P-FMEA Process Failure Mode and Effects Analysis
With systematic risk prevention as the core, identifying potential failure risks throughout the production process, quantifying risk root causes, proactively avoiding quality defects and operational losses.
Core Advantages
AIAG-VDA Standard Compliance
Strictly comply with AIAG-VDA standards, with scoring logic, format, and processes all compliant. Versions, changes, and rectification records are fully traceable.
Shorten Project Cycle
Reuse historical database and template data to shorten FMEA preparation cycle, intelligently lighten preparation, and significantly reduce costs and improve efficiency.
Continuous Experience Accumulation & Reuse
Form an enterprise-specific knowledge base, intelligently recommend and one-click reuse for new projects, get rid of dependence on senior engineers' personal experience, and realize quality experience capitalization.
Full Lifecycle Closed-loop Management
From risk identification, analysis and evaluation, measure formulation, task follow-up to verification closure, the whole process is managed in a closed loop, making risks truly controllable.
PFMEA & Control Plan Linkage
Process failure analysis and control plan data are interconnected, changes in one place are synchronized to multiple places, significantly reducing repetitive work.
Open Integration Capability
Supports seamless integration with PLM, MES, ERP, 8D quality systems, synchronizes process, production, and defect data, enabling on-site issues to drive FMEA updates.
Application Scenarios
FMEA Analysis + Report
Simple FMEA analysis and report generation
FMEA + Control Plan
Quality risk management for SMEs
All Functional Modules
Complete quality management system
Pain Points & Solutions
Pain Point
Manual Excel preparation, scattered files, version chaos, difficult data traceability
Inconsistent analysis standards, subjective scoring, non-standard descriptions, uneven quality
Tedious offline cross-department communication, disconnected DFMEA and PFMEA, low collaboration efficiency
Engineer experience is difficult to retain, historical cases cannot be reused, repeated quality problems
Difficult to match the new AIAG-VDA standard, non-compliant audits, tedious data organization
Risk measures are only recorded on paper, cannot track implementation, difficult to form closed-loop management
Solution
Unified data management, full version tracking, permission control, true data traceability
Built-in standard vocabulary and scoring rules, unified analysis standards, reducing human bias
Online collaborative work, module data linkage flow, improving cross-department collaboration efficiency
Build enterprise quality knowledge base, one-click reuse of historical cases, accumulate professional experience
Native adaptation to the latest standards, following seven-step process, one-click generation of compliant reports
Full-process task tracking, progress warning, achieving closed-loop management of risk measure implementation
Product Features
FMEA Analysis
Includes seven-step analysis, structure tree, structure diagram, flow chart and other modules
Risk Assessment
Includes SOD scoring, AP/RPN calculation, risk matrix and other modules
Control Plan
Includes control plan preparation, approval process, execution tracking and other modules
AI Data Recommendation
Based on historical data and knowledge base data, AI intelligently recommends required data
Knowledge Base
Includes experience base, function base, failure base, measure base and other modules
Data Security
Includes on-site document encryption, watermark settings, operation logs and other modules
Technical Architecture
Adopts SpringBoot3 + Vue3 frontend-backend separation architecture, supporting both One-click Local Deploymentand Kubernetes Containerized Cluster Deploymentdeployment methods. Built-in distributed task scheduling capability supports high-concurrency, scalable, and easily maintainable business scenarios.
Technical Components
Frontend: Vue3, TypeScript, ElementPlus
Backend: SpringBoot3, Redis, MinIO, Docker
Database: PostgreSQL
Workflow: Drag-and-drop workflow designer, supporting complex logic like conditional branches, parallel processing
Security & Permissions: Data source level, page level, operation level
Deployment Methods
Local Deployment
Private cloud or local server deployment, data security is controllable
Hybrid Deployment
Key data deployed locally, non-critical data stored in cloud