The Core of Battery Safety: Full-Parameter Monitoring & 'Lag' Correlation Mining

Tackling the GWh-scale massive data challenge in the Li-ion industry. From closed-loop control of electrode coating to full-process traceability of cell packaging, use SPC to lock down every tiny fluctuation affecting safety.

timelineAuto-Lag Correlation monitoringSub-second Monitoring hubMulti-Cutter Consistency fingerprintIndividual Cell Traceability
Auto-Lag · Highest R² Match
Auto-Lag Correlation Chart

Industry Pain Points

"When coating thickness deviations are found, thousands of meters of electrode have already been wound. How do we close the time gap between 'process' and 'result'?"
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The 'Time Lag' Black Box in Continuous Processing

Adjusting the feed pump speed (X) doesn't immediately reflect on the thickness gauge (Y); there is often a delay of seconds or minutes. Traditional SPC cannot auto-match this time gap, making precise process adjustment impossible.

all_inclusive

Throughput Pressure of Massive Data

A single production line generates tens of millions of data points daily (temperature, pressure, tension, thickness). Standard SPC software lags or crashes when handling high-frequency data, and monitoring failure means risks spiral out of control.

health_and_safety

Safety Anxiety & Full Lifecycle Traceability

A single cell failure can trigger thermal runaway. Automakers demand 100% data traceability from raw material batches to electrolyte injection volume. Excel simply cannot handle this data chain.

NEXSPC Core Scenarios & Solutions

Deconstructing Li-ion's 'continuous flow, high-frequency, multi-channel, safety traceability' into computable, monitorable, and interceptable engineering actions.

Auto-Lag Auto-Lag Regression Analysis

Exclusive 'Auto-Lag' Regression Analysis

Auto-Lag

Let the algorithm automatically link the 'current effect' to the 'past cause' from minutes ago. This is the killer application for optimizing front-end Li-ion processes (coating, calendering).

  • Smart Spatiotemporal Alignment：Automatically traverses time lags (T-1s...T-60s) to find the optimal alignment window.
  • Optimal Match Lock-in：System prompts: 'Highest correlation at 45 seconds lag (R²=0.98)'.
Value: Accurately build mathematical models between KCC (Key Control Characteristics) and KPC (Key Product Characteristics) to achieve closed-loop control.
OPC UA / PLC OPC UA PLC Integration

'Sub-second' Monitoring of High-Frequency Data

PLC / OPC / MQTT

Monitor every meter of electrode quality like an ECG. Tailored for the high-speed operation of coaters and calendering machines, NEXSPC provides high-performance data acquisition and computation.

  • Direct PLC Communication：Read key data such as tension, roll gap, and temperature via OPC UA.
  • Xbar-S Control Chart：Xbar-S is recommended for high-frequency sampling; it captures micro-variations more sensitively than Xbar-R.
  • Data Cleansing：Automatically filters invalid segments during downtime/roll changes to prevent Cpk calculation pollution.
Value: Trigger early warnings before deviations expand, stopping defects in the exact second they occur.
Group Compare

多通道/多切刀一致性分析

Group Compare

分切工序的“多胞胎”管理专家。一大卷极片被切成 20 条窄带，差异往往来自某一把刀具磨损或局部辊压不平。

  • 分组箱线图：一键生成 20 把切刀毛刺高度对比。
  • 异常定位：快速识别 #12 刀磨损导致偏大，还是整体问题。
  • 精准更换：无需停机全检，直接更换故障刀具。
价值：把“抽检猜测”升级为“数据定位”，减少停机与误更换。

客户价值对比（Before & After）

从工艺优化到数据吞吐，再到安全追溯：每一项都是“安全与成本”的硬指标。

维度 传统模式 NEXSPC 锂电行业版
工艺优化 经验估算延迟，调整常“过调/欠调” Auto-Lag 自动计算最佳滞后时间，精准控制
数据处理 Excel 几万行就卡死，无法全量分析 高性能数据库架构，轻松吞吐 GWh 级海量数据
分切管理 混在一起抽检，不知道哪把刀有问题 20 把切刀分组对比，精准定位磨损刀具

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