Why Industry 4.0?

Maximising revenue while minimising risks and costs requires accurate and consistent decision making. Turning operating data into information for better decisions can deliver substantial commercial and competitive advantage. Digitalisation is increasing the effectiveness and efficiency of our processes by collecting quality data, turning this data into insights and insights into actions that improve our business performance.

In Shell we are aggregating data from diverse sources, using AI, machine learning and machine vision enables us to make better decisions, realising competitive advantage. In our operations, digitalisation makes it possible to anticipate and autonomously manage conditions, to maintain optimised asset performance. This has the potential to transform maintenance, operational productivity, improve safety and reduce emissions.

Across our operations, we have been collecting real-time data for decades. At present, more than 10 million operational variables per minute are collected, streamed, archived, integrated with operational control systems. There is a huge potential to exploit this data further.

Industry 4.0 Examples

  • Engineers reviewing data at control station

    Predictive Maintenance

    When process equipment at Shell facilities malfunctions, the cost of production loss is significant. Predictive Maintenance enables us to leverage over a trillion data points through machine learning to detect anomalies. Machine learning and predictive analytics cut waste and enhance process safety by predicting potential malfunctions of critical equipment, which allows preventive actions. The initial predictive maintenance applications for valves and compressors are now deployed at scale across the world. Leveraging this experience, combined with Shell’s deep in-house statistics knowledge and a market leading cloud platform, we are able to deliver insight across a growing number of equipment classes and locations.

    Download paper

  • Engineers reviewing data on a ruggedized mobile device

    Connected Field Worker

    Frontline workers are being equipped with mobile and wearable devices, such as tablets and helmets. These are used on a real-time basis to raise notifications, engage with offsite experts for over the shoulder coaching, communicate with support for status of equipment and tools, etc., improving safety, efficiency and resulting in faster, better decision making. Providing staff with the digital mobile capability to execute tasks in the field and being able to understand and relate the work they do through real-time asset performance, is both a key productivity enabler and asset performance improvement lever.

  • Engineers reviewing data at a control station

    Real Time Production Optimisation (RTPO)

    We use AI to optimise asset performance. For instance, our real-time production optimisation program marries the state of art engineering capability with the insights from data. In addition, it provides a digital product to enable asset engineers to sustainably execute data driven trouble shooting and decision making. This means that we are optimising how we work, while we work.

    You can compare RTPO to the satellite navigation in your car. Like Google Maps helps you find the quickest or most economic route by taking in external and internal data, RTPO helps engineers to see the how to close the gap to potential with current or additional handles. It takes information from sensors like pressure, temperature and flow rates and then calculates the optimum setting. At the same time, it handles operational, economic and engineering constraints.

    In addition, when the actionable insights are brought into the continuous closed loop process control layer, it acts like an self-driving car, autonomously optimising optimum production each minute. Currently it is primarily used in LNG assets. At the heart of every LNG plant is the refrigeration unit – this is basically a chiller, like your domestic refrigerator, but driven by a gas turbine bigger than engines used on commercial planes. Continually optimising this process under changing weather conditions, allows us to squeeze out an additional few percent of LNG production – effectively for free.

  • Engineer in a warehouse using mobile device to manage stock

    Inventory Optimisation

    For safety, Shell assets all need spare parts to be available at short notice so that maintenance teams can rapidly deal with any issues. Shell carries a huge safety stock of material assets, such as subsea facility equipment and pipeline parts. Parts are bespoke/niche and the usage patterns are complex. Our assets require large, expensive parts that take a long time to build and deliver. We apply AI to historical inventory data to optimise inventory stock levels. The solution has been deployed to the vast majority of Upstream, Manufacturing and Integrated Gas sites globally providing improved stock level recommendations – supporting inventory analysts to make informed choices regarding the amount of inventory to hold.

  • Engineers reviewing data on a ruggedized mobile device

    Digital Twin

    A digital twin is the virtual representation of the physical elements of an asset and its dynamic behaviour over the asset lifecycle. This goes well beyond creating a 3D model of the asset. A digital twin integrates how we operate, maintain and inspect our asset, recreated in a virtual and digitalised world. This enables a range of efficiency and production improvements whilst reducing safety exposure. We can simulate real conditions and apply the outcomes to help us prepare and schedule maintenance work, inspections, do proactive interventions and so forth.

    Find out more about digital twin in Nyhamna Gas Processing Hub



Digital technologies such as robotics and machine vision increase efficiency and make it possible to keep people out of harm’s way.

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