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How Big Data Can Make Manufacturers More Efficient and Sustainable

Updated: Mar 8, 2022

Big data has been a key part of the current wave of manufacturing and industrial advances known collectively as Industry 4.0. In fact, experts predict that the global market for big data analytics in the manufacturing industry is headed towards being worth $4.5 billion by 2025 – a momentous leap from $904.6 million in 2019. The reasons for this massive growth are simple: big data analytics is paving the way for manufacturers to achieve peak efficiency and long-term sustainability. So how can you leverage big data to make your own manufacturing operations better?

Predictive Maintenance

Big data analytics allows manufacturers to have full purview of the numbers behind their operations in order to make better business decisions. In manufacturing, one of the earliest applications of this process is predictive maintenance. Through the use of sensors and connected devices, plant managers can instantly determine the status of their manufacturing equipment, which enables them to identify and address any maintenance issues more quickly. Apart from preventing minor issues from ballooning into major and more costly ones, the continuous application of big data for predictive maintenance can also prolong the service life of essential equipment and ensure consistently efficient operations. Used correctly, predictive maintenance can improve a manufacturer’s operational efficiency, which in turn also translates to greater overall business sustainability.

Digital Twin Technology for Better Product Design and Employee Training

Manufacturers can also use big data analytics in order to improve both their product design and their employee training methods. The key to these applications is called digital twin technology, wherein an exact replica of a physical object is created in the digital world. Rather than being a static digital copy, this digital twin can consistently mirror the capabilities and conditions of its physical counterpart, which is possible thanks to the collected data of the aforementioned sensors and connected devices used in manufacturing today. Apart from its obvious applications in predictive maintenance, a digital twin can also be used to assess the performance of any new products and test it against future scenarios. From lowering product testing costs to filling gaps in product design, digital twin technology can help futureproof products. Furthermore, the same technology can also benefit employee training in similar ways. Using the digital twins of essential manufacturing equipment, the training or upskilling of workers can take place online. This can allow manufacturers to not only lower the costs of training but also to identify and fix performance issues in trainees within a safe digital environment before they’re allowed on the actual production floor. Considering the many benefits of digital twins, it’s no surprise that the global market for digital twin technology is expected to grow from just $3.1 billion in 2020 to $48.2 billion in 2026.

Optimized Process Automation

Big data analytics also paves the way for using smart controls at manufacturing plants. Through the combined use of smart sensors and switches, manufacturers can lessen the need for manual intervention by automating essential manufacturing processes. Our own analysis has determined that the automation of production processes can allow manufacturers to save over 60%