AI for refrigerators
The industry traditionally lags behind the more "light" business areas, and yet only a few large projects with the participation of AI belong to the manufacturing sector. That is, appropriate technologies, of course, are used here, but rather in supporting roles. To integrate the AI directly in the production process is solved a few, primarily because of the price issue: the costs of implementation are very significant, and the imperfection of the technology can result in serious losses. So often we are talking more about the remote control processes, where technology is only relative independence. For example, recently, the American Caterpillar presented a draft for the remote control of machinery in mines and quarries, where the work of drivers is associated with increased risk. Instead, the work of bulldozers and trucks will be to follow the operators in the future, with distances of several thousand kilometers, and in case of emergency you can stop the technique. Although it is already extreme case in that the vehicles are equipped with systems with AI that can recognize obstacles and avoid collisions with people and other equipment.
More credible artificial intelligence has demonstrated the South Korean LG Electronics, which last fall announced the construction of a factory of kitchen appliances worth $525 million it is Assumed that all stages of production, from manufacturing and procurement to quality control of finished products, should be managed by a single system based on AI, which in this case will also constantly to optimize the production process. The plant will occupy an area of 336 thousand sq. m by 2023 will produce up to 3 million units per year.
World leader in number of deployments of technologies of artificial intelligence and machine learning, according "information systems jet" and TAdviser, USA. They are followed by United Kingdom that use AI mostly in major investment banks, as well as India, to supply these technologies to foreign customers. The volume of Russian market of artificial intelligence and machine learning in 2017, experts estimate that 700 million rubles, and large industrial projects in which AI can be counted on the fingers.
From oil to steel
One of the already implemented projects on the use of AI in the Russian industry — the introduction of artificial intelligence technologies for steel production in basic oxygen furnace shop of the Magnitogorsk metallurgical combine. Because remelted scrap is typically inhomogeneous in composition, to bring the steel to the required standard it is necessary to introduce it in the smelting process of ferro-alloys and other special additives. Developed Yandex Data Factory service accepts data on the initial composition and mass of the charge (original mix materials loaded into the melting furnace) and taking into account the target parameters of the finished steel gives the operator real-time guidance on the use of additives. Consumption of the latter in the course of experimental heats with the application of new technologies decreased by 5%, and given the relatively high cost of ferro-alloys steelmakers expect to save up to 23 million rubles a month.
The technological leader in oil and gas industry, the company "Gazprom Neft", is implementing several projects involving AI. One of them, "Cognitive geologist" implies the creation of a learning model of geological object. The fact that key decisions on development of deposits it is necessary to take at an early stage of development, and the error made in the beginning of the process in the future to correct is almost impossible. Geologists are trying to restore the data to get reliable picture of the structure of the subsoil and to answer the main question: how cost-effective would be the prey? It takes a year or two, the confidence in the correctness of the answer still does not exceed 60%. "Cognitive geologist" will be mathematically processing the original information to estimate the probability of correctness of the responses and make recommendations on methods of development or the need for additional research. According to specialists of "Gazprom oil" and the interpretation of geological data due to the work of AI will be reduced to six times, and the number of extracted useful information will increase by 30%.
Another project of "Gazprom oil" involves the use of AI in drilling difficult wells. A typical example: oil companies on the basis of a geological model is necessary at a depth of several kilometers to get to a thickness of only two or three meters and to use it as a well over a kilometer, responding quickly to change the configuration of the productive horizon, which are tracked using sensors mounted on the drilling tool. However, the sensors are located at 17 m from the bit, so the experts remotely control the situation from the control Center drilling "Geonavigator" in Saint-Petersburg, learn about the outlet hole of the productive horizon with a delay of 20-30 minutes. During this time, the trajectory of the drilling can go from a three-meter reservoir at a considerable distance.
Photo courtesy of PJSC "Gazprom Neft"
The solution was found in the trained model, which in real time will draw conclusions about changing conditions at the farthest point wells based on the parameters such as load on the drilling tool, resistance, temperature, vibration and speed of penetration. This will enable the specialists of "Geonavigator" quickly adjust the trajectory of the drilling to Refine the geological model of the Deposit, simultaneously forming additional data for further study "smart" drill. In the future, a mathematical model of the drilling will enable indirect data to proactively predict potential emergencies and to establish the optimal regimes of equipment operation and even real-time to determine the formation productivity, while evaluating the economic efficiency of drilling concrete horizon.
Despite the fact that many of the projects with the AI, especially in industry, are still experimental, analysts believe in the great prospects of this direction. "Infosistemy Dzhet" and TAdviser in their submissions, the forecast growth of the Russian market of artificial intelligence and machine learning to 28 billion rubles by 2020. On a global scale, according to a recent PwC forecast, the use of AI by 2030, will boost world GDP by 14%, or $15.7 trillion. And businesses that ignore these technologies today risk tomorrow to be simply uncompetitive. Moreover, if you believe the predictions of some futurists, in the area 2030-2050 years, the expected breakthrough in the field of creation of "strong" artificial intelligence which has exactly nothing to inferior to the human.