For many years, companies have been digitizing their facilities to improve conditions for operators. However, the opposite is true for the use of artificial intelligence, where many companies have not yet adopted the latest analytical solutions to support better decision-making.

Operators often rely on intuition rather than data and perform multiple tasks at the same time, exceeding their capabilities and leaving room for error. Reliance on experience also poses a challenge in replacing skilled operators when they retire. Using artificial intelligence is an important step to improving operations, as it can adapt quickly to ever-changing conditions and provides accurate, automated decision-making, also in a manufacturing environment.

In this post, we will explore the field of manufacturing and the different transformative opportunities that the application of artificial intelligence brings to this sector. As a company working in the field of artificial intelligence, we want to highlight the most important opportunities that artificial intelligence offers to improve manufacturing processes. So how can manufacturing companies harness the power of AI?

Predictive maintenance

One of the main areas where AI excels is in predictive maintenance. By analyzing data from sensors in machines, AI algorithms can predict when equipment will fail or need repair.

Such predictions enable planned maintenance, which significantly reduces unforeseen downtime and the associated additional costs. The point here is simple but important: problems must be eliminated before they spread in order to ensure a seamless, uninterrupted production process.

Operational efficiency and optimization of resources

Artificial intelligence can be the key to improving and optimizing processes in manufacturing today. By automating the collection, pre-processing, and aggregation of data from different devices, it offers insight into in-depth analytics. In addition, the emergence of digital platforms for real-time monitoring of operations provides new opportunities for resource optimization.

For example, by using interactive dashboards, employees in key positions have real-time insight into energy consumption, which allows them to make more informed decisions that lead to energy savings and, consequently, cost reductions.

Advanced monitoring and analytics

The transition to AI-driven systems represents an advance in the field of monitoring and analytics. There are new "plug & play" platforms emerging that provide customized analytics tailored to the specific needs of the manufacturing sector.

The emergence of MBDaaS (Manufacturing-Big-Data-as-a-Service) innovations, which offer easy-to-use platforms for efficient monitoring and predictive analysis of machine tools, is also an indication of the shift. All these developments address the weaknesses of previous systems and present a single solution that is essential to improve the monitoring and analysis system in manufacturing.

Encouraging the process of digitization

The applications of artificial intelligence outlined above are central to supporting the digitization of the manufacturing sector. Automated processes and open-source software are not just technological upgrades, they are a step towards a more digital future.

They are also an effective and easy transition to digitalization and are aimed both at large companies and SMEs.

Ignoring artificial intelligence can come at a high price, especially for big manufacturing companies. Pioneers such as Google and Amazon have made significant leaps forward thanks to the benefits of AI.

Fortunately, with existing data, combined with external expertise, you can step forward today and secure a strong position in the manufacturing sector.