![]() ![]() Using digital twins, Boeing has been able to achieve a 40 percent improvement rate in first-time quality of parts. By 2022, as many as 70 percent of manufacturers may be using digital twins to conduct simulations and evaluations – which gives you an idea of just how transformative this trend could be. Digital twin technology can even be used to visualize and simulate an entire supply chain. For example, in a manufacturing setting, a digital twin could be used to simulate a new product's dimensions or create a digital replica of the equipment on the factory floor to see how the machinery operates under certain conditions. This shows how predictive maintenance processes can be applied even to legacy machinery.ĭigital twins can be used to simulate any physical process or object. Siemens has used such sensors on older motors and transmissions – and by analyzing the data from these sensors, Siemens says it can interpret a machine’s condition, detect irregularities and fix machines before they fail. The idea is that by understanding when a machine or part is likely to fail, manufacturers can take preventative action and maintain their equipment more effectively.Īnd this doesn’t just apply to fancy new equipment. ![]() In a manufacturing context, predictive maintenance refers to the use of sensor data and artificial intelligence (AI) to detect failure patterns in machinery and components. Manufacturers can create a private 5G network on their premises which will give them superfast data speeds without the need for cables and much-improved data security. The fifth generation of mobile data network technology (5G) will enable manufacturers to easily connect their IIoT technology and leverage the data collection and data processing within devices such as smart machines and sensors (what we refer to as edge computing). ![]()
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