Industry 4.0 holds vast potential for manufacturers. Learn how MongoDB can facilitate your move to connected, data-driven manufacturing processes.
Accelerate manufacturing digital transformation. Developers can easily build Industrial Internet of Things (IIoT) apps on MongoDB, connecting thousands of sensors and devices across the shop floor.
MongoDB auto-scales to ingest enormous amounts of sensor and event data and support real-time analysis for catching any critical events or changes as they occur.
Industrial IoT applications built on MongoDB can become a key differentiator for successful manufacturing companies throughout the entire supply chain.
Workers need constant access to critical data from anywhere on the shop floor. MongoDB provides your workforce with real-time insights and offline-first applications.
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See how MongoDB fulfills the demands of Industry 4.0–interoperability, flexibility and scalability.
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Techniques to ensure that applications can not only manage large data volumes but can also scale.
The manufacturing and automotive industries are under pressure for constant innovation — delivering better products as fast as possible and at the lowest cost for both producers and end buyers. Massive volumes of data trapped in legacy systems are holding these industries back from reaching their true potential.
Instead of depending on reactive data analysis, slowed by siloed and legacy systems, MongoDB’s developer data platform connects operational technology and IT data for improved overall equipment effectiveness (OEE), and enables the jump from manufacturer to a business able to accelerate customer satisfaction and monetize connected, smart products. Whether it’s adopting Industrial Internet of Things (IIoT) solutions or gaining a single view of your business from raw goods to shipped products, data underpins the entire operation.
With MongoDB’s developer data platform, manufacturers and automotive industry leaders can combine the enormous variety and volume of data their equipment and products produce into a single view and analyze it all in one place. This enables them to make real-time decisions that increase OEE, automate the factory, and serve customers long after their products have left the shop floor.
Industry 4.0 (I4.0) symbolizes the beginning of the Fourth Industrial Revolution. It represents the current trend of automation technologies in the manufacturing industry and includes the enabling disruptive technologies and concepts such as Cyber-Physical Systems (CPS), Industrial Internet of Things (IIoT), cloud computing, and immersive visualization.
IIoT and CPS technologies are integrating the virtual space with the physical world. This is resulting in a new generation of industrial systems, such as smart factories, to deal with the complexity of fast-paced and hyper-personalized production in current macro environments.
Industry 4.0 technologies, such as IIoT and CPS, are integrating the virtual space with the physical world. This is resulting in a new generation of industrial systems, such as smart factories, to deal with the complexity of fast-paced and hyper-personalized production in current macro environments.
IIoT is expected to offer promising transformation of existing industrial systems enabling digital transformation and unlocking tomorrow’s smart enterprise. The technology has been finding its way into products and sensors all while revolutionizing the existing manufacturing systems; thus, it is considered to be a key enabler for the next generation of advanced manufacturing.
Industry 4.0 generally comprises many complex components, and has broad applications in all manufacturing sectors. One of the biggest challenges faced by manufacturing companies is to make use of data generated by connected equipment and products to drive insights.
The digital economy is demanding that manufacturing applications become smarter, drive better customer experiences, surface insights, and take intelligent action directly within the application on live operational data — in real-time. The objective is to always out-innovate the competitors. To meet those demands for working with fresh data, we can no longer rely only on moving data out of our operational systems into analytics stores — this adds too much latency and separates the application from the insight that is created. To overcome these challenges, analytics processing has to be “shifted left” to the source of the data — to the applications themselves. MongoDB calls this shift “Application-Driven Analytics.'' And it’s a shift that both developers and analytics teams need to be ready for because it impacts their roles and responsibilities, along with the tools and technologies they are using.
MongoDB serves application-driven analytics through a set of platform capabilities and features — from database through data lake, a federated query service and connectors.