Production Planning
Production Planning for Metals Manufacturers
The plan is always wrong by lunchtime. Jobs change. Material isn’t where the spreadsheet said it was. A customer calls to move their order forward. And you’re trying to reroute four jobs in your head while three machinists wait for instructions.
That is the production planning problem in metals. It is not a capacity problem. It is a data problem. The plan fails because it was built on yesterday’s stock figures, last week’s job list, and a schedule that hasn’t been updated since Tuesday.
Artificial Intelligence (AI) scheduling closes that gap. Real-time data from your inventory, your machines, and your order book feeds directly into the plan. When material changes, the plan updates. When a job slips, you see the knock-on effects before the shift starts.
Posts in this section cover:
- Production scheduling tools and workflows for metals operations
- AI-driven capacity planning: what works and what doesn’t
- Cut planning and material allocation to reduce scrap
- Linking stock visibility to the live production plan
- How to stop losing hours every day to manual replanning
Cutting Plans is GoSmarter’s cut optimisation tool. It generates cutting patterns that minimise offcut waste. Your current stock and today’s order list drive every decision. Metals Manager gives you the live inventory picture that makes every plan trustworthy.
Know what’s in the yard. Know what’s on the schedule. Plan once and mean it.
How AI Optimises Steel Production Processes
- Ruth Kearney
- Blog , Learning
- Jan 8, 2026
- Updated
How AI reduces waste and costs in steelmaking: boosting yields, predicting equipment failures, optimising energy use and production schedules.
Read More: How AI Optimises Steel Production ProcessesSmart Cuts, Less Scrap: A 1D Cutting Stock Problem
- Ruth Kearney
- Blog , Case studies
- Aug 21, 2025
- Updated
In rebar manufacturing, scrap directly impacts profitability and sustainability, making efficient production essential. Mathematical optimisation, particularly the 1D Cutting Stock Problem, helps minimise waste by determining the most efficient way to cut raw steel bars into required lengths while reducing leftover material.
Read More: Smart Cuts, Less Scrap: A 1D Cutting Stock ProblemCategories
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