According to expert forecasts, by 2025–2030 new technologies and automation in production facilities will simplify the work of about 800 million employees worldwide. Machines will take 85 million jobs, but will also create 97 million new ones instead. At the same time, modern technological solutions already affect production in a variety of countries. Let’s figure out how this happens.
Why Do We Need AI in Production?
Today, artificial intelligence technologies are actively used in industry, construction, and energy. For example, algorithms calculate the timing of equipment failure, which allows employees to assess when to repair machines and when to replace parts. Various AI–based technologies already allow you to collect video streams from cameras and process data and transfer them to responsible employees to make managerial decisions. AI also monitors loading and unloading operations and technological processes in production, monitors the presence of personnel of certain qualifications in the appropriate work areas, and monitors instrument readings and the correct assembly of units in the enterprise.
AI technologies can reduce the risk of the human factor and optimize the costs of the enterprise, although everything, of course, depends on the “maturity” of the intelligence.
A New Stage of Development
Modern production facilities are almost completely automated–the share of manual labor tends to be zero. Now a new stage of development has come, which consists of the development and integration of AI in the manufacturing industry to increase the efficiency and stability of production.
First of all, such technologies can reduce the risk of equipment failure. Regardless of the specific tools, the goal is to fix potential problems in advance, which allows them to be solved before the moment a malfunction leads to a catastrophe or expensive production downtime.
In addition, AI can fully take over the functionality of managing technology and business processes. After training the relevant data, an algorithm can identify technological defects, deviations in the stages, and completeness of the executed processes. This makes it possible to increase the final efficiency of the business, minimizing the human factor.
The number of jobs in production has been reduced due to automation. However, there is a growing need for specialists who support and develop technologies. Thus, it can not be said that robotics in manufacturing allows you to completely abandon people–rather, it shifts the focus in terms of applied skills and the responsibilities of employees.
Today, China, Japan, and South Korea, as well as the United Kingdom, the United States, Canada, and several European countries (primarily Germany) are leading the transformation of the industry.
The list of the most popular technologies is headed by sensor devices, robots, and video analytics systems with computer vision functions. For example, BMW factories around the world use computer vision to check the quality of cars and detect defects in real time. People are not always able to do this work as efficiently as possible for various reasons. In this case, technologies that can handle these and other routine tasks much faster and more efficiently come to their aid.
Counting the number of hours worked is also possible for artificial intelligence: cameras record the time employees arrive at the facility and the time they depart. All the data from the devices is subsequently automatically uploaded to the database and used if necessary.
Another unusual use of AI is the control of the psycho–emotional state of employees. It is extremely important for many enterprises that employees come to the facility rested and cheerful. If a camera equipped with a face recognition system captures fatigue on the faces of some employees, they may be sent home or for a medical examination.
Speaking about the impact of AI on the creation of safe working conditions inside enterprises, experts note that “smart” cameras can notice a fire and sources of smoke, as well as damage to pipes and even open hatches, which allows you to quickly respond to the situation and reduce the number of victims.
One of the innovative developments in the field of AI in production has become “digital foremen” for process control and safety in enterprises. It allows you to minimize the risk of violations in the workplace with the help of AI and machine vision. This is a software and hardware complex with a neural network. Images of objects are processed using video cameras in automatic mode. The availability of equipment or personal protective equipment is checked, the number of personnel and working equipment is monitored, employees‘ working hours are recorded, and technological processes are monitored.
Risks and Obstacles
Along with many advantages, the use of AI in production carries certain risks. The use of systems in production should be controlled by specialists, otherwise, there may be situations in which the AI will make a decision that does not meet the requirements of economic feasibility and safety and will harm the company. The second group of risks is associated with employees who may lose their jobs due to the automation of processes– therefore, many should think about retraining.
At the same time, almost every industry has its examples of successful implementation of AI–based solutions. For example, in the mining industry, “advisors” or recommendation systems are used that tell line personnel how to act based on the analysis of historical data and the choice of optimal operating modes of equipment. In the process of managing dump trucks, they recommend when drivers should accelerate and at what speed they should maintain on each of the sections of the route, which allows you to significantly save on diesel fuel and reduce carbon dioxide emissions.
The introduction of new technologies in production naturally requires new professional competencies from employees. For business, this means that in parallel with the technological upgrade, it will be necessary to take care of personnel–to spend money on finding and training personnel, to increase wages, since technological production requires highly qualified and therefore expensive workers. An increase in the cost of labor, in turn, will lead to an increase in the cost of final products.
Experts predict that by 2030 automation will simplify the work of about 800 million employees. At the same time, the growing demand for the introduction of digital technologies contributes to the growth of the personnel reserve of IT specialists and stimulates interest in professional development and re–profiling.