7 applications of artificial intelligence (AI) which are revolutioning the production.

Today, the AI systems are able to adapt their behavior by analyzing the effects of their previous actions and working in autonomy: applicated in the production it give the possibility to imprve the total efficiency of the equipments (OEE) and the manifacturing production incomes.

The artificial intelligence (AI) is often applicated in the production to have a better total efficiency of the equipments (OEE) and the manifacturing production incomes. The producers can use the AI to increase the productivity times, to improve the quality and the coherence of the processes, with the possibility to optimize performances and predictions.

So as for many digitalization aspects, the implementation of AI could seems particuraly complex. Between the biggest worries of producers there’s the use of billions of data produced by the elaboration power of processors and devices connected to the network. So, there’s still uncertainty on how to start this route, so they keep going with prudence in the investments i the AI, in the IT equipments with the fear of not being preparred to this aspect of the 4.0 Industry yet.

The necessity of staying compeitive, is now clear, goes through production systems which use business models way more connected to the data, with the consecuence of often asking the reorganization of the employees, the replacement of the hardwares and updates of the softwares.

The artificial intelligence is already reaility, and it can be applicated to the factory.

The artificial intelligence is already reaility, and it can be applicated to the factory.

The artificial intelligence is the ability of a machine to show the human skills: nowdays the AI systems are able to adapt their own behavior by analyzing the effects of previous actions and working in autonomy.

Preventive and predictive maintenance

Between the frequent reasons of stop of a certain production task there’s the machine stop because of a mechanic or electric fault. Also, an easily predictable problem following the preventive maintenance programme recommended by the builder. Often, the maintenance programms are overlooked or not optimized to avoid the shcedulated production stop. Now, with the power of the available IoT, sensors, MES data and automatic learning algorithms, producers can count on more data to predict these faults. The maintenance programmes based on the analisys of the data permit to intervene in a specific way, in order to organize the spares provisions and the labour, and so, optimize the lyfe cycle of the components, the machineries and the production.

Optimization of the supply chain

Nowdays, the supply chains are networks complex to manage, with thousands of providers and hundreds of headquarters. The artificial intelligence is becoming an innovative instrument to bring materials and components in the costumer production line in a prompt way. With the learning algorithms they can create the supply chain optimizated for their products. Questions like “How many pieces should be ordered for the next quarter?” Or “Which is the best shipping route for the productt A?” can find their answer without trusting the best approximation.

Intelligent managment of the inventory.

The inventory managment is an important challenge. The production places a lot of its trust on the stock and avalaiblity to keep the lines feeded and produce manifactors. Each phase of the process requires a certain quantity of materials to work out. Once their finished is necessary to replenish rapidly to give continuity to the production. Keeping the factory supplied of the whole necessary inventory is a challenge in which the AI can help. The AI can examine and optimize the distribution in the whole factory.

Optimization of the production

The optimization of the processes, talking about the planning that includes a lot of data, is a hard acitivity. Descovering which process parameters produce the maximum production performance is not easy. The ingeneers of production and the quality resposables make a lot of simulations to constantly optimize the process parameters, also by using significants budgets. With the high elaboration speed of the AI, technicians and analystics can find perfect sets for the production. Questions like “Which speed or tmperature of the transfer should I set up to have the best result of the process? The AI will costantly learn from all the production points given, so as to costantly improve the process parameters.


When we talk about the AI applicated to the production, we can’t not talk about the income predictions. The ROI coming fromg having an AI prediction type with high precision is unlimited. The previsions of income help to prepare in the best way the supply chain and the inventiry managment, based on the future needs linked to the necessity of components. Knowing if the return will be lower than the predictions can alert the production direction in order to start an increase of the provision that satisfies the needs of the demand. The previsions of the income is a complex data problem, and the artificial intelligence is an excellent instrument to satisfy this uncertainty.

For example, SKF is a multinational manifacturing corporation, so it needs to predict with precision the end market size of the products, and the demand of specific types of products.

“Which products should manifacture the company and in which quantities? Where should it invest or disinvest and how should respond to the developments in this sector? The AI helps us to answer this questions.”- Fritz Ulrich Dettmer, Manager of Business Intelligence, SKF

Augmented and virtual reality

Whith the constant improvement of the augmented and virtual reality technologies, with big companies who develop devices for this market, the manifacturing industry will soon adopt this type of immersive technologies. The virtual reality can help to better train those in charge in the production to make assembling or preventing maintanence tasks. The augmented reality give reports in real time leaded by the automatic learning, in the factory or in the application field, helping to rapidly define the defective products and the operative improvement areas. The production applications AR/VR are infinity and can have a significant role in the resolution of the nowdays challenges.

Managment of energy

The AI can help in the managment of energy. Most of the engeneers don’t have time to analyse the cost and the energetic use of the factory. Having a software of artificial intelligence which exam the energetic use of a production operation can significantly reduce the operation costs. The reduction of the costs can leave more capital for the improvement resources of processes that can bring an higher quality and income.

Fonte web 2022 | Autor of article Andrea Ghedin