Abstract
Robot manipulators and unmanned vehicles are continuing to make their way into more and more applications within inspection and maintenance. These robots are generating a vast amount of data from the assets they are being deployed on. And the data can be vital in identifying maintenance needs and fully understand the condition of the assets. But the amount of data makes it tiresome, if not practically impossible, to manually process all the data being collected.
The industry has already started to investigate and to some extent deploy tools such as AI-based methods for automatic analysis of robot-enabled inspection data, but still many open challenges remain. To this end, we target the three main questions to investigate throughout the presentations and subsequent plenary discussions during the workshop.
1) What are the success stories in achieving actionable data from deploying AI-based automatic analysis of robot-enabled inspection data in the I&M industry today?
2) What are the challenges with identifying possible maintenance needs from AI-based analytics? E.g., regulatory, technological, data quality, acceptance of new technologies, new work methods, etc.
3) How can we bridge the gap from today’s challenges to further increase the uptake of AI-based analytics of robot-enabled data in the I&M industry?
The industry has already started to investigate and to some extent deploy tools such as AI-based methods for automatic analysis of robot-enabled inspection data, but still many open challenges remain. To this end, we target the three main questions to investigate throughout the presentations and subsequent plenary discussions during the workshop.
1) What are the success stories in achieving actionable data from deploying AI-based automatic analysis of robot-enabled inspection data in the I&M industry today?
2) What are the challenges with identifying possible maintenance needs from AI-based analytics? E.g., regulatory, technological, data quality, acceptance of new technologies, new work methods, etc.
3) How can we bridge the gap from today’s challenges to further increase the uptake of AI-based analytics of robot-enabled data in the I&M industry?