Digitalization in the metal-mechanical sector is still in its initial phase, that is, it is expected to impact and improve companies even more in the short term. This growth in the industry urges every metalworking company to monitor industry trends and adapt to the new technologies and opportunities that Artificial Intelligence can provide.
Speaking of real numbers, a study by McKinsey estimates that digitalization could increase global productivity by 25% by 2025. In the case of Mexico, according to the Mexican Institute for Competitiveness (IMCO) it is estimated that AI in the industry could increase productivity by 20% by 2027.
What is it used for?
The goal of AI is to develop systems and programs that can simulate human intelligence to solve complex problems faster and more efficiently. Within the metal-mechanical sector, companies make use of AI for predictive maintenance on machinery, perform assembly operations, plan production, and warehouse stock, among others.
Let’s take a closer look at some of its most common applications:
- PREDICTIVE MAINTENANCE: Programs and digital systems predict the opportune time when machines need maintenance, this allows companies to reduce machine downtime.
- DEMAND PLANNING: One of the most common activities through AI is the prediction of demand by analyzing the market and certain patterns, this allows companies to make more accurate decisions about data and quantities that customers may require.
- ROBOTIZATION: Through the programming of robots, the assembly of parts can be achieved faster, especially in the automotive industry, reducing errors. Within the automotive sector, we also find machines that find any detail in the car parts before they are assembled to avoid later returning the car for factory defects. This robotization can optimize the use of materials and improve sustainability in production.
Risks of AI in the metalworking industry.
Despite the numerous opportunities offered by Artificial Intelligence and digitalization in metal fabrication, there are also several challenges faced by companies that have implemented these processes, let’s talk about the most common ones.
- SECURITY: AI collects an impressive amount of data, which, with it enables the prediction of certain activities, and such data is often highly confidential. The cyber-attack and risk to the data is very high; therefore, data protection and information security is a major concern in AI implementation.
- LABOR IMPACT: Although human supervision is needed on machinery and personnel for the interpretation of data from AI, the replacement of human workers with intelligent machines could lead to changes in the skills required and, potentially, the reduction of the human workforce.
- COSTS: The cost of implementing and training personnel for this type of technology is usually very high, so it is still a challenge for small and medium-sized companies to be able to implement this in their processes.
Careful planning of all the factors involved in the implementation of Artificial Intelligence can lead companies to achieve great results, gaining a competitive advantage over their competitors.