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Ignore what you do and listen to the data: how we used big data to start the smart factory process for a gigafactory

man looking at car on a tablet

Who was the client?

A start-up manufacturer of lithium batteries for electric cars.

What was the problem?

The client is based in Europe and, like all battery manufacturers, gets its components from China. Facing higher labour costs and stricter regulations than competitors based in Asia, their competitive advantage lies in one thing only: being much smarter with their data.

What was the Expleo solution?

Agnostic data analysis. This means analysing the client’s manufacturing process data – without thinking about the end result (lithium batteries). By examining the data as pure data, our team were able to extract more surprising insights into performance and process.

How did that help?

By working closely with the client’s R&D team, we were able to share these insights and make recommendations to their data and production teams. These were first deployed in their pilot plant. Then, when the improvements were proven to work, they were quickly scaled to the real plant.

What were the results?

The agnostic data analysis and subsequent recommendations gave the client a far greater understanding of their manufacturing process so they could drastically improve their battery quality, lowering time-to-market, scrap rates, and costs.

It was also the business’s first step in becoming a truly data-led company with a Smart Factory set up. The process solved many of the company’s issues around data cleanliness and quality, setting them up to transition from a traditional battery manufacturing company to become a smart manufacturer.

Could it work for me?

Agnostic data analysis is a worthwhile exercise for most manufacturing businesses as it removes preconceptions and biases, allowing you to see your data afresh. It’s a particularly effective technique for businesses that have a lot of data but currently don’t know how to use it to drive innovation and progress.

It’s also a crucial first step in moving towards a Smart Factory. By getting your data ready for analysis to innovate in one area, you lay the groundwork for an operation where every piece of technology and every process generates useful insights that can help you get to what you need more quickly.

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