Quality Defect Investigation Digital Worker
Implements a 5-agent ReAct (Reasoning + Acting) pattern system that processes defect images, classifies defect types, performs systematic root cause analysis with hypothesis testing, generates corrective actions, and validates recommendations—all with real-time reasoning transparency and IoT sensor integration..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
AI Credit Engine Dashboard overview showcasing intelligent quality control system with expected business impact metrics and three-stage quality analysis workflow
Quality analysis configuration page displaying multi-agent architecture with orchestrator, vision analyzer, root cause investigator, and validation agents using LangGraph pattern
Real-time agent orchestration view showing AI agents collaborating with chain-of-thought reasoning, tool activity, and defect classification analysis in progress
Comprehensive analysis results presenting defect identification, root cause determination, financial impact assessment, and actionable recommendations with high confidence scores
AI Agents
Specialized autonomous agents working in coordination
Orchestration Agent
Quality investigations require coordinated analysis across vision, data, and domain expertise. Ad-hoc coordination leads to incomplete investigations.
Core Logic
Manages the investigation workflow using task decomposition and priority-based agent coordination. Routes defect cases to appropriate specialist agents based on defect type and severity. Maintains investigation state and ensures all evidence is collected before conclusions. Handles escalation to human experts when confidence thresholds are not met. Tracks investigation SLAs and prioritizes based on production impact.
Vision Analyzer Agent
Visual defect identification requires trained inspectors and is subject to fatigue and inconsistency. New defect types may go unrecognized.
Core Logic
Processes defect images using convolutional neural networks trained on manufacturing defect taxonomies. Classifies defects into categories (surface, dimensional, structural, contamination) with confidence scores. Detects defect features including location, size, pattern, and severity. Identifies similar historical defects using image embedding similarity search. Flags novel defect patterns for human review and model retraining.
Root Cause Analyst Agent
Identifying true root causes requires systematic hypothesis testing against process data. Engineers often fix symptoms rather than causes, leading to recurrence.
Core Logic
Performs systematic root cause analysis using Ishikawa (fishbone) methodology across 6M categories (Man, Machine, Material, Method, Measurement, Mother Nature). Correlates defect occurrence with process parameter deviations using statistical analysis. Tests hypotheses against historical data patterns and sensor readings. Ranks contributing factors by evidence strength and causal probability. Documents evidence chains supporting conclusions.
Strategy Agent
Corrective action planning often focuses on quick fixes without considering cost-effectiveness, implementation feasibility, or long-term prevention.
Core Logic
Generates tiered action plans: immediate containment, short-term correction, and long-term prevention. Calculates Cost of Poor Quality (COPQ) including scrap, rework, inspection, warranty, and reputation costs. Assesses implementation feasibility based on resource availability and production constraints.
Validation Agent
Recommended actions may be technically infeasible, violate constraints, or introduce new risks. Without validation, implementation fails or creates new problems.
Core Logic
Validates proposed actions against production constraints, equipment capabilities, and safety requirements. Checks for unintended consequences using process simulation and FMEA analysis. Verifies action feasibility with current resource levels and schedules. Confirms regulatory compliance for process changes. Assigns confidence scores to validated recommendations and flags items requiring engineering review.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
6 technologies
Architecture Diagram
System flow visualization