A new energy battery non-standard assembly equipment auxiliary variant design method

By designing process-motion-equipment mapping and material attitude matrix, and combining stochastic maxima with algebraic modeling, the problems of low equipment matching efficiency and insufficient stability assessment during process changes in new energy battery assembly lines are solved, thus achieving efficient and reliable assembly line design.

CN121167983BActive Publication Date: 2026-06-05GUANGDONG UNIV OF TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GUANGDONG UNIV OF TECH
Filing Date
2025-08-05
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing new energy battery assembly lines lack a systematic process-action-equipment mapping mechanism when facing process changes, resulting in low equipment matching efficiency, unsmooth material transfer, and failure to comprehensively measure stability and reliability when evaluating assembly line performance.

Method used

By employing process-motion-equipment mapping, material attitude matrix design, loss value and trade-off value calculation, combined with stochastic maxima algebraic modeling, equipment sets are screened through a knowledge graph library, a mapping matrix is ​​constructed, multiple assembly line schemes are generated, and multi-objective trade-off evaluation is performed.

Benefits of technology

It improves the efficiency and quality of assembly line design, ensures accurate equipment selection, reduces material transfer disruptions and failure risks, comprehensively assesses production line stability and reliability, and significantly shortens the design cycle.

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Abstract

The present application relates to the technical field of new energy battery assembly line system configuration design, and proposes a new energy battery non-standard assembly equipment auxiliary variant design method, which comprises the following steps: obtaining a device set meeting the new process action requirement from a knowledge graph library; constructing a process-action mapping matrix and a device-action mapping matrix based on the multi-color set theory and the device set, and then generating a process-device relationship matrix through the conjunction and disjunction operation; defining the material posture matrix of the inlet and outlet position of each device for each device in the process-device relationship matrix; generating several new energy battery assembly line schemes based on the space position function matrix of the buffer area; performing random maximum plus algebra modeling, introducing a disturbance event parameter to calculate the line productivity, configuration cost and system fragility loss; performing weighted summation on the line productivity, configuration cost and system fragility loss to generate a multi-objective trade-off value, and outputting an optimal new energy battery assembly line design scheme.
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