Exensio Manufacturing Analytics: Tool to Tool Matching

See the system live at our booth all day Optical Measurement Module (OMM): In-Line µm Electrode Inspection for Predictive Quality in Battery Manufacturing As battery manufacturers face increasing pressure to reduce costs while maintaining high quality, traditional inspection methods are no longer enough. Enter the Optical Measurement Module (OMM) —PDF Solutions’ AI-powered, high-resolution inspection system designed to transform battery production from reactive to predictive . OMM leverages advanced optical imaging and machine learning to detect surface texture anomalies, impurities, and process drift in real time—without requiring prior process knowledge. With a resolution of 1-3 µm, OMM captures microstructures and surface defects that conventional systems miss, enabling manufacturers to catch issues early, reduce scrap, and improve yield. Unlike traditional inspection tools that are reactive and subjective, OMM delivers rich, objective data insights that correlate directly with yield and equipment health. It identifies early signs of equipment wear, such as calender roll degradation or slurry clumping, allowing for predictive maintenance and tighter process control. Key Capabilities: Detects organic/inorganic impurities and metallic particles as small as 15 µm Monitors surface porosity, grain size, and texture oscillations Enables real-time, inline inspection during electrode production Correlates surface data with yield to identify root causes of variability Reduces downtime, rework, and over-maintenance Proven Use Cases: Impurity Detection in NMC : OMM identified impurities missed by conventional systems, reducing scrap and improving material quality. Cathode Process Optimization : A major LFP cell manufacturer used OMM to uncover yield-impacting surface texture changes, leading to actionable process limits and improved consistency. Why OMM? Battery manufacturing is entering a new era—one where AI, automation, and data-driven decisions are essential. OMM gives manufacturers the edge to stay competitive by enabling smarter, faster, and more cost-effective production. Backed by PDF Solutions With over 30 years of experience in semiconductor analytics, PDF Solutions brings deep expertise in complex manufacturing environments. Our technologies manage over 40,000 tools globally and are trusted by 18 of the top 20 semiconductor companies. Now, we’re bringing that same innovation to batteries. Learn More Watch our recent webinar to see OMM in action and hear how leading manufacturers are using it to drive real ROI: 👉 For more information, visit www.pdf.com/battery or contact sales@pdf.com . | Yield-Aware Tool Matching: Align Tools by Performance, Not Guesswork Description ( TTTM ): Consistency across tools is essential for scaling battery production—but traditional tool matching methods often rely on subjective judgment or incomplete data. PDF Solutions’ Yield-Aware Tool-to-Tool Matching (TTTM) , powered by Exensio Manufacturing Analytics, changes that by aligning tools based on their actual impact on yield. TTTM identifies a “golden tool” and fingerprints its key performance characteristics. Other tools are then benchmarked against this standard using advanced statistical analysis, including t-tests and process capability indices. This ensures that all tools are operating within optimal parameters and contributing positively to yield. Key capabilities include: Golden Tool Benchmarking : Establishes a high-yield reference tool for comparison. Statistical Matching : Uses rigorous analytics to detect subtle but yield-impacting tool differences. Yield Correlation : Links tool performance directly to downstream cell quality and yield metrics. Maintenance Guidance : Identifies when tools need adjustment or servicing based on performance drift. Trend Monitoring & Reporting : Tracks tool performance over time for continuous improvement. Unlike traditional matching methods that focus on tool settings or visual outputs, TTTM focuses on what matters most— yield . This approach enables faster ramp-up, fewer process excursions, and more consistent product quality across lines and factories.