Smart manufacturing is a combination of various technologies and solutions, including artificial intelligence (AI), robotics, cybersecurity, Industrial Internet of Things (IIoT), and blockchain that are implemented into a manufacturing ecosystem to optimize manufacturing processes by generating and/or accepting data.
Smart manufacturing design is founded on an IIoT method for process analysis. Data analytics can showcase what is needed for a more efficient, transparent, flexible, and ultimately profitable production process. The purpose of smart machines and smart systems is to streamline operations through process enhancement and the automation of certain manufacturing systems. Smart manufacturing is all about collecting and properly utilizing information, and as such, cybersecurity is crucial to the success of smart factories.
IIoT uses data communication systems to connect every device, machine, and process. Each piece of industrial equipment contains sensors that can generate any relevant data and send it through those data communication systems to the cloud or the appropriate software system. This is done to create insight into any dark areas along the production process and to suggest any corrective action to increase efficiency, productivity, and profitability.
Robots with AI capabilities are also being implemented in many manufacturing ecosystems. Typical manufacturing plants have previously employed robots programmed to do single tasks. Now, with smart manufacturing, intelligent robots are on the shop floor, connected with implanted sensors to get data and adjust their actions accordingly. These AI robotics enable perception-based decision-making, something that was previously impossible with only rule-based algorithms. AI can also be applied to smart manufacturing for predictive maintenance, used to discover machine performance, equipment breakdowns, and any operating conditions in real-time.
Digital twins are another part of smart manufacturing, which involves creating a virtual copy of an asset, system, or process using data from system and asset sensors along with algorithms to make data-based process projections. Predictive maintenance systems utilize digital twins as they lead to reductions in time and cost of new product development and eradicate any unplanned downtime. The increased use of IoT platforms, cloud platforms, 3D printing, and 3D simulation software all inspire digital twin adaptation.
Smart manufacturing is not as widely implemented as some other smart technologies, as it is difficult to integrate IIoT into current or older systems. Smart manufacturing concepts need to be introduced in the design of a manufacturing facility to effectively utilize sensors and related technology.