Predictive Component Obsolescence System
Orchestrates seven specialized AI agents that continuously monitor market signals, analyze component lifecycle data, assess revenue and supply chain impact, identify pin-compatible alternatives, simulate disruption scenarios, and generate autonomous recommendations with migration roadmaps..
Problem Statement
The challenge addressed
Solution Architecture
AI orchestration approach
Analysis Input - Select components and configure risk threshold parameters
Agent Orchestration - Live visualization of inter-agent communication and analysis
Risk Assessment - Component lifecycle predictions with EOL probability scoring
Migration Roadmap - Alternative components and transition planning recommendations
AI Agents
Specialized autonomous agents working in coordination
Data Collector Agent
Obsolescence analysis requires aggregating data from multiple internal systems (PLM, ERP, inventory) and external sources (distributors, manufacturers).
Core Logic
Executes database queries against internal systems to retrieve component usage, BOM structures, and inventory positions. Calls external APIs for distributor stock levels, manufacturer lifecycle status, and pricing trends. Normalizes data from disparate sources into unified component profiles.
Market Intelligence Agent
Early warning signals of obsolescence appear in market data (inventory decline, price increases, EOL announcements) that are difficult to monitor manually.
Core Logic
Monitors distributor inventory levels, tracks pricing trends across sources, scrapes manufacturer websites for EOL announcements, analyzes industry news for supply chain disruptions, and generates market signal alerts with severity ratings and affected component lists.
Risk Analyzer Agent
Component risk depends on multiple factors (supply, demand, technology trends, manufacturer health) that must be weighted and combined into actionable scores.
Core Logic
Calculates multi-factor risk scores incorporating supply indicators, demand patterns, technology obsolescence curves, and manufacturer financial health. Uses ML inference to predict EOL probability and timing, generates risk trend analysis, and identifies risk factor contributions for prioritization.
Impact Assessor Agent
Understanding business impact of component obsolescence requires tracing through BOMs to affected products, programs, and revenue streams.
Core Logic
Traverses bill-of-materials to identify all products using at-risk components, calculates revenue exposure by product and customer, assesses field population and spare parts demand, quantifies last-time-buy costs, and generates financial impact summaries with NPV analysis.
Solution Architect Agent
Finding suitable replacement components requires evaluating pin compatibility, electrical specs, form factor, certifications, and lifecycle viability.
Core Logic
Searches component databases for functional equivalents, evaluates technical fit across electrical, mechanical, and thermal parameters, assesses pin/code compatibility scores, verifies certification status, compares pricing and lifecycle outlook, and ranks alternatives with migration complexity ratings.
Recommendation Engine Agent
Translating analysis into actionable recommendations requires synthesizing inputs from all agents and balancing cost, risk, and resource constraints.
Core Logic
Generates prioritized recommendations categorized as immediate actions, strategic initiatives, and contingency plans. Creates detailed migration roadmaps with phases, timelines, budgets, and resource allocations. Identifies quick wins and long-term strategies aligned with business priorities.
Autonomous Decision Agent
Some obsolescence responses (emergency purchases, stakeholder notifications) require rapid action that cannot wait for manual review cycles.
Core Logic
Evaluates trigger conditions for autonomous actions based on risk thresholds and urgency. Proposes actions with full reasoning chains and confidence scores. Supports configurable autonomy levels from fully autonomous to human-in-loop approval. Executes approved actions and logs outcomes for continuous learning.
Worker Overview
Technical specifications, architecture, and interface preview
System Overview
Technical documentation
Tech Stack
7 technologies
Architecture Diagram
System flow visualization