Machine Learning Enhanced Acoustic Inspection to Improve Battery Manufacturing

Summary

SCH Number
2021040198
Public Agency
California Energy Commission
Document Title
Machine Learning Enhanced Acoustic Inspection to Improve Battery Manufacturing
Document Type
NOE - Notice of Exemption
Received
Posted
4/7/2021

Document Description
The California Energy Commission is providing Feasible, Inc. with a $1,000,000 grant to support the commercialization of a machine-learning-driven battery inspection platform called EchoStat, which uses ultrasound and data analytics to detect manufacturing issues earlier and with more sensitivity. This project aims to reduce battery cell cost and to reduce the likelihood of safety incidents from unexpected battery failures. The project will be carried out in the fully permitted, existing 4942 sq. ft. facility in Emeryville, CA. No permits are required for the operation of the project, and is categorically exempt from the provisions of CEQA.

Contact Information
Maggie Deng
Commission Agreement Manager
Lead/Public Agency
1516 Ninth Street
Sacramento, CA 95814

Phone : (916) 776-0749
maggie.deng@energy.ca.gov

Location

Cities
Emeryville
Counties
Alameda
Cross Streets
1516 Ninth Street
Zip
95814

Notice of Exemption

Exempt Status
Categorical Exemption
Type, Section or Code
Cal. Code Regs., tit. 14, § 15301 ; Cal. Code Regs., tit. 14, § 15306
Reasons for Exemption
The project involves development, testing, and validation of a machine-learning-driven battery inspection platform called EchoStat. The development and assembly will take place at a Feasible, Inc.'s existing facility in Emeryville, California. This will include minor interior alterations and operation of facilities and mechanical equipment. There will be no change of use and no expansion of the building. The testing and validation will be performed at one or more existing manufacturers' facilities already in operation, possibly the facilities of a Tier 1 German automaker.

Attachments

Notice of Exemption
CEQA-EPC-20-020- Deng (4   PDF 208 K

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