Battery Manufacturing Signal Analysis for Real-Time Quality Control
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Solution Overview
Problem
The lack of effective, non-destructive, and inexpensive monitoring methods during battery cell manufacturing leads to low yield, poor quality, and inefficient resource utilization, necessitating a need for improved process control and diagnostics.
Innovation Solution
Implementing acoustic and process signal analysis systems to monitor various stages of battery cell production, providing feedback and feedforward data for process adjustments to enhance quality and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional monitoring methods are used during battery manufacturing, then device complexity is low, but manufacturing precision and quality are poor
Solution Approach 1:
The patent replaces complex mechanical monitoring equipment with acoustic emission sensing systems. Acoustic sensors detect stress waves and vibrations generated during manufacturing processes, enabling high-precision quality control through non-contact, non-destructive acoustic signal analysis rather than complex mechanical measurement systems.
Solution Approach 2:
The patent introduces acoustic signals as an intermediary medium to monitor manufacturing processes. Acoustic emission waves serve as carriers of information about internal stress, deformation, and defects, allowing indirect but highly precise measurement of manufacturing quality without direct physical intervention or complex contact-based systems.
2Manufacturing precision
If comprehensive monitoring is implemented during manufacturing, then manufacturing precision improves, but loss of time increases due to additional measurement steps
Solution Approach 1:
The patent implements continuous acoustic monitoring throughout the manufacturing process without interrupting production. Acoustic sensors continuously detect emission signals during battery cell assembly, sealing, and formation processes, enabling real-time quality assessment without stopping the production line or adding sequential measurement steps that would extend cycle time.
Solution Approach 2:
The patent performs acoustic emission detection during the manufacturing process itself, capturing quality information before defects become critical. By monitoring acoustic signals in real-time during assembly and sealing operations, the system identifies potential issues early in the process flow, eliminating the need for subsequent rework or additional inspection steps that would consume time.
3Reliability
If advanced diagnostic methods are used, then reliability of battery quality control improves, but device complexity increases
Solution Approach 1:
The patent replaces complex multi-sensor diagnostic systems with acoustic emission sensing. Acoustic waves naturally penetrate battery structures and reveal internal defects, stress concentrations, and process anomalies through their propagation characteristics, providing reliable quality control information through a single sensor type rather than complex arrays of mechanical, thermal, and electrical sensors.
Solution Approach 2:
The patent employs acoustic emission sensors that serve multiple diagnostic functions simultaneously. The same acoustic sensing system detects sealing quality, assembly defects, internal stress, and process anomalies across different manufacturing stages, providing universal reliability assessment without requiring separate specialized equipment for each diagnostic function.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances battery cell quality, reduces production costs, and improves manufacturing efficiency by identifying defects early and making real-time adjustments.
Implementation Method 1
acoustic signal and/or process signal based monitoring of various process steps
Data Source
AI summary
Systems, methods, and computer-readable media are provided for controlling a battery manufacturing process. For instance, signal based analysis that can include audio signal analysis can be performed during a first process step of a battery manufacturing process. Based on the signal based analysis, at least one adjustment can be determined for a second process step of the battery manufacturing process. Information associated with the at least one adjustment can be provided to the second process step.