Industry 4.0 technology is having a major impact on the manufacturing sector. Artificial intelligence (AI) and smart devices have enabled a range of new technologies, maintenance strategies, and management techniques.
A growing number of factories are adopting smart tech and investing heavily in AI solutions. Over the next few years, an increasing number of facilities will likely come to depend on both AI and Internet of Things (IoT) technology to improve performance and conduct site maintenance.
These three applications of Industry 4.0 tech show the impact AI and IoT are having on manufacturing — and how the sector is likely to transform in the near future.
1. Improved Site Monitoring With IoT
A fleet of IoT sensors can be used to monitor a facility and give supervisors real-time insights into the flow of goods, machine performance, and site workflows.
For example, signals from RFID tags attached to pallets can be tracked by IoT sensors installed throughout a factory. This could provide managers with a real-time picture of how goods are moving around the floor — potentially helping them identify issues that could be creating bottlenecks.
Similarly, Internet-connected cameras and machine-monitoring solutions can enable remote monitoring of a factory, allowing supervisors to monitor the floor even when they can’t be on-site.
2. Smart Factory Management
IoT devices can also enable a wide range of other smart factory solutions. When processed with AI analytics, data collected from a factory IoT fleet can provide detailed insights into the performance of factory machinery though a central app. This helps managers optimize their use and prevent downtime.
One of the most common applications of industrial IoT technology and AI is predictive maintenance. Factory managers install IoT sensors that monitor various indicators of machine performance and health — like temperature, oil barrel pressure, vibration, and machine timing.
Information from these sensors is fed into an analytics module or big data analytics platform. After establishing baseline performance, an analytics tool can detect anything unusual that may signal a damaged part or misconfigured machine.
When a machine drifts outside of the normal performance range, the system can automatically alert the factory’s maintenance team. This allows them to shut down operations as needed or catch issues before they lead to more serious problems down the line, such as damage or failure.
As a result, managers can be more proactive with maintenance than they would with a preventive approach that relies on regular maintenance checks conducted at fixed intervals. This proactivity can make a factory more efficient by preventing downtime and improving machine health.
In combination with regular maintenance checks, this approach can also save factory owners 8%-12% on maintenance costs compared to preventive maintenance, and they saved up to 40% compared to reactive maintenance.
Predictive maintenance may also allow managers to improve machine performance over time. Enough data on operational performance can uncover relationships between things like machine efficiency and timing, or temperature.
In some cases, an AI management solution may be able to fully automate some tasks. An advanced predictive maintenance solution could automatically shut down a machine that’s performing unusually, potentially preventing damage or failure.
3. Smart Robotics
AI and IoT have also enabled a new range of robotics that are capable of performing complex tasks and working with human workers with minimal outside input. For example, autonomous mobile robots, like those used by e-commerce giant Amazon in its warehouses, can automatically navigate a warehouse floor, picking stored components or materials and delivering them to workstations as needed.
These robots offer the typical benefits that robotics without AI offer — like consistent and accurate performance. They also provide additional advantages, like less need for human guidance. They use AI technology called machine vision, which allows the robot to break down visual information recorded by a front-facing camera. This enables it to identify obstacles and navigable floor space.
Other robots, called collaborative robotics, use AI to work close to humans. In addition to their AI, these robots also come with practical safety features, like force limiters and padded edges that reduce the risk of injury to workers.
These autonomous robots and cobots can typically be monitored in the same way as other IoT solutions. Over time, the movement patterns of these robots can provide supervisors with additional insights into factory workflows.
With the right combination of AI and IoT, factory managers can adopt a wide range of new smart factory management technology — including predictive maintenance, remote monitoring, and intelligent robotics.
Together, these applications can improve factory efficiency and cut down on major expenses, like maintenance and machine downtime. Manufacturers would be wise to adopt AI and IoT to streamline their processes and ride the wave of the future. Doing so can help ensure success and boosted profits.