AI, Machine Learning Offer Manufacturing Real Solutions

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Artificial intelligence (AI) and Machine Learning (ML) are opening new possibilities to the world’s industries, including the automotive sector. Once these technologies reach their full capacity and create an integrated ecosystem, all the automotive supply chain could reap substantial benefits.

“The technology is already here. Mexico’s problem is that while it some sectors are boosting Industry 4.0, Industry 1.0 is still rampant in others. The automotive sector is advancing toward AI and ML but we need to change the mindset of companies. Sometimes people think that this technology is highly expensive or complex but there are numerous tools available for Tier 2s,” said Sergio Bautista, Robotics Local Business Unit Manager of ABB.

The pandemic, technology and changes in consumer behavior are disrupting the operation and processes of companies. Automakers, suppliers, dealers and everyone involved in the supply chain need to adapt to changes, taking advantage of the new technologies powered by data.

Despite not necessarily being electric, new-generation vehicles are getting smarter thanks to software and telematics systems that generate data and connect with other vehicles. “Analytics and big data are starting to focus on specific industries in Mexico. We have hyperconnectivity, with huge amounts of data being generated. The right connection and use of this information helps lifecycle management, processes design, supply chain management and manufacturing processes,” said Javier Vallejo, Senior Manager of Architect Solutions of AWS.

AI is not only used for autonomous vehicles, it is also useful for forecasting, according to José Rivero, Country Manager of Infor. “The pandemic taught us the importance of assertive forecasts,” which based on ML motors and analytics models could predict future demand with precision. Manufacturing plants continue adding sensors and “collecting tremendous amounts of data,” said Rivero. These sensors enable companies to know how machines are working in real-time and forecast the ideal moments to do preventive maintenance, saving time and money.

Telematics offer similar benefits when used in vehicles in movement. Sensors in vehicles provide information about the car’s health, ideal maintenance times and drivers’ behavior. AI came to change every part of the automotive industry, from manufacturing to sales, fleet management, insurance companies and autonomous vehicles.

AI solutions are being offered “to clients looking to give their customers a plus, aiming to reach the highest standards of quality,” said Abraham Sosa, Director of Global Accounts in Latin America at Universal Robots. Collecting data is key to take well-informed decisions. However, collecting information is not enough.

“Data is vital in the manufacturing process. You cannot improve something that you did not measure to know its exact condition. Integration to an ecosystem is needed for a future intelligent plant that is able to automatically control processes, stockage, budgets and forecasts,” said Ricardo Anaya, Product Manager at Qualcomm.

Volkswagen, one of the most important employers in Mexico with over 15,000 employees in its two plants, has already started a digital revolution in its plants across the world. The German automaker will invest US$1 billion during the coming years in its three plants in North America to successfully implement technology such as cloud software, intelligent robots and AI, which require exhaustive training and capacitation. With the unified software launch, Volkswagen will be able to optimize collaboration between its plants, upgrade the work environment for its employees and suppliers and improve the manufacturing process in general.

Adaptability is key. It is not only about OEMs or Tier 1s, companies need to know how data influences the entire supply chain. “Volkswagen is connecting its 120 plants with over 500 suppliers in on single data protection strategy to speed up the complete process from the beginning to the final consumer,” said Vallejo.

The main challenges that AI and ML face both in Mexico and the world are the standardization and homologation of information, agreed industry experts. “People talk about a fully integrated ecosystem, but this is idealized; it still does not exist,” said Bautista. Mexico does not lack people talented in data science. Electrification and new tendencies in the automotive sector will change the industry. AI and ML will have to keep up with the new needs and different processes that OEMs are implementing, said Bautista.

Technologies such as AI and ML are yet to see their best, full potential, according to Sosa, but to reach it companies need to trust the technology solutions offered. “We have to traduce the solution created with data into something applicable to real life and have a technology-flexible client to test the solutions offered,” said Sosa.

The biggest challenge is not developing new technology but to smartly use the one already available, according to Vallejo. Tech managers and company decision makers need to clearly identify which pieces of information are the ones needed to make the decisions and “avoid the temptation of activating hundreds of alerts that will not really help. It is important to focus on key pieces of data,” said Vallejo.

Data translation into real solutions is only possible with hard, prolonged work, agreed experts. Integration and the creation of a connected ecosystem will play key roles in the following years for the automotive industry.