close x
download

Brochure

Enter Your Info Below And We Will Send
You The Brochure To Your Inbox!

aibotics go-ditial brochure (en)

Thank you!
Your submission has been received!

Oops! Something went wrong while submitting the form

brochure
News

How To Make AI Work In Extreme Conditions?

Ekaterina Lyapina, AiTHORITY
3.3.2020

Artificial Intelligence (AI) can be applied to a lot of industrial environments to save costs and to improve processes.

This industrial Artificial Intelligence does not only include the smart algorithms and Big Data concepts that reside in the virtual space inside the computer systems, but it consists of the physical devices themselves too. Data has to be captured with sensors. Commands have to be sent to actuators and control systems. This whole chain and flow of information, wireless or via cables, goes through places with extreme conditions. From the points of operation inside factories, mines, or oil rigs to the Big Data storage and huge processing power inside data centers and control rooms there is a long way to go.

Industrial production facilities, physical transport systems, and distribution channels are complex and feature often a zoo of devices from different manufacturers. As automation is far advanced, there are a lot of existing digital control and management systems in place. Today you find data networks, Supervisory Control and Data Acquisition (SCADA), programmable logic controllers (PLC), and Heating, ventilation, and air conditioning (HVAC) in industrial settings. All these systems are looked at on different levels of abstraction. There are concepts and higher management levels of complexity, and there are lower levels stronger connected to physical challenges.

It's Getting Rough

Existing industrial installations have a lot of wiring and kilometers of cables. These sophisticated networks keep operations running. You have industrial standards for digital networks that connect devices and switches, that provide gateways and that create connectivity to control rooms. These systems were built to perform well under harsh environments. With the arrival of Artificial Intelligence and new global digital connectivity in an industrial context, the new smart devices also need to be able to perform under these extreme conditions. AI is closely connected to the industrial internet of things (IIoT) to offer more wireless connectivity and links to enterprise-wide systems and the internet.

All these new systems face the challenge of nature and the powerful forces of heavy industrial machines. Production facilities may be located in faraway places, with no power grid. Imagine operations in the jungle with only one improvised road to give access. You have to bring all the energy sources by yourself via generators or batteries. The environment may be cold or hot, with nasty gases that corrode electronics or make them vanish in an explosion. But the heat and the cold could not only source from nature but from production processes also. Melting and freezing workpieces could be part of the production process. A lot of work takes place in the mechanical realm. You have parts moving at high speeds. You have machines that create vibrations and shocks. Artificial Intelligence is now facing these physical challenges mainly in the form of robotics and IIoT networks.

There Are Robots Everywhere

Robots are a complex challenge. They need to do things, and they need to move themselves to where they’re needed. To achieve this without human interaction, an AI brain inside this robot is needed to make it autonomous. But, we all remember robots failing in decommissioning nuclear power plants. The problem, in this case, was the radiation destroying the electronics. So, a hardened brain is needed. Further, communication with the outside world is difficult. In intense radiation wireless or wired communication is a challenge.

However, it’s not only very intimidating nature of nuclear decay that is a problem statement for industrial Artificial Intelligence but also examples of deep-sea exploration or mining. They’re very challenging too. With a lack of general infrastructure and no fixed power supply or internet available, you need to adapt to existing best practices to the digital and data-driven transformation of AI.

You may not find these extreme examples on the edge of production in your everyday production facility. But you’ll find similar challenging situations. The environment and machines in operation created threats that are everywhere in industrial production. And the armada of autonomous or ready to be autonomous robots is growing every day.

You have robotic arms, walking, and diving autonomous vehicles, and flying machines for all kinds of tasks. They come in classes like automated guided vehicle (AGV), unmanned ground vehicle (UGV), rovers, autonomous underwater vehicle (AUV), remotely operated underwater vehicles (ROV), autonomous dump trucks, autonomous haul or mining trucks, Unmanned Aerial Vehicles (UAV), or drones.

These robots come in many forms to be more efficient and cost-effective. They can perform tasks that employees couldn’t do. May these tasks are just mundane longer shifts or may they be working in even harsher environments. They could do inspection whenever and wherever it is needed.

Everything Will Be Connected

The second big application of industrial AI is the connection and aggregation of data throughout the enterprise. All sensor data collected will be stored in one Big Data lake. A network that behaves like a living organism could be created with the help of industrial IoT. Here, the wireless and wired data connections are facing the physical world. Cables, switches, routers, and gateways need to be robust. They need to be able to sustain dust, and vibrations, mist and water, and more dangerous and harmful substances and physical effects. They need to be reliable, and they should be able to operate for years without help from the maintenance personnel.

The new industrial AI also faces the challenge to integrate in safety and security aspects. A lot of legacy systems operated in a fine-tuned manner for years. They provide solutions for very good performance in the extreme conditions they face. Their optimization processes have been going on for the year. So, a new industrial AI should not endanger this achieved equilibrium. Another concern is data and operational security. Once the production facilities are hooked to the global internet, attackers have theoretical access to the systems. And as the values and stakes are very high in the heavy industry, this is another extreme reality.

Read the full story on AiTHORITY

...
more posts