The Importance of IIoT in a Smart Factory
In the manufacturing sector, the rise of Industry 4.0 is evolving at a rapid pace and technological advancements are the backbone of this evolution. Key technologies such as Artificial Intelligence, Machine Learning, Automation and Industrial Internet of Things (IIOT) are essential. As part of connected and adaptive manufacturing, Smart Factories are a new opportunity to adopt exciting technology in order to achieve demanding production goals.
Smart Factories rely heavily on smart manufacturing, with the use of data, they are a highly digitalised and connected production facility. They are designed to drive the adoption of digital manufacturing processes and create better outcomes for productivity, delivery, reduced labor and energy costs.
As part of Industry 4.0, new technologies will be introduced as part of intelligent manufacturing and they can also be found in Smart Factories, for example:
- Adopting robotics at a deeper level such as drones that would replace current human workloads.
- Use of machine learning to analyse data gathered by sensors and monitoring devices in order to make real-time decisions to improve the efficiency of production.
- Utilising IIoT to create a system of connected devices with predictive capabilities to make autonomous decisions based in an intelligent, decision-making environment.
IoT focuses a lot more on connectivity, data analytics and automation as part of a huge digital ecosystem. “In IIoT technology, sensors are attached to physical assets,” says Robert Schmid, Deloitte Digital IoT Chief Technologist. “Those sensors gather data, store it wirelessly, and use analytics and machine learning to take some kind of action.”
IIoT can transform linear manufacturing supply chains into interconnected digital supply networks (DSN), making factories more efficient, saving on costs and reducing risk for human operators.
The most notable feature of IIoT systems is the use of sensors to detect, for example, if a machine goes down or reaches a temperature that’s too high, sensors then track the source of the issue and trigger a service request. This is known as ‘Predictive Manufacturing’, a fascinating system that converts data into information and make intelligent decisions about the machine or process.