Rod-Length Optimisation & Scenario Planning
PuLP-based optimisation tool translating manufacturing constraints into deterministic cutting recommendations, contributing to an estimated 15% material reduction.
Overview
Developed a production-ready optimisation tool for rod cutting plans on a manufacturing floor, then extended it with scenario planning capabilities and a web interface for engineering users.
Problem
Rod stock must be cut to specific lengths for product assembly. Suboptimal cutting patterns generate excess waste. The planning was previously done manually, making it difficult to evaluate alternatives systematically.
Approach
Phase 1 — Optimisation core
The cutting-stock problem was formulated as an integer linear programme and solved with PuLP. Constraints encoded:
- Available rod lengths and stock quantities
- Required output lengths and quantities
- Minimum waste thresholds per cut pattern
The solver produces a deterministic, reproducible cutting plan with a clear objective: minimise total waste.
Phase 2 — Scenario planning
Extended the tool with a scenario comparison module: users can evaluate whether purchasing rods of different lengths reduces overall cost for specific product variants. Break-even analysis and cost comparisons are computed automatically.
Phase 3 — Web interface
A Streamlit and later Flask interface made the tool accessible to engineering users without requiring Python knowledge. Results are displayed as tables and downloadable reports.
Results
Contributed to an estimated 15% material reduction. The tool was adopted by the engineering team and used in regular production planning cycles.
Limitations
The model assumes deterministic demand. Stochastic demand or supplier variability would require a reformulation.