OMM: AI-Powered Electrode Optical Inspection for Battery Lines

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 . | 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: 👉 https://parmonic.ai/pdfsolutions/lp/webinar/c050807146c05ca4 For more information, visit www.pdf.com/battery or contact sales@pdf.com .