Case Study: Plywood Manufacturing ERP Transformation
How a ₹42 Cr plywood manufacturer gained real-time production visibility and reduced wastage using a custom AI-driven ERP on Odoo.
🏭 The Client
A third-generation plywood manufacturing business based in Gujarat, operating two production lines with hot press and cold press operations. The company supplies across Western India and had grown steadily but relied heavily on manual processes like registers, Excel sheets, and verbal communication.
⚠️ The Challenge
Wastage was tracked only at month-end, making it impossible to identify root causes or take corrective action in time.
Stock was tracked by thickness but not by grade (MR, BWR, BWP), leading to frequent dispatch errors and rechecks.
Accounts were always 24–48 hours behind due to manual data entry from production registers.
Procurement relied on guesswork, causing overstocking or sudden shortages.
⚙️ The Solution
A custom-built ERP on Odoo with a strong production module and AI analytics layer tailored specifically for plywood manufacturing workflows.
- ✔ End-to-end production tracking from log intake to finished goods
- ✔ Real-time wastage calculation at every stage
- ✔ Grade, thickness, and size-based inventory tracking
- ✔ Fully integrated accounting, purchase, and sales workflows
- ✔ AI-powered analytics for wastage, forecasting, and yield prediction
🔧 Key Components
Each log tracked with lot numbers, species, and yield monitoring across peeling and drying stages.
Hot press, cold press, gluing, trimming, and grading fully digitised with real-time data capture.
Identifies inefficiencies by machine, operator, shift, and raw material quality.
Finished goods tracked precisely by grade, thickness, and size for accurate dispatch.
2-week raw material forecasting and yield prediction for better planning.
📊 Implementation Timeline
| Phase | Duration | Delivery |
|---|---|---|
| Odoo Foundation Setup | 4 weeks | Inventory, accounting, purchasing, sales configuration |
| Custom Production Module | 4 weeks | End-to-end manufacturing workflow digitisation |
| AI Analytics Layer | 3 weeks | Wastage detection, forecasting, yield prediction |
| Training & Deployment | 3 weeks | On-floor training, phased go-live, support |
Total Go-Live Time: 11 Weeks
📈 Results (After 6 Months)
Improved yield from 49.5% to 54.1%, saving ₹12–15 lakh per month.
Reduced from 7 days to just 2 days with real-time accounting integration.
Errors reduced from 12–15/month to just 2 in 6 months.
2-week forecasting eliminated production stoppages due to raw material shortages.
Owner gained daily visibility into production, wastage, and efficiency metrics.