Artificial intelligence (AI) has become an integral part of our daily lives and has applications in various fields such as medicine, programming, marketing, and manufacturing. Sometimes AI can outperform humans in completing tasks or make them much easier. In this article, we’ll look at how artificial intelligence is being used in manufacturing. For more detailed information about the use of AI in business, you can read this guide. Let’s start with what the concept of artificial intelligence actually is.
What is Artificial Intelligence?
Artificial intelligence is a technology aimed at developing programs that are able to cope with intellectual tasks and generate new information based on existing information. In this way, AI can simulate human activities.
Technologies based on artificial intelligence are capable of processing huge amounts of information, identifying basic patterns, making complex decisions, making predictions, recognizing images and human speech, and performing many other tasks. Systems that support artificial intelligence have the ability to constantly learn and adapt to new situations.
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Artificial Intelligence capabilities
The development of artificial intelligence systems as a direction is largely due to the need to solve specific problems, which are often labor-intensive for people. AI allows you to:
Automate repetitive decision-making processes by leveraging data and continuously performing multiple calculations; Carry out in-depth analysis of large volumes of data in real-time; Achieve an unprecedented level of accuracy, completely eliminating human errors; Optimize processes, taking into account various constraints associated with the context of solving the problem.
Troubleshooting and anomalies
For example, for a technological process, it is important that the parameters responsible for the process are within the required ranges. In large-scale production, deviations from technology can lead to undesirable consequences – manufacturing defects, recall of product batches, and stopping production processes. Monitoring and detecting anomalies using artificial intelligence allows manufactured products to maintain their ideal characteristics.
Another application scenario is identifying faults at early stages, reducing downtime, and optimizing scheduled repairs. A system equipped with AI can detect and eliminate critical faults much earlier, when they are not yet capable of causing serious damage to production – for example, failure. This often leads to downtime and takes away money and time from responsible employees in production.
This approach minimizes situations when equipment suddenly breaks down, stopping a significant part of production processes: artificial intelligence will warn about malfunctions in advance, and employees will have time to make a decision.
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Process optimization
When producing any product, it is important to follow the technological process and adapt it to changing conditions (changes in the parameters of incoming raw materials, temperature, requirements for the characteristics of the finished product, etc.). At the same time, you need to monitor and manage a large number of parameters. The operators responsible for the process may have different experiences, work on different equipment, may be distracted, etc. This leads to the fact that process control is not always optimal, and in this case, we talk about the “human factor”.
In this case, you can use machine learning algorithms that can make forecasts based on the current situation and select the optimal mode of control actions (setpoints) to achieve the required results. Such systems can operate both in recommendation mode when the operator is given advice on control actions, and in automatic mode, when algorithms directly control the process under the control of the operator.
Forecasting
This scenario is also based on the ability to build predictive models that take into account many factors. This can be useful when planning the release of finished products, planning purchases, sales, and logistics. Thanks to this use case, it becomes possible to plan more flexibly, increase profitability, and optimize production as a whole.
When planning, it is important to understand what raw materials you will be working with. The range of products, the workload of enterprises, and logistics depend on this.
Conclusion
These are just a few of the major uses of AI in manufacturing and industry. In modern manufacturing, AI has one of the main roles, as it improves and simplifies not only the production process itself but also the quality of the product. No matter how professional a person is, there is always a human factor due to which an error can occur. The main problem with the implementation of AI is the small number of specialists who can work with this technology in production. Over time and with the development of AI, workers will be able to fully cooperate with AI, making their work easier, but at the highest quality.
