PDF Solutions to enhance battery analytics platform with acquisition of Lantern Machinery Analytics

PDF Solutions, a provider of comprehensive data solutions for the semiconductor and electronics ecosystems, has acquired Lantern Machinery Analytics, a privately-held provider of automated image analysis and feature extraction AI/ML software for critical inspection and metrology steps at battery cell development and manufacturing processes for the electric vehicle industry.

Machinery Analytics’s automated ML models find and measure features of interest throughout the development and manufacturing processes. For example:

• Scanning Electron Microscopy (SEM). Identify and measure any features in SEM or TEM images at any scale. Generate featured size density functions for individual images or batches of images.

  

• Optical Microscopy. Identify active material, binder, voids, agglomorations and areas of high texture in optical microscopy images. Generate featured size density functions for individual images or batches of images. One case study example adduced by the company is the use of microstructure imaging to remove coating solvent. The image analysis software is used with optical microscopy to map active material distribution, agglomeration distribution and coating texture for an NMP-free cathode coating.

  

• X-Ray. Measure features and identify voids using X-ray or tomography images. Combine multiple images to generate part level data.

  

• Time-Series. Automatically identify unusual events in time-series data up to 1500 channels and 4GB/day data rates. Classify and then automatically tag any recurring anomalies.

The combination of Lantern Machinery Analytics’ software with PDF Solutions’ analytics platform is anticipated to enhance the company’s process control and yield improvement offerings by providing unique data and capability in the area of vision inspection for electric vehicle battery cell manufacturing.

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