What is
Manufacturing 4.0?

The Fourth Industrial Revolution, often referred to as Industry 4.0, leverages machine learning, artificial intelligence (AI) and interconnected devices to help machines work smarter. By leveraging 5G networks and mobile edge computing, these technologies are better able to harness massive data volumes in near-real time to power new capabilities and use cases. While Industry 4.0 can be applied in all industries, manufacturers that leverage these technologies to design, produce, and deliver products will be able to make manufacturing more agile and adaptable, allowing them to unlock new levels of production efficiency and customization.

Manufacturing 4.0 is simply the application of Industry 4.0 in manufacturing, relying on the use of smart technology, interconnectivity, machine learning and automation to integrate data and feedback loops into the production and delivery of products across the supply chain. The rise of smart manufacturing creates new opportunities to be more agile and responsive to changes in demand, build better products, and proactively identify and mitigate issues that may impact the business.

Key to Manufacturing 4.0 is the smart factory, which connects and collects data across machines, people, devices and production systems to power machine learning and AI-driven analytics platforms. These platforms use data to allow managers to make data-driven decisions or, in many cases, automatically make decisions without human intervention, enabling manufacturers to optimize the entire production process.

A Manufacturing 4.0 approach can generate improvements in operational productivity and help make manufacturers more resilient to the unexpected so that they can continue to meet customers' needs no matter what situation might arise. In addition to helping a manufacturer remain competitive against other players in their industry, adopting a Manufacturing 4.0 strategy can also allow them to better attract digital-native employees and implement the latest technologies across the workforce.

By integrating near real-time data and intelligence across factory floors, warehouses, transportation, and the rest of the production and logistics supply chain, businesses have been able to unlock a number of exciting new use cases, including:

Every step of the manufacturing process produces massive amounts of data. Smart manufacturing allows organizations to use IoT sensors to capture and measure all that data, while advanced analytics platforms make it possible to combine that data with other sources from across the organization, such as sales, marketing, finance and operations. AI-powered systems can then automatically decide which products to create and where to send them, allowing the business to stay ahead of customer demand.

Manufacturing 4.0 allows organizations to use their data to monitor the near real-time condition of every aspect of their machinery. By tracking the real-world condition of each part, operations managers can proactively identify machinery at risk of failure, allowing them to fix machines before they break down,  thereby reducing the chances of unexpected and costly downtime. Operations managers can also use this data to get more life out of their machinery by continuing to use working parts past their scheduled life instead of replacing them unnecessarily.

The pandemic demonstrated how vulnerable and fragile supply chains can be. By connecting manufacturing, logistics, transportation and sales data together, manufacturers can leverage a near real-time understanding of where products are across the supply chain to identify bottlenecks or redirect supply. This visibility can also help third-party partners better predict when they'll get the products they need, helping them improve their own supply chain management.

Digital twins, which are a complete digital replication of a real-world machine, enable operations managers to virtually inspect and experiment with a digital representation to discover the optimal maintenance solution before sending a technician to work.

Smart manufacturing requires four advanced technologies working together:

IIoT uses sensors to collect data from machines, robots, components and products to capture near real-time location, performance and condition data.

All of this data is captured and stored in the cloud, which provides the storage volume, scalability and cost efficiency to manage massive volumes of data. Data can be shared and accessed with other departments to allow the business to operate as one.

Analytics systems that are powered by machine learning and AI use all the data that the business captured in the cloud to identify patterns and insights no human analyst could detect. Managers can use the analytics to make decisions, or the analytics can trigger automation that allows the smart factory to manage itself.

Any connected device in the smart factory can be a target for cyber criminals, competitors seeking intellectual property secrets or even state actors seeking to disrupt their rivals' critical industries. Automated security and cloud management services can continually test and patch vulnerabilities to help IT staff keep up as the attack surface scales.

Smart manufacturing requires internet-connected production machines that generate massive data volumes, which are then migrated to the cloud. Once there, analytics platforms need to access and leverage these data volumes to power their processes. And all of this must be done in near real-time, requiring two advanced networking technologies to deliver the bandwidth, resilience and security required: 5G and mobile edge computing (MEC).

5G has the potential to move data substantially faster than 4G, allowing manufacturers to move and leverage more data between sensors, devices and the cloud in near real-time.