Autonomous Maintenance Software

AMS integrates advanced sensors, artificial intelligence (AI), and the Internet of Things (IoT) to automate the monitoring, diagnosis, and repair of essential urban infrastructure such as water systems, transportation networks, and energy grids.
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Technology Readiness Level (TRL)

Technology Readiness Level (TRL)

Prototype Demonstration

Prototype is fully demonstrated in operational environment.

Autonomous Maintenance Software

Artificial intelligence maintenance techniques are being employed in a wide range of industries, covering everything from policing to prevention, decision-making, and operational problem-solving. They extend from intelligent maintenance optimization models, simulations, and intra-logistical processes to practical applications, such as selecting optimal repair methods or cost budgeting. With the ever-increasing complexity of big industries, automated and artificial intelligence algorithms have been essential tools to deal with such an immense amount of data and crossing parameters. Several inputs, such as energy consumption, material consumption, carbon footprint, and efficiency, have to be taken into consideration to extend the life of existing assets for as long as possible.

Existing hybrid AI techniques are employed in industrial maintenance management, meaning that each AI method succeeds in assessing specific dimensions of intelligence. For instance, fuzzy logic is largely employed when dealing with uncertainty, like risk-based inspection, and has been successfully used in the gas and oil industry to estimate risk by combining the likelihood of occurrence and the potential consequences. On the other hand, neural network algorithms are often used in modeling and simulating statistical analysis for optimization. It helps to estimate the remaining life of machines and components, predicting what impact degradation of individual pieces would have on the final product. It has been primarily used in sustainable management maintenance models of supply chains.

The most common AI application in maintenance is genetic algorithms due to the powerful optimization tools able to deal with complex maintenance planning issues, like maintenance and inspection schedule. Also, genetic algorithm solutions can “evolve” with mutation, and weaker solutions become extinct. However, genetic algorithms may require high computing power and processing due to their intricate nature, but they continue to be a powerful solution for large-scale and elaborate applications of unaccounted variables.

Nevertheless, complex AI systems could autonomously operate maintenance tools and robots, freeing human workers from dirty, dangerous tasks while eliminating errors and reducing variability. Upon integration with factory AI operating systems, robots would represent to manufacturing what a medical doctor means to a human. It would be able to identify which facilities require regular maintenance and optimize systems while preventing disturbances. Instead of deploying personnel when things break down in those settings, these systems could make it possible for places to run autonomously for long periods, allowing for factories to be created farther away from residential areas, deeply shaping the architecture of cities.

Future Perspectives

These AI hybrid implementations could autonomously acquire data at all levels of complexity by cross-checking information, improving and updating themselves, and coming up with sophisticated solutions, thus, working like the nervous system of the whole factory. Also, with everything interconnected, the hacking risk is likely to rise. Preemptive strategies should be developed and implemented to prevent these attacks before this technology is deployed.

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Sources
Over the past 3 decades many attempts have been made to apply Artificial Intelligence (AI) techniques in maintenance modeling and management. Essentially the use of AI is an attempt to replace human intelligence with machine intelligence.
7 a Space Shuttle launch, the two solid rocket 1 masters fire for two minutes as the Shuttle drills ts way through the atmosphere to an altitude of tbout 25 miles. Then they separate from the 'II orbit-bound Shuttle "stack" and drop Earthward to a parachute-softened splash in the ocean. They are retrieved by recovery teams and delivered to a land facility for refurbishment and reuse.
A new study shows that a swarm of hundreds of thousands of tiny microbots, each smaller than the width of a human hair, can be deployed into industrial wastewater to absorb and remove toxic heavy metals. The researchers found that the microbots can remove 95% of the lead in polluted water in one hour, and can be reused multiple times, potentially offering a more effective and economical way to remove heavy metals than previous methods
In North America alone, it has been estimated that nearly 21% of tap water is being wasted or lost during distribution year-on-year, chiefly as a result of lack of efficiency. Moreover, it has been estimated that global water consumption will increase nearly twofold in the next 7 years until 2023 and there is an urgent need for alternative water management techniques and methods that are both sustainable and efficient.
This swimming eel-robot does not make me happy. Watching its long, black, mechanical body move underwater, its red eyes glowing, makes my nerves twitch. The discomfort is primal. I have every sense...
An aircraft maintenance robot (20) for maintaining aircraft surfaces is described, that includes a maintenance tool (228), for example a nozzle (78), conduits and a pump, which supply fluid to the maintenance tool, which sprays the fluid on aircraft surfaces; movable arm with rotatable hinges and wrists such that a manifold to which the maintenance tools are coupled may be positioned in response to control signals; and a processor which, after accounting for the position of the aircraft, the weather conditions, and the physical dimensions of the aircraft, generates the control signals used to position the maintenance tool such that, after positioning the aircraft, the maintenance operation may be performed without human intervention. The preferred embodiment of the present invention discloses the use of the maintenance robot (20) for deicing aircraft. A wide variety of interchangeable end effectors, however, may be used for a wide variety of applications. These may include various cleaning, painting, paint removing, and even firefighting applications.
Factories will soon replace more human workers with robots. The switch makes economic sense and from a cost perspective will be a boon to manufacturing.

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