What is Cutting Optimisation in Steel Manufacturing?

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Every day, somewhere in a steel stockholder or long products manufacturer, someone is staring at a whiteboard or a spreadsheet trying to figure out how to cut this week’s orders from the stock on the rack.

They’re asking: which bars do I use? How do I cut them so I don’t end up with a skip full of short pieces I can’t sell? How do I get everything shipped without ordering more stock than I need?

This is the cutting stock problem. It’s been studied by mathematicians for decades. It’s one of the problems that computers solve far better than humans. And solving it well is worth real money.

What is Cutting Optimisation?

Cutting optimisation (also called cut plan optimisation or cutting stock optimisation) is the process of calculating the most efficient set of cuts to make from a set of stock lengths in order to fulfil a set of customer orders — while minimising the material left over as scrap or off-cut.

It’s a class of mathematical problem called the cutting stock problem — a type of combinatorial optimisation. In plain English: given the bars you have in stock and the lengths your customers need, what’s the best way to cut them?

“Best” means different things in different contexts:

Minimum waste (scrap by weight or length)
Minimum number of bars used (fewer saw cycles, lower labour)
Maximum use of existing remnants (reducing the need to open new stock)
A combination of all three, weighted by what matters most to your business

Why Humans Can’t Solve It Optimally by Hand

The cutting stock problem is NP-hard. You don’t need to know what that means mathematically, but the practical implication is important: as the number of order lines and stock lengths increases, the number of possible cutting combinations increases exponentially.

A simple example: three order lines against one bar length might be manageable. Try 30 order lines against 6 different stock lengths, with multiple bars available of each, and the number of possible combinations runs into the millions. No human can evaluate all of them. No spreadsheet is designed for it.

What actually happens in practice:

The saw operator uses experience and instinct to build a cut list
They usually start with the longest pieces and work downwards — a heuristic, not an optimum
They get a workable result, but rarely the best possible result
Offcuts accumulate in the rack, and no one is quite sure what to do with them

The gap between “workable” and “optimal” is where money disappears. In high-volume long products manufacturing, that gap can be significant.

What Scrap Savings Look Like in Practice

Numbers make this concrete.

Say you process 500 tonnes of steel bar per month. If your current cut planning produces 4% scrap, you’re throwing away 20 tonnes of steel every month. At £600 per tonne, that’s £12,000 per month — or £144,000 per year — going in the skip.

Optimised cut planning typically reduces scrap by 1–3 percentage points on comparable order profiles. At 1.5 percentage points, you recover 7.5 tonnes of steel per month. That’s £4,500 per month you were previously writing off.

Midland Steel achieved a 50% reduction in scrap after implementing the GoSmarter Cutting Optimiser. The saving wasn’t marginal — it fundamentally changed the economics of their operation.

The scrap reduction benefit compounds. Less scrap means:

Fewer raw material purchases (you’re getting more output from the same input)
Lower disposal costs (skip hire, transport, processing)
Better margin on every order

How Optimised Cut Planning Differs from a Manual Cut List

A manual cut list typically looks like this: someone lists the required lengths in descending order and assigns them to bars, moving to the next bar when the current one can’t fit the next piece. This is called the First Fit Decreasing heuristic. It’s the instinctive approach most people use.

It’s not bad. It’s just not optimal. It tends to produce more waste than necessary because it doesn’t consider the full combination of available lengths and order quantities simultaneously.

An optimised cut plan considers:

All order lines at once, not sequentially
Multiple stock lengths simultaneously
Existing remnants and off-cuts in the rack
The relative cost of different scrap patterns
Constraints like bar type, grade, and heat number (where orders require specific material)

The result is a cut list that may look counterintuitive — cutting shorter pieces first, or using a specific bar that seems inefficient in isolation — because it’s been calculated to minimise waste across the entire batch.

What Types of Material Cutting Optimisation Works For

Cutting optimisation applies to any material that is processed in linear lengths:

Steel bar (round, square, flat, hexagonal)
Structural sections (angle, channel, universal beam, universal column, RSJ)
Hollow sections (rectangular hollow section, circular hollow section, square hollow section)
Rebar (reinforcing bar, cut to schedule)
Tube (steel, stainless, aluminium)
Aluminium extrusion (in architectural and engineering applications)
Any other linear material cut to order from stock lengths

It’s specifically suited to long products — the cut-to-length, bar and section world. Flat products (plate, sheet, coil) involve a two-dimensional nesting problem, which is a related but different class of optimisation.

How the GoSmarter Cutting Optimiser Works

GoSmarter Cutting Optimiser takes your open order lines and your available stock as inputs. It calculates the optimal cut plan — telling your saw operator exactly which bars to pull, in what sequence to cut them, and what lengths to produce.

The process:

Orders come in. The system reads the required lengths, quantities, grades, and any certification requirements.
The system checks available stock — including remnants and off-cuts already in the rack.
The optimisation engine calculates the cut plan that minimises waste across all open orders.
The cut list goes to the saw. The operator follows it. The offcuts are automatically recorded back into inventory with their heat number and cert link intact.

The system accounts for saw kerf (the material lost per cut), stock length tolerances, and minimum remnant thresholds (what’s worth keeping versus scrapping).

FAQ

Is cutting optimisation only useful for large operations?

No. The relative benefit of optimisation is consistent regardless of volume — you’re always reducing waste as a percentage of input. But the absolute pound value of savings scales with throughput. Even a smaller service centre processing 50–100 tonnes per month will see meaningful scrap reduction. The GoSmarter Cutting Optimiser is built for SME manufacturers, not just large operations.

What's the difference between a cut plan and a cutting schedule?

A cut plan (or cut list) specifies which bars to cut and what lengths to produce from each. A cutting schedule sequences that work across time — which orders get cut first, which saw handles which material type, and so on. Cutting optimisation primarily refers to the cut plan: the mathematical problem of how to cut. Scheduling is a secondary layer on top.

Can cutting optimisation handle multiple grades or specifications on the same order batch?

Yes. The optimiser handles grade, size, and certification constraints. It will not suggest substituting a lower-grade material for a higher-grade order requirement. Each order line’s material constraints are respected — the optimisation is done within those constraints, not by relaxing them.

What happens to the off-cuts?

Off-cuts above a minimum useful length threshold are recorded back into stock automatically with their original heat number and cert link. They become available for future orders that require shorter lengths. Off-cuts below the threshold are logged as scrap. Over time, the system learns the typical off-cut profile for your order mix and the optimiser factors this into future cut plans.