How do you turn all that raw manufacturing data into real business value? And how do you ensure true collaboration between teams to make the most out of the data collected?
Momentum Talks is a show about Smart Factories. In this episode our panel of experts dive into one of the most valuable resources in manufacturing, data. Watch the full episode below or read our recap of Momentum Talks and watch the corresponding highlights!
This episode of Momentum Talks is hosted by Sarah Wickbers. The guests in this episode are:
José Figueroa, Atlas Copco
Marie Jonsson, Linköping University
Jannik Henser, Scania
When does data become valuable?
In manufacturing, data only becomes valuable when it’s actively used, not just when it’s collected and stored. Its power emerges when everyone from engineers to operators to managers share a common understanding of its purpose and how best to yield it. Thus, it is when the data is given a context that informed decisions can be taken. As Jannik Henser from Scania points out, dispersed or siloed information is difficult to act on. And that’s why data integration matters. When data is connected across systems, decisions become smarter, guesswork is reduced, and surprises on the production floor are minimized.
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Unlocking potential with data
The possibilities of data in manufacturing extend far beyond operational insight. Companies can leverage data to become more sustainable and energy-efficient, aligning business performance with environmental responsibility. Today, machines generate vast amounts of information from vibrations to temperature to torque, but modern AI tools, large language models, and machine vision can extract even deeper insights like engineering details, assembly routines, and more. Depending on the use case, focusing on data can yield gains from modest two-percent improvements to double-digit boosts.
José Figueroa from Atlas Copco emphasizes the power of incremental change: small improvements at each operation may seem minor, but when multiplied across the entire production line, the effect is transformative. To achieve these compound gains, companies must treat data adoption as a transformational journey, starting with small, achievable steps and building toward higher efficiency to generate long-term impact.
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Taking the first step
Getting started requires a clear framework. Companies can reflect on three essential pillars: digital infrastructure, robust data structure, and data analytics. First, digital infrastructure refers to the right sensors, connectors, and networks to integrate systems seamlessly. Second, a strong data structure ensures information is stored efficiently, connected to products, and accessible for real-time insights. Third, data analytics combines traditional physics-based models with AI-driven approaches such as large language models to generate clarity.
Whilst building a data driven approach Marie Jonsson from Linköping University reminds us, sustainability should be a consideration. Data centres consume significant energy, while AI tools drive additional demand for storage, cooling, and processing, expanding the overall footprint.
In light of these considerations and the rapid pace of technological development, companies should prioritize critical applications first, set clear goals, and plan sustainably for the long term. After all, manufacturing involves thousands of simultaneous processes, and clarity at the outset is essential.
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The promise of data in manufacturing
The ultimate promise of data lies in continuous improvement. At Atlas Copco, José Figueroa highlights how tools capture and transmit operational data to servers, helping customers make smarter, data-driven decisions. Over time, incremental improvements to processes, like the tightening process, compound and have the potential to transform production lines.
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Key takeaways to leverage data in manufacturing
Data is a completive advantage waiting to be unlocked
Deciding who owns the data is crucial
And get all on board and adapt your processes to implement the change
