2026 Capabilities

The Confluence of Failure Analysis & RCA in Power Infrastructure, IoT, Autonomous Systems and IP Law

Semiconductor Forensics & Intellectual Property

• Execution of reverse engineering and competitor evaluations at both the package and semiconductor levels.

• Investigation of potential patent infringement and identification of copycat behavior.

• Utilization of a comprehensive failure analysis (FA) toolbox to strategically evaluate and work around competitor patents.

• Management of outsource labs, including FIB-STEM and Auger, to optimize technical bandwidth for complex material characterization.

Data Center & Power Infrastructure Reliability

• Deployment of diagnostic methodologies to isolate complex root causes, including AC transient analysis for gate-drain shorts and R3D simulations for low on-resistance paradoxes.

• Analysis of thermo-mechanical stress on interconnects, identifying wire bond fatigue and degradation resulting from active power-cycling.

• Application of uncooled long-wavelength infrared (LWIR) Lock-In Thermography (LIT) to localize low-level leakage and characterize circuit operation at the package and die levels.

• Troubleshooting of complex power architectures, including Voltage Regulation Modules (VRMs), multi-phase buck converters, and 3-phase half-bridge power MOSFETs.

Autonomous Systems & Electromechanical Sustainment

• Development of Application-Specific Reliability (ASR) frameworks to investigate field failures caused by severe electromechanical stress.

• Engineering of custom High-Current-Temperature (HCT) characterization systems combined with multi-scale physical analysis (SEM/TEM) to model empirical fatigue.

• Management of robust FRACAS workflows leveraging structured methodologies, including 5 Whys, 8D, and Fault Trees.

• Evaluation and optimization of smart home ecosystems and HVAC loads through sensor technology and predictive analytics.

Executive Leadership & Quality Systems

• Integration of failure analysis protocols into ISO9001 Quality Management System (QMS) frameworks to establish closed-loop defect prevention.

• Execution of data-driven performance management, establishing KPI reports, operating cost models, and tracking databases.

• Resolution of complex, high-stakes engineering disputes through empirical, physics-based data to drive systemic manufacturing and supply chain improvements.