AI, custom-made application, Industry 4.0, Internet of Things

Artificial intelligence in industry

ai in industry

Artificial intelligence (AI) is increasingly being used in companies in the industrial sector. AI enables to perform assessments, learn and solve problems by systems. Intelligent applications can quickly process huge data sets and then support process optimisation in industrial companies.

From the article, you will learn about:

Artificial intelligence is based on machine learning (ML). It is the ability to recognise patterns in unstructured data sets. As a result, with the information obtained, the computer can make decisions and continuously learn and improve its actions.

One of the techniques used is a deep learning based on neural networks. These are built on the analogy of neurons found in the human nervous system. ‘Deep’ means that the network structure is based on multiple layers. With deep learning, the computer identifies connections between data, draws conclusions, and makes decisions. Artificial intelligence can analyse not only numerical and textual data but also images or videos.

Another technique that supports artificial intelligence and the Internet of Things (IoT) is the digital twin. This is a virtual model of a real process or product. The digital twin is created based on readings from sensors and sensors that collect data. The digital twin supports the testing of prototypes and facilitates error analysis, for example in the automotive or medical industries.

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How can artificial intelligence assist the industry?

The main areas where artificial intelligence in the industry can find its application are: 

  • quality control (e.g. artificial intelligence in pharmaceutical industry),
  • improving safety (e.g. artificial intelligence in automotive industry),
  • product and service innovation,
  • discovering new relationships, trend forecasting and anticipating future risks (e.g. artificial intelligence in the construction industry, AI in the fashion industry),
  • process improvement, e.g. optimisation of the production process (artificial intelligence in manufacturing industry).


Examples of the gains from implementing artificial intelligence in the industry:

  • Artificial intelligence supports cost reduction,
  • AI, through ongoing analysis and rapid response to failures, extends machine uptime in the long term,
  • Artificial intelligence improves production quality by analysing production data.


sztuczna inteligencja


In which areas will artificial intelligence solutions work?

  • Health and safety – advanced warning
  • Quality Assurance (QA) – defect detection
  • Maintenance – planning maintenance and extending machine life
  • Production – analysis of parameters and their impact on final product quality
  • Supply chains – demand forecasting and price forecasting
  • Energy management – thermal efficiency analysis


However, the application of artificial intelligence is much broader. Kotrak is currently developing a fleet management app for company cars using neural networks and a digital twin. Thanks to the multidimensional analysis of a large number of factors, such as vehicle operating time and incurred costs, among others, we can create an advanced calculator for entrepreneurs. It will significantly facilitate the work of the fleet manager.  


Production planning using artificial intelligence

Kotrak is currently running a project involving the use of a genetic algorithm in a manufacturing company. The computer generates a population of production plans and sorts them to match the most important criteria selected by the planner. Once many plans have been accepted by the operator, the system learns the patterns of the situation. As a result, it is then able to suggest solutions or detect possible risks early on. As in the case of the quality control described earlier, the system is taught to plan based on previously accepted plans for production companies.

AI w przemyśle


Artificial intelligence in enhancing security

Artificial intelligence systems in the industry can make existing products or services more efficient, reliable, durable and, above all, safer. AI is used in the automotive industry, for example, in pedestrian and obstacle detection systems, and by visually analysing the position of the car concerning the lanes. The artificial intelligence algorithm also plays an important role in the aerospace industry. NASA carries out parallel analysis of text reports and numerical flight data. Thanks to artificial intelligence, anomalies are detected, and then it is also possible to link them to random errors. By analysing past faults, artificial intelligence can be used to prevent possible problems in the future.

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Cut costs with industrial artificial intelligence

Predicting and preventing maintenance through data-driven machine learning is also important for cost reduction in industrial companies. PHM system (Prognostic and Health Management System) capture changes on the shop floor by modelling machine wear and tear, allowing work to be planned accordingly without unnecessary downtime.

An example of the use of artificial intelligence in such a role could be the conclusions drawn thanks to sensors installed on the blade of a cutting machine. Appropriate analysis and interpretation of the data allow a quick understanding of the condition of the blade and prediction of its service life. In this way, workers do not have to rely solely on their experience to assess the condition of the blade, which is safer and prolongs the trouble-free operation cycle of production machines.


AI in manufacturing companies

Collaborative robots are another opportunity to demonstrate how artificial intelligence supports manufacturing companies. Their arms can learn to repeat performing movements that a human demonstrates to them. As a result, they can then perform them independently and repeat them many times.


AI w produkcji


Artificial intelligence also enables the modelling of large-scale systems. These are fault-tolerant thanks to evidence-based modelling and deep learning on large amounts of data. In practice, the knowledge gained from such a model can help, for example, to create a maintenance schedule for machines and manage the spare parts warehouse more efficiently. The implementation of artificial intelligence can also automate processes such as work schedules. An example is the Hong Kong underground, where an AI programme decides engineers’ work schedules with greater efficiency and reliability than humans.


Artificial intelligence in quality control

AI can analyse data, improving production processes. Thanks to AI algorithms, it is also possible to improve the quality of manufactured parts on the production line. AI performs automatic image recognition and controls deviations from the norm after a specific component has been manufactured. It can also eliminate pseudo-errors and restore a component that was previously eliminated. As a result, the quality of production is noticeably increased and the control of production processes can take place without human intervention. Intelligent process quality control can also be carried out for fabric production. Using microscopic images, AI can perform a visual check of the proportion of fibres in the yarn.

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Supporting employees with a virtual assistant

The virtual assistant (voice or text bot) allows immediate response to the needs of employees in a variety of areas, including reporting technical problems in production, HR and personnel matters, authorisation and data verification. It can also support the activities of the support and technical assistance department. The bot can carry out the entire conversation and dynamically exchange information with the IT systems that are used in your company. It automatically retrieves and transmits information from various data sources that are needed to resolve the intercepted request.



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