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₹8.2L in scrap last month. Which defect codes? Which lines? Which shifts? Now you see—and act.
Solution Overview
₹8.2L in scrap last month. Which defect codes? Which lines? Which shifts? Now you see—and act. This solution is part of our Productivity domain and can be deployed in 2-4 weeks using our proven tech stack.
Industries
This solution is particularly suited for:
Manufacturing Automotive Aerospace
The Need
A batch of 1,000 units comes off your line. 50 fail inspection. You scrap them. End of story—or so it seems. But that's 5% scrap, which means $15,000-$30,000 per month in lost material and labor. Over a year, that's $180,000-$360,000 in a single facility. And you have no idea why it's happening. Was it the same setup problem last month? A supplier quality issue you could fix? Tool wear on that machine?
When scrap isn't tracked systematically, the same problems repeat. Equipment causes 8% scrap one month, 8% scrap the next month, because you never investigated root cause. Recycling gets handled whenever someone remembers—scrap sits in bins, consuming floor space. You could recover 30-50% of material value through systematic recycling, but you're leaving money on the table. In aerospace and medical device manufacturing, you can't document traceability, which creates regulatory exposure.
The Idea
A Scrap Management System makes every scrap event traceable, trackable, and actionable. When an inspector finds defective material, they scan the work order on their mobile app: "PO-2024-0567, 3 units scrapped." The system instantly retrieves production context: raw materials used, labor costs allocated, total cost per unit. It shows: "3 units = $240 material + $180 labor + $90 overhead = $510 total cost."
Inspectors classify defects by type: tool wear, equipment drift, operator error, material contamination, assembly mistake. The system suggests root causes based on historical patterns: "Tool wear defect code appears 47 times. Most frequent cause: equipment drift (28 times). Second: operator error (7 times)." This consistency reduces guessing.
Scrap is automatically routed for recycling by material type and quality status. Steel goes to metal recyclers, plastic to resin processors, aluminum to the highest-payout recycler. The system tracks which recycler gets paid how much and recovers 30-50% of scrap material value. Dashboards show: "Scrap rate: 3.2% (up from 2.8%), mostly dimensional (45%, indicating tool wear). Tool wear causes 28% of all scrap." This triggers action: adjust tool change schedules, investigate supplier contamination (15% of scrap), or target operator training (8%).
When the same defect code appears 5+ times in a week, the system automatically escalates to quality and triggers a corrective action workflow.
How It Works
flowchart TD
A[Quality Inspection
Detects Defect] --> B[Inspector Logs
Scrap Event] B --> C[Scan Work Order
& Material Codes] C --> D[Select Defect Code
& Root Cause Hypothesis] D --> E[System Calculates
Scrap Cost] E --> F[Display Cost Impact
Material + Labor + OH] F --> G{Route Material
for Recycling?} G -->|Yes| H[Tag Material
by Type & Quality] H --> I[Assign to
Recycling Partner] I --> J[Track Material
in Recycling Bin] J --> K{Bin Full or
Pickup Scheduled?} K -->|Yes| L[Generate Shipment
Manifest] L --> M[Track Recycling
Revenue] M --> N[Update Scrap Cost
with Recovery $] G -->|No| O[Dispose via
Waste Stream] O --> N N --> P[Update Production
Order Status] P --> Q[Trending Analysis:
Scrap Rate Metrics] Q --> R{Defect Pattern
Detected?} R -->|Yes| S[Auto-Create CAPA
Request] S --> T[Management
Investigation] T --> U[Update Preventive
Actions]
Detects Defect] --> B[Inspector Logs
Scrap Event] B --> C[Scan Work Order
& Material Codes] C --> D[Select Defect Code
& Root Cause Hypothesis] D --> E[System Calculates
Scrap Cost] E --> F[Display Cost Impact
Material + Labor + OH] F --> G{Route Material
for Recycling?} G -->|Yes| H[Tag Material
by Type & Quality] H --> I[Assign to
Recycling Partner] I --> J[Track Material
in Recycling Bin] J --> K{Bin Full or
Pickup Scheduled?} K -->|Yes| L[Generate Shipment
Manifest] L --> M[Track Recycling
Revenue] M --> N[Update Scrap Cost
with Recovery $] G -->|No| O[Dispose via
Waste Stream] O --> N N --> P[Update Production
Order Status] P --> Q[Trending Analysis:
Scrap Rate Metrics] Q --> R{Defect Pattern
Detected?} R -->|Yes| S[Auto-Create CAPA
Request] S --> T[Management
Investigation] T --> U[Update Preventive
Actions]
Comprehensive scrap management system capturing defect codes, calculating scrap costs in real-time, routing materials for recycling, and triggering root cause analysis when defect patterns emerge.
The Technology
All solutions run on the IoTReady Operations Traceability Platform (OTP), designed to handle millions of data points per day with sub-second querying. The platform combines an integrated OLTP + OLAP database architecture for real-time transaction processing and powerful analytics.
Deployment options include on-premise installation, deployment on your cloud (AWS, Azure, GCP), or fully managed IoTReady-hosted solutions. All deployment models include identical enterprise features.
OTP includes built-in backup and restore, AI-powered assistance for data analysis and anomaly detection, integrated business intelligence dashboards, and spreadsheet-style data exploration. Role-based access control ensures appropriate information visibility across your organization.
Frequently Asked Questions
Deployment Model
Rapid Implementation
2-4 week implementation with our proven tech stack. Get up and running quickly with minimal disruption.
Your Infrastructure
Deploy on your servers with Docker containers. You own all your data with perpetual license - no vendor lock-in.
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