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Auto Parts Quality Analysis

作者 zxw8309 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install auto-parts-quality
功能描述
Senior automotive parts quality analysis expert skill. Use when analyzing quality issues, failure modes, 8D reports, SPC data, PPAP documents, or any automot...
使用说明 (SKILL.md)

Auto Parts Quality Analysis

Core Workflow

1. Quality Issue Analysis

When analyzing quality issues, follow this structure:

A. Problem Definition

  • Part name, part number, supplier
  • Symptom description (field failure, customer complaint, in-process defect)
  • Failure rate / population affected
  • Timeline (when discovered, volume shipped)

B. Evidence Collection

  • Photos / microscope images
  • Measurement data (dimensional, roughness, hardness)
  • Cleanliness analysis results (particle size, composition)
  • Test reports (8D, PPAP, material certs)

C. Failure Mode Identification

  • Surface failure (honing pattern, wear, scoring)
  • Dimensional failure (out of tolerance)
  • Material failure (crack, corrosion, contamination)
  • Assembly failure (mating, sealing)

D. Root Cause Analysis

  • Use 5-Why or Fishbone diagram logic
  • Distinguish internal vs external causes
  • Check for process drift vs sudden change
  • Verify with data (SPC, correlation analysis)

E. Countermeasures & Verification

  • Short-term containment (sorting, 100% inspection)
  • Long-term corrective action (process change, design change)
  • Effectiveness verification (pilot run, SPC monitoring)
  • Closure criteria definition

2. 8D Report Review Checklist

When reviewing 8D reports from suppliers:

Section What to Check
D1 Team formed, problem severity acknowledged
D2 Problem description with data (quantity, affected lots)
D3 Interim containment actions (sorting, 100% audit)
D4 Root cause identification (why-level 5, verified with data)
D5 Permanent corrective actions selected
D6 Implementation & verification plan
D7 Prevent recurrence (FMEA update, control plan revision)
D8 Team recognition & lessons learned

Red flags:

  • Root cause stated as "human error" without systemic fix
  • Countermeasures not linked to root cause
  • No data supporting root cause conclusion
  • No effectiveness verification plan

3. Key Automotive Quality Metrics

Metric Formula Threshold
PPM Defects per million \x3C 100 PPM typical
CPK Process capability index ≥ 1.33 acceptable
DPMO Defects per million opportunities Track trending
Lot reject rate Rejected lots / total lots \x3C 1% target

4. Common Failure Modes for HPFP/Fuel System Parts

Seizure/Jamming:

  • Insufficient honing pattern (RVK too shallow, angle wrong)
  • Lubrication failure (oil starvation, contamination)
  • Thermal overload (clearance too tight)
  • Material mismatch (surface hardness)

Internal Leakage:

  • Valve seat damage (contamination, wear)
  • Spring failure (fatigue, corrosion)
  • Foreign material embedded in sealing surfaces

External Leakage:

  • Seal damage (installation damage, aging)
  • Connector fitting issues (thread debris, torque)
  • Housing crack (stress concentration)

Performance Degradation:

  • Pressure drop (restricted flow, pump wear)
  • Noise/vibration (bearing failure, cavitation)
  • Calibration drift (sensor issues, contamination)

5. Supplier Quality Assessment

When evaluating supplier capability:

Area Assessment Points
Process Control SPC data availability, Cpk levels, control plan existence
Measurement System MSA results, gauge R&R, calibration records
PPAP Level Documentation completeness (typically Level 3)
FMEA Current version, action prioritization (RPN threshold)
Cleanliness In-process cleaning, particle control, packaging
Traceability Lot tracking, raw material certs, process parameters

6. Report Structure for Quality Analysis

When presenting quality analysis results:

## 质量分析报告

### 1. 问题概述
- 零件信息
- 问题现象
- 影响范围

### 2. 根本原因分析
- 证据链
- 5-Why分析
- 原因验证

### 3. 改善对策
- 短期措施(围堵)
- 长期措施(纠正)
- 实施计划

### 4. 验证结果
- 改善效果
- 后续跟进

### 5. 行动项
| 行动项 | 负责人 | 截止日期 |
|--------|--------|----------|

Reference Files

  • references/qc-tools.md - SPC, MSA, FMEA templates and guidelines
  • references/failure-modes.md - Detailed failure mode library for fuel system components

Load reference files only when specific detailed guidance is needed.

安全使用建议
This skill is an instruction-only reference for automotive quality analysis and appears coherent with its description. Before installing: consider whether you want an agent to use these domain checklists autonomously (default agent invocation is allowed), and avoid providing unrelated credentials to the agent. If you expect the agent to process sensitive customer or supplier data, ensure your environment and data-handling policies are appropriate (the skill itself does not request external endpoints or secrets). If you need stronger assurance, request a provenance/source URL or author contact since the package lists no homepage or known publisher.
功能分析
Type: OpenClaw Skill Name: auto-parts-quality Version: 1.0.0 The skill bundle is a legitimate tool for automotive quality analysis, focusing on 8D reports, failure mode identification, and quality metrics. The instructions in SKILL.md and the reference files (failure-modes.md, qc-tools.md) are strictly domain-specific and contain no evidence of malicious intent, data exfiltration, or unauthorized command execution.
能力评估
Purpose & Capability
The name/description (automotive parts quality analysis) aligns with the content: structured workflows, checklists, SPC/MSA/FMEA guidance, and failure-mode libraries. There are no demands (binaries, env vars, credentials) that are unrelated to this domain.
Instruction Scope
SKILL.md contains only domain-specific instructions and templates (problem definition, evidence collection, 8D checklists, SPC interpretation). It references the included local reference files for detailed guidance and does not instruct the agent to read arbitrary system files, call external endpoints, or exfiltrate data.
Install Mechanism
There is no install spec and no code files beyond the documentation; nothing will be downloaded or written to disk. This is the lowest-risk installation mode and matches the skill type (instruction-only).
Credentials
The skill declares no required environment variables, credentials, or config paths and the instructions do not reference any secrets. No disproportionate access is requested for the stated functionality.
Persistence & Privilege
always is false (default) and autonomous invocation is allowed (platform default). There is no attempt to modify other skills or system-wide configs and no request for permanent presence or elevated privileges.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install auto-parts-quality
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /auto-parts-quality 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release for automotive quality analysis
元数据
Slug auto-parts-quality
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Auto Parts Quality Analysis 是什么?

Senior automotive parts quality analysis expert skill. Use when analyzing quality issues, failure modes, 8D reports, SPC data, PPAP documents, or any automot... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 88 次。

如何安装 Auto Parts Quality Analysis?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install auto-parts-quality」即可一键安装,无需额外配置。

Auto Parts Quality Analysis 是免费的吗?

是的,Auto Parts Quality Analysis 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Auto Parts Quality Analysis 支持哪些平台?

Auto Parts Quality Analysis 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Auto Parts Quality Analysis?

由 zxw8309(@zxw8309)开发并维护,当前版本 v1.0.0。

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