A risk analysis method for potential failure modes in the lithium-ion battery assembly process based on optimized...

Area of Science:

• Materials Science
• Engineering
• Risk Management

Background:

• Lithium-ion batteries are critical for modern technology, necessitating enhanced safety and quality.
• Traditional risk analysis methods may lack the precision to capture complex uncertainties in battery manufacturing.

Purpose of the Study:

• To develop an improved Failure Modes and Effects Analysis (FMEA) for lithium-ion battery risk assessment.
• To enhance the accuracy and objectivity of risk ranking in battery production.

Main Methods:

• Utilized Double Hierarchy Hesitant Fuzzy Linguistic Term Set (DHHFLTS) for nuanced evaluation.
• Employed Similarity Measure (SM) and Water Filling Theory (WFT) for consensus-based weight determination.
• Applied Combined Compromise Solution (CoCoSo) and Multi-Objective Aggregation Technique (MOAT) for risk analysis and validation.

Main Results:

• The proposed SM-WFT method offers a more suitable approach for weight calculation in FMEA compared to dispersion-based methods.
• The CoCoSo method effectively minimizes identical risk rankings, improving differentiation.
• The MOAT provides a robust framework for validating new risk analysis techniques.

Conclusions:

• The novel FMEA method demonstrates practicality and objectivity in analyzing potential failure modes in lithium-ion battery assembly.
• This approach contributes to enhanced product quality and operational safety in battery manufacturing.