Closed-Loop Manufacturing, AI & IIoT

The first use of computers in manufacturing happened when a robotic head dipping soldering iron in a pan of molten metal was guided by computer software to solder the components on a printed circuit board. So far, no computers have been able to think for themselves. However without being able to think they can collaborate in the decision-making process and absolutely operate the plant autonomously. The early adopters are already enjoying the significant benefits of Closed-Loop Manufacturing and it is expected that more companies will start to catch up very soon.

Closed-loop manufacturing is a system of production and comprehension that seeks to minimise the risks involved in industrial processes in less time, with improved performance and fewer costs. Closed-loop manufacturing creates smarter, more efficient plants and enables a higher level of operational optimization.

The convergence of advanced artificial intelligence technologies, edge computing and closed-loop manufacturing is evolving into an intelligent plant that will be able to learn, sense, adapt and even predict. The advancement of artificial intelligence (AI), edge computing, and closed-loop manufacturing integration systems are eliminating the need for plant operators to address common industrial problems. For example, AI technology can sense the state of an intelligent system and control it according to its own analysis. This reduces the need for conventional manual operation, resulting in more precise and efficient production lines that are less prone to errors than a human operator. Closed-loop manufacturing merges the natural world with advanced automation and artificial intelligence (AI) technologies to fundamentally change how industrial processes respond to events in real-time. By leveraging these insights, manufacturers are able to generate wealth from existing infrastructure, utilizing existing assets more efficiently and achieving a quantum leap in plant productivity.

As with edge IoT, the role of IT will change from a centralized asset and service provider to more of an enabler that sets standards and bridges globally distributed facilities; processes and infrastructures.

AI and IoT are currently being used largely for applications involving data analytics and insights for improved business outcomes. One area receiving less attention is industrial IoT (IIoT). IIoT refers to the machinery connected to cloud-based software networks. IIoT already has a wide presence in manufacturing, transportation, and logistics.

With IIoT, machines and trackers report data in real-time, giving management insights on valuable output statistics. IIoT is a colossal opportunity as more and more devices become wirelessly connected to one another. The IIoT will add significant value as all these assets within a facility can be managed from one location. IIoT technologies collect and share machine data, also known as industrial data, in real-time. Machine data is any information that helps track or define the performance and health of a machine, such as vibration and temperature. IIoT tools bring together various devices scattered throughout an entire facility, allowing management insights into valuable output statistics that help streamline production processes.

Information about the IIoT is moving fast and becoming increasingly complicated. Making sense of it all, let alone figuring out where to start, is a major challenge for manufacturers. And there’s no time to waste—every manufacturing company needs a long-term vision that leverages digital technology to enhance value chains and drive growth, which can only be accomplished with the help of an experienced and trusted partner.