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智能制造与工业4.0
by
ai-gaoqian
· GitHub ↗
· v1.0.0
· MIT-0
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Install in OpenClaw
/install smart-manufacturing-industry40
Description
面向制造业的AI智能体技能，支持生产排程优化、质量缺陷检测（视觉AI）、设备预测性维护、BOM物料管理、工业安全合规、MES/ERP数据对接。适用于离散制造和流程制造两大领域。
README (SKILL.md)
智能制造与工业4.0 (Smart Manufacturing & Industry 4.0)
概述
将AI能力融入制造业核心流程，从生产计划到质量检测，从设备维护到物料管理，全面提升工厂运营效率和产品质量。支持离散制造（汽车、电子）和流程制造（化工、食品）两大领域。
核心能力
1. 生产排程优化
- 多订单、多产线、多工序的智能排程
- 插单、急单的排程动态调整
- 瓶颈工序识别与产能利用率分析
2. 质量缺陷检测
- 基于视觉AI的产品外观缺陷检测（划痕、色差、形变、毛刺等）
- 不良品统计分析与根因追溯
- SPC统计过程控制图表自动生成
3. 预测性维护
- 设备运行参数异常检测（振动、温度、电流）
- 故障模式识别与剩余寿命预测
- 维保计划自动生成与备件需求预判
4. BOM与物料管理
- BOM结构分析与成本拆解
- 物料需求计划（MRP）自动计算
- 替代料推荐与供应链风险提示
5. 工业安全与合规
- 安全生产规范合规检查
- 危险作业风险评估与防护建议
- 事故案例分析库查询
使用方式
优化 [生产订单数据] 的排程方案
检测这批产品图片是否存在缺陷 [上传图片]
分析 [设备运行参数] 是否需要提前维护
计算 [BOM清单] 的物料需求计划
输出格式
- 排程方案：甘特图数据 + 产线占用率 + 交付达成预估
- 质量报告：缺陷类型分布 + 关键工序CPK值 + 改进建议
- 维护计划：设备风险等级颜色标记 + 维保时间窗 + 备件清单
- MRP报表：物料需求时间序列 + 采购建议 + 安全库存预警
适用场景
- 电子/汽车零部件企业的生产排程与质量管控
- 化工/食品企业的流程优化与安全合规
- 设备密集型工厂的预测性维护
- 中小制造企业的数字化转型起步
注意事项
- 预测性维护模型需要足够的设备历史数据支撑
- 视觉检测精度受光照和拍摄条件影响，建议标准化采集环境
- 生产排程优化结果需结合现场实际情况微调
- 数据底座覆盖ISO/GB制造业标准及常见工业协议格式
Usage Guidance
Install only if you intend to analyze manufacturing operations data. Avoid uploading trade secrets, customer-identifying records, plant-security details, regulated operational records, or full ERP/MES exports unless you are authorized and have minimized or redacted the data.
Capability Assessment
Purpose & Capability
The skill describes production scheduling, defect image review, predictive maintenance, BOM/MRP analysis, and safety compliance; image, file, data, and structured-data capabilities are coherent with those tasks.
Instruction Scope
Invocation examples are broad and the skill would benefit from clearer activation boundaries and required inputs, but the examples remain within the stated manufacturing purpose.
Install Mechanism
The artifact contains only a single SKILL.md markdown file and no executable installer, scripts, package hooks, or external dependency setup.
Credentials
Factory orders, BOMs, equipment telemetry, ERP/MES exports, and inspection images may be sensitive; the requested file and analysis capabilities are proportionate, but users should provide only authorized, minimized data.
Persistence & Privilege
No persistence, background workers, privilege escalation, credential/session use, network calls, mutation authority, or destructive behavior are present in the artifact.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install smart-manufacturing-industry40 - After installation, invoke the skill by name or use
/smart-manufacturing-industry40 - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of Smart Manufacturing & Industry 4.0 skill.
- Provides AI-powered production scheduling optimization for discrete and process manufacturing.
- Supports visual AI for quality defect detection and reporting.
- Enables predictive maintenance via equipment parameter monitoring and fault prediction.
- Offers intelligent BOM analysis and automated material requirements planning (MRP).
- Includes industrial safety compliance checks and risk analysis.
- Integrates with MES/ERP data and supports standard industrial data formats.
Metadata
Frequently Asked Questions
What is 智能制造与工业4.0?
面向制造业的AI智能体技能，支持生产排程优化、质量缺陷检测（视觉AI）、设备预测性维护、BOM物料管理、工业安全合规、MES/ERP数据对接。适用于离散制造和流程制造两大领域。 It is an AI Agent Skill for Claude Code / OpenClaw, with 41 downloads so far.
How do I install 智能制造与工业4.0?
Run "/install smart-manufacturing-industry40" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 智能制造与工业4.0 free?
Yes, 智能制造与工业4.0 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 智能制造与工业4.0 support?
智能制造与工业4.0 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 智能制造与工业4.0?
It is built and maintained by ai-gaoqian (@ai-gaoqian); the current version is v1.0.0.
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