Industry 4.0 IOT

The Industrial Internet of Things (iIoT), which is also known as Industry 4.0 when applied to the manufacturing industry, is a concept of integrating smart manufacturing machinery, AI-powered automation, and advanced analytics to help make every worker and every factory more efficient.

The iIoT will revolutionize manufacturing by enabling the acquisition and accessibility of far greater amounts of data both faster and more efficiently than ever before. Many manufacturers have already started to implement the IIoT devices and processes by leveraging intelligent, connected devices inside their factories, warehouses, and workshops.

In most cases, companies are deploying iIoT devices and machinery that are connected by communication technologies that assist industries in collecting, monitoring, analyzing, and delivering valuable insights like never before. The exact mechanics of how this technology is deployed varies from company to company, but the goal is always the same; to improve operational efficiency through analytics, automation and connectivity.

For instance, by equipping warehouse workers with wearable technology, companies can collect advanced analytical data to gain insights into warehouse efficiency. These valuable insights can help manufacturing firms make faster and better-informed decisions.

The industrial Internet of Things is already improving the manufacturing industry by giving manufacturers, more visibility throughout the manufacturing process and by making data immediately available to multiple data consumers and applications.  

The principal idea behind iIoT is to make machines smarter and more efficient than human counterparts by constantly collecting, analyzing, and acting upon data. With companies now developing cutting-edge sensory technologies to capture data, the retrieved data can be coupled with real-time predictive analytics, artificial intelligence and machine learning to get a better understanding of how machines and production lines are performing.

By utilizing machine learning, systems can be trained to identify potential patterns that could result in a future failure; and if the results are concerning, then it can be automatically reported for further investigation. Such applications can help save companies millions, or even billions of dollars.

The biggest opportunity for the industrial Internet of Things exists in revolutionizing existing legacy infrastructures within industrial and manufacturing processes. For example, tire manufacturer Michelin replaced traditional tire testing protocols both within their factories and post-delivery with built-in sensors that automatically monitor tire pressure and other variables. The tires were sold as part of a service to coach truck fleet drivers on how they can save fuel based on the analytical data captured from the tire sensors.

The example above also illustrates how end consumers will benefit from the industrial IoT revolution. They will receive higher quality products and services, faster.  

Furthermore, iIoT networks have broken up stringent data silos and connected all staff, data and processes right from the factory floor to c-suite level. Business leaders can utilize iIoT data gathered from various touchpoints to get a full and accurate picture of how their enterprise is performing.

The first significant challenge is interoperability. Both devices and machines use different protocols and are made up of different architectures. One way this can be addressed is to utilize an API-driven environment to allow both device and machine to communicate with each other through API calls.

The second challenge is security. Transitioning to iIoT means moving to the cloud and many companies will be quite apprehensive about this since it could open up the possibility of the disruption of operation and production, cyber attacks and data theft. Companies, stakeholders, policymakers will need to work together to mitigate the risk of intelligent machinery connected to the network.