Find the root cause of metalworking issues in minutes, not weeks.

Visplore helps engineering teams at foundries, presses, rolling mills and machining lines turn scattered process, quality and asset data into clear answers, without writing code or waiting on outside data science support.

Visplore helps identify coil grip failure events during hundreds of coil changes in a rolling process, and a clamping force issue as potential explanation. The changes are extracted and compared automatically, and impact factors are sorted by relevance.

Used by engineering teams across Europe

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“With Visplore, we reduced the time for analyzing years of data from days to 5 minutes”

Troubleshooting in metalworking still takes too long

Casting defects, rolling instability, extrusion issues and tool wear all leave traces in your process data. The data is usually there, in iba or PI. Explaining what happened, and catching it earlier next time, is the hard part.

Dashboards show what, not why

Monitoring tools flag a deviation. Explaining what actually caused it still means digging through thousands of raw process variables by hand.

Root cause analysis across process steps is cumbersome

Tracing quality issues, customer complaints or asset failures back through the whole production chain takes so much effort that the analysis is often not done at all.

Asset issues are detected too late

Gradual degradation of presses, mills, furnaces and drives builds up quietly in the data, and is often only noticed once it causes downtime or scrap.

Three ways engineering teams put Visplore to work

The same platform supports asset management, quality troubleshooting and process optimisation, so teams can start with the problem that matters most and expand from there.

Catch wear and failure before it causes downtime

Asset Management

Model the expected behaviour of presses, mills, furnaces and other critical equipment, then get an early signal when readings drift outside their normal range.

Trace scrap and non-conformities back

Quality Troubleshooting

Compare good and bad batches side by side across process, material and quality data to find what actually changed, rather than guessing.

Find hidden losses in production lines

Process Optimisation

Understand how process parameters affect cycle time, yield and energy use across a line or between sites, and act on what you find.

Further use cases in metalworking

Whether you operate a steel mill, aluminium plant, foundry, forge, extrusion line or machining facility, engineers use Visplore to investigate:

Scrap and quality deviations Rolling mill instability Furnace and reheating optimisation Extrusion defects Die and tool wear Press performance Equipment degradation Unexpected downtime High energy consumption Process variability Throughput losses OEE reduction

See Visplore on your own production data

Book a short demo with our team and bring a real troubleshooting case from your plant.

One workspace to explain quality, process and asset issues

Visplore connects to the systems already running on your shop floor and gives engineers a guided way to investigate deviations themselves, without code and without waiting on IT or data science support.

5 min

from days to minutes

Customers report cutting root cause analysis that used to take days of manual data work down to a few minutes.

IT/OT

One workspace, every source

Connect iba, PI, MES, LIMS and file-based data in one place, without building custom pipelines.

No code

Built for engineers

Guided, visual workflows are designed for process, quality and maintenance engineers, not only data scientists.

On-prem

Data stays on site

Visplore deploys inside your existing infrastructure, so production data never has to leave the plant.

Improve the KPIs that matter

Engineering teams use Visplore to improve measurable production performance, including:
OEE Scrap rate Yield Throughput Energy per ton MTBF (Mean Time Between Failures) MTTR (Mean Time To Repair) CpK

Works with the systems already on your shop floor

Visplore connects directly to historians, databases and files, so investigations start from live production data rather than manual exports. Results feed back into the tools your team already uses.
 

See what Visplore can explain in your data

Tell us a little about your production environment and we will set up a short demo, ideally around a real troubleshooting case from your own plant.

  • 30 to 45 minutes, tailored to metalworking
  • Live analysis on realistic industrial data
  • No preparation needed from your side