What does artificial intelligence mean for industrial companies in practice and how should it be approached? Technology opens many opportunities, but plans for renewal should always be preceded by clear business justifications.
Industrial applications for AI can be broken down into seven major areas: market and trend analysis, machinery and equipment, intralogistics, production process, supply chain, construction and the product itself. In this text, we are focusing on AI with regard to industrial products and autonomy in particular, as it is the future goal of many manufacturers of complex industrial equipment. Our example product is a smart mobile machine–a description that could be applied to a forest or a mining machine, tractor, car, truck, ship or an earthmoving vehicle, to name a few.
What will autonomy add to smart mobile machines?
In simple terms, autonomy refers to a machine’s ability to operate independently without an operator. Automation has actually been utilised in control systems for some time now to enable them to perform actions without any input from an operator. Some examples of this include cruise control and automatic windscreen wipers in passenger cars. So, what does autonomy add and how is it different from automation?
An automated system is pre-programmed to operate in specific situations by utilising sensors and actuators. In mobile machines, this means that a traditional action-based automation system is performing predefined actions independently. An example of this is changing gears with an automatic transmission, where the gear change can be done easily with a micro switch. Alternatively, it can be a fully automated process, where gears change according to speed. The driver does not change gears manually, as is the case with a manual transmission. However, the operator is still ultimately responsible for the overall control of the vehicle.
As we move from automation to autonomy, the operator’s control over the machine begins to decrease. Partially autonomous systems are often informally referred to as driver-assistance systems. These systems still require the presence of an operator, but the machine can already perform many tasks independently, such as features related to automatic control and working. In the automotive industry, such functions include driving assistants and adaptive cruise control, both of which can temporarily control the vehicle independently. Work machines include similar functions, such as headland automation in tractors and automatic driving on fields.
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AI in the product development of mobile machinery
The more responsibility a machine or device has over the overall control, the more software and intelligence is needed. This is where artificial intelligence comes into play, in more ways than one. AI can be embedded in the machine itself for the purposes of detecting driving lines, obstacles and people, for example. The machine can learn these things through machine learning, which it can also do during driving.
AI can also be of assistance during the product development process. The best way to develop autonomous devices is to use a virtual environment, where AI can add effectiveness in many ways. For instance, in quality control AI can automatically generate test cases, driving situations or various identifiable objects.
On the other hand, AI can support people in software development, as long as it is ensured that the software is in accordance with the required specifications and security standards. The opportunities for the use of AI seem limitless, and new innovations are introduced at a rapid pace.
Will AI and autonomy replace people?
What does future hold for autonomy? This is an important question, as increasing the autonomy of machinery can also cause uncertainty. Are we needed in the future? Not every industry that utilises mobile machinery finds fully autonomous operations necessary–at least not in the near future. This is often due to the high costs of the “sensory system” or sensor networks of machines or the quality of the vehicle’s operating environment or work tasks.
A cost-benefit comparison is important from a product development perspective. Substituting the human operator or driver should not be seen as the intrinsic value of autonomy. Instead, replacing the operator should be seen as an opportunity in situations where having an autonomous machine can significantly improve safety or increase work efficiency dramatically.
The increase in autonomous or highly automated functions to improve work efficiency and quality is a trend even in machine or equipment types, where full autonomy is still nothing more than a utopia. These functions can facilitate the everyday life of end users and help them complete their work tasks more efficiently.
