The Industrial Challenge · Why melt condition matters in aluminium processing | DIGI-HSMC

THE INDUSTRIAL CHALLENGE

Why melt condition matters in aluminium processing

Melt quality is a significant driver of scrap, re-melting and unpredictable process performance for SME foundries. Many smaller foundries rely heavily on operator judgement rather than measured melt data, creating limited visibility into what is happening within the melt.

01 · CONTEXT

The industrial challenge in context

The documented challenge is not limited to the melt itself. It extends across melt quality, process uncertainty, furnace holding time, re-processing, scrap and rework, and the energy and operational cost that follow.

INDUSTRY CONTEXTNOT DIGI-HSMC RESULTS Source: DIGI-HSMC project documentation
Scrap rates
5–15%
Energy as a share of total production costs
20–30%
Potential annual loss for a typical SME processing 1,500–2,000 tonnes of aluminium per year through scrap, rework and avoidable furnace time
£150,000–£300,000
Increase in furnace operating costs since 2021
40%

These figures describe the wider industrial context. They are not outcomes achieved or measured by DIGI-HSMC.

02 · LOSS CASCADE

How melt variability becomes cost

When melt condition cannot be observed directly, uncertainty is carried forward. Each stage adds furnace time, material and energy to the process.

LOSS CASCADE CONCEPTUAL · NO VALUES SHOWN
  1. STAGE 1 · PHYSICAL Melt variability Feedstock, composition and melt history vary between batches.
  2. STAGE 2 · INFORMATION Process uncertainty Melt condition is hard to observe, so decisions rely on operator judgement.
  3. STAGE 3 · FURNACE Longer holding / re-processing Uncertainty is managed conservatively at the furnace.
  4. STAGE 4 · CASTING Scrap / rework Defects that are not prevented are found after casting.
  5. OUTCOME Energy & cost burden Furnace time, energy and material accumulate across the process.
  1. STAGE 1 · PHYSICALMelt variabilityFeedstock, composition and melt history vary between batches.
  2. STAGE 2 · INFORMATIONProcess uncertaintyMelt condition is hard to observe, so decisions rely on operator judgement.
  3. STAGE 3 · FURNACELonger holding / re-processingUncertainty is managed conservatively at the furnace.
  4. STAGE 4 · CASTINGScrap / reworkDefects that are not prevented are found after casting.
  5. OUTCOMEEnergy & cost burdenFurnace time, energy and material accumulate across the process.
Physical and process burden Information and process visibility

03 · CHALLENGE AREAS

Three connected challenges

The industrial challenge can be understood through three connected areas of melt processing.

01

MELT QUALITY & CASTING DEFECTS

Casting quality can be influenced by the condition of the melt before it reaches the mould.

Factors that can affect aluminium casting quality include:

  • Oxide films
  • Dissolved gases
  • Solid inclusion clusters
  • Melt inhomogeneity

These factors can contribute to porosity, inclusion-related defects and inconsistent mechanical properties.

02

ENERGY, FURNACE TIME & COST

Process uncertainty can carry a cost at the furnace and beyond.

When melt condition is uncertain, it can contribute to longer furnace holding, re-melting, additional energy use and higher operational cost.

PROJECT TARGET 10–20% reduction in furnace holding time. Target, not yet a verified DIGI-HSMC result.
03

SCRAP VARIABILITY & CIRCULARITY

Variable feedstock makes consistent melt processing harder.

Recycled and secondary aluminium feedstocks can vary from batch to batch. That variability carries into melt condition and makes consistent, resource-efficient processing more challenging for recyclers and secondary producers. This reinforces the need for real-time visibility into melt condition.

04 · PROCESS CONTEXT

Existing approaches to melt treatment

Several established process categories are used to treat aluminium melts. Each addresses particular aspects of melt quality.

Rotary degassing
A rotating impeller disperses inert gas through the melt to reduce dissolved hydrogen.
Flux injection
Treatment fluxes are introduced to help separate oxides and inclusions from the melt.
Inert-gas / lance injection
Inert gas is introduced through a lance to support degassing and melt cleaning.
Mechanical stirring
Agitation helps homogenise melt temperature and composition.
Melt filtering
Filters capture inclusions as the melt flows toward the mould.
IDENTIFIED GAP

Existing approaches can address aspects of melt treatment, but the project identifies a lack of continuous real-time visibility into melt condition as an important unresolved challenge.

05 · THE RESPONSE

The challenge creates a need for better process visibility

DIGI-HSMC is developing an integrated approach that combines High-Shear Melt Conditioning with sensing, monitoring and a physics-informed digital twin.

PHYSICAL Physical Melt Conditioning
INFORMATION Sensing & Monitoring
DIGITAL Physics-Informed Digital Twin
ONE INTEGRATED SYSTEM Explore the Technology →

EVIDENCE MATURITY ON THIS PAGE

The Challenge page describes documented industry context and the problem the project is addressing. It should not be interpreted as evidence of achieved DIGI-HSMC performance.

  • INDUSTRY CONTEXTUsed: section 01
  • PRIOR RESULTNot used
  • PROJECT TARGETUsed: section 03, challenge 02
  • VERIFIED DIGI-HSMC RESULTNone yet

Explore the technology response

Discover how DIGI-HSMC brings physical melt conditioning, process sensing and a physics-informed digital twin into an integrated system.