Current in-scope (within 6 years) U.S. Government Secret Clearance

What the JD emphasized

  • Prognostics and Diagnostic processes, analysis, and design
  • Reliability and Maintainability (R&M) engineering analyses and processes
  • develop and decompose requirements
  • developing simple and complex logic or rulesets which can be used in Prognostic and Diagnostic Algorithms
  • analyze flight and sensor logs for anomalous behavior and identifying root cause
  • Built in Test (BIT) analysis
  • timeline analyses
  • detailed trade studies
  • sensor placement assessments
  • Mission Systems software analyses
  • interface definition studies
  • technical planning, system integration, verification and validation, cost and risk, and supportability and effectiveness analyses
  • functional analysis
  • requirements allocation
  • data analysis (algorithms, data structures, and architectures), probability, statistics, signal processing, and predictive modeling
  • anomaly/outlier detection in time series data

Other signals

  • Develop models and scalable algorithms derived from both data and underlying physics of failure models
  • Create predictive models of physical degradation, failures, and data-driven prognostics algorithms
  • Formulate health monitoring strategies to detect anomalies/outliers in real flight data
  • Conduct research and development projects concentrating on Prognostic Health Management (PHM) and Condition Based Maintenance Plus (CBM+)