Advanced utility clients are leveraging drone-mounted LiDAR, HD photo, video, corona detection and thermography sensors. Teamed with automated analysis, predictive analytics and advanced scheduling these solutions are transforming maintenance organisations.
Regular asset inspection is labour intensive and time-consuming. Drone-based solutions remove the need for field teams - removing personal safety risks and creating significant cost savings.
Traditional fault analysis is often inaccurate and cumbersome and results in poor prioritisation of maintenance efforts. Automated analysis of sensor data is accurate and efficient. Asset failure can often be prevented and failed assets are back online faster.
Predictive analytics offers an additional layer of improved prioritisation. Traditionally, planned maintenance is scheduled based on time passed since last inspection or service. Predictive analytics uses historical asset performance and current conditions to predict future maintenance requirements, so assets are only maintained when they need to be, reducing wasted efforts and improving asset availability.
We are helping our utility clients leverage drone-mounted condition based monitoring solutions:
We team up with technology experts to run a pilot - using the time to assess the impact on resourcing and changes required to achieve the new maintenance operating model
We help you capture the savings - transitioning to a smaller maintenance team focused on condition-based inspection scheduling
We hardwire the new organisation to ensure the savings are sustainable - deploying wiring with clear role descriptions, accountabilities and KPIs, standard operating instructions and support tools, establish reporting cycles from top to front-line and provide coaching to managers and supervisors to ensure teams are held to account.
We are working closely with a global market leader of automated drone-based asset inspections, to provide our clients with #rapid, sustainable results. Experience shows a 20% reduction of inspection cost, as well as lower maintenance cost by moving towards a condition based maintenance regime.