IoT & Augmented Reality: Reimagining Enterprise Asset Management
Implementing IoT technology to streamline asset management and leveraging AR capabilities enhances uptime and mitigates maintenance costs.
FREMONT, CA: An organization's greatest asset could be the advanced technology that holds the business running efficiently. Capital-intensive industries have recapitulated to utilize large numbers of enterprise assets at each stage of the production method. Failure in any of these assets can create shutdowns that can cost upwards to tens of thousands of dollars per hour in failed production. To avoid failure and to keep equipment working, veteran service technicians must be observant in identifying any faults in the production process and quickly fix them. Businesses are adapting to emerging technologies like the Internet of Things (IoT) and Augmented Reality (AR) to modify the industrial maintenance and field service process. These technologies can capture data in real-time and spontaneously converting it into actionable information that enables failures to be diagnosed quickly.
Digital technologies will complement the ability of field technicians. It will improve the technicians' skills productivity by extending diagnostic information and other information undeviatingly over their view of the asset expecting service. To enhance asset management, uptime harnessing the power of IoT and AR, from initial exposure to the problem to the resolution is required. Assets of the enterprise should be equipped with sensors and then should be connected to the IoT technology. This way, their performance can be observed and diagnosed remotely. Enterprise assets are now equipped with thousands of sensors that monitor vibration, flow, pressure, and many other parameters. It is used to transfer data and control system where operating judgments are made.
Machine Learning (ML) systems can interpret the data stream from sensors to learn what's going on deep inside sophisticated machinery. Analysis of prior failures should be used to compare sensor readings and the condition of crucial components that might induce machine failures. Algorithms predict particular elements that are contributing to failure and monitor the status of in-service equipment to ascertain when maintenance is needed. This approach makes it feasible to perform maintenance only when it is required. Advancing technologies like AI, IoT, etc. will find greater adoption in various verticals and industry segments.