What will the new tools and technologies in Asset Management look like in the next 20 years?
What will be required by companies using Asset Management to upskill employees, inform clients and keep abreast of these technologies?
A futuristic viewpoint.
I have a visual of the plant and equipment on the mine site on my monitor. There is a complete processing plant that has been built by COMSYS robots. The COMSYS has four roles in the mining equipment, processing, and infrastructure space, and include the Construction, Operations, Maintenance and SYStem analytics.
The mine has been operational since 2035, with human operators remotely controlling all robotics, equipment, and infrastructure.
The occupants of the entire remote operations room are Asset Management Specialists, utilising the Total Remote and Mixed Reality capabilities of our third-generation maintenance robots. My dashboard on my console currently shows that the mine is now at 96% production, a regular occurrence.
My trusty COMSYS robot is on-site as usual, completing another twenty-four-hour shift, self-diagnostics show no internal faults detected. I take control and start my typical hourly hybrid plant and equipment analysis.
I initiate the robots RAMRs, Remote Access Mixed Reality scanning equipment. A secured encrypted signal which streams big data to the cloud, no issues of data loss or hacking, the data is protected.
The scanner purrs into life, the nanoprobes have embedded themselves into the machine’s data module. It establishes the connection and begins its analysis and Relialytics to predict any faults on the plant and equipment.
The dashboard on my monitor glows red in the vicinity of the axel's mounts of the mobile plant. I can physically and digitally see the objects that will go into a failure condition, they co-exist, and I can interact with them and the COMSYS robot in real-time. The RAMR analysis is complete, an AI feedback loop has deduced the failure, and has initiated the robot to take the necessary action to prevent the catastrophe.
The AI has used its growing knowledge of its environment, machine understanding, business intelligence, and completed the proper actions that have maximised its chance of successfully achieving its goals of, plant uptime and strategy improvements. Further, the AI identified the risks and delivered proposed opportunities to maximise life cycle and ROI.
The RAMRs dashboard on my console has updated the operational data on the equipment in real-time. An accurate lifecycle position which has optimised the maintenance strategy using Live Life Cycle Costing. The report shows an integrated overview of; Asset Health, Asset Performance, Component Capacity, Economic Life, and Maintenance Efficiency, and has Forecasted Budget, Long-Term Planning with KT Project Management and material requirements.
I accept the request for the plan and materials and move the COMSYS robot onto the next module of mobile equipment.
In the above scenario, today's businesses are applying most of these technologies, and they just are not integrated into each other. The ideal asset management strategy is quite straightforward, consolidate all your information and technology into 'One Engine'.
I see the role of the Asset Management Specialists in the future to be highly specialised, our function in the design and management of technology for remote access, Relialytics, project management, analysis, AI interpretation and programming to final consolidation of reporting of purpose-built dashboards for clients of real-time data of asset health, forecasting and Live Life Cycle management of plant and equipment.
Add to this the engagement on-site, under real circumstances remotely, interacting with the environment and operations/maintenance personnel in assisting and assessing failures, scrutinising, and accepting AI analysis or flagging outputs.
We will be the doctors of assets, ensuring client uptime and production for maximum return on investment.