The digitization of the industry has created means by which defects can now be detected at an early stage, even before damage occurs. This is possible thanks to the Internet of Things. With its help, machines can be equipped with technology that allows them to sense and communicate their own states. This is usually done with suitable sensors that record and transmit key data – for example, temperature or vibration patterns. Such automated data evaluation is an essential part of the predictive maintenance concept. By analyzing both historical and real-time data, you can detect malfunctions at an early stage and take appropriate action.
Automated troubleshooting with artificial intelligence
Artificial Intelligence (AI) is typically used in Industry 4.0 to analyze large amounts of data. Combined with IoT and automation, AI acts as a multi-level alarm system, relieving the workload of employees.
For example, these systems can monitor the temperature of machines. If they think there is a risk of failure, they inform the employee and trigger automatic cooling. Artificial intelligence alerts the employee and provides him with all the important data at the same time. The person responsible for the operation of the machines does not have to react immediately and rush to the machine with a set of tools. The first stage of repairs usually includes remote diagnosis. Thanks to IoT and remote access, the worker can connect to the machine software to find the cause of the fault, analyze the logs and evaluate the data directly on the system. If the software is the cause of the failure, the employee can take the appropriate measures to solve the problem or change the settings directly from their computer, wherever they are. If the hardware is the cause of the failure, the worker can receive digital assistance via augmented reality (AR). Then the expert and the technician connect using smart glasses or smartphones. They both see the same camera image, and in addition to the voice call, they also have the ability to place visual markers – for example, highlighting certain switches with arrows or placing rings around them. them indicating that they should be pressed to identify the cause of the fault.
Efficient machine repairs in Industry 4.0 thanks to augmented reality
The machine repair method can also be recorded through AR to train employees and improve using artificial intelligence. To ensure compliance and quality, individual work steps can be documented using a camera installed in the smart glasses, and all combined with an AI personal assistant. Because the latter has been trained, he recognizes the machine as soon as he sees it and then gives the appropriate instructions – without the employee having to search for them for a long time. It also displays all the important safety instructions that must be followed when using and maintaining the machines. Artificial intelligence can also indicate which tools to use for repairs. He is also able to check the quality of the work carried out. For example, he will check that the screws have been tightened by checking the number of turns made and the pressure force.
The operation of industry in the reality of Industry 4.0 means that machines and systems are becoming more and more intelligent and more and more tightly connected in a network. Digitization offers tools to avoid production stoppages. All you need to do is properly implement AI, AR, and IoT to streamline the troubleshooting process and make it work properly. From now on, it is only up to the companies to seize these opportunities or not.