JULY 20258 BUILDING A STRONG COLLABORATIVE FRAMEWORK FOR ARTIFICIAL INTELLIGENCEOnce confined to the domains of science fiction, artificial intelligence (AI) has since come a long way in imitating intelligent human behavior. From transportation to manufacturing and production processes, the advancement of AI has led to profound changes in the world of mobility and motion.The use of AI can be grouped into rule-based systems and highly complex systems based on Machine Learning and Deep Learning algorithms. This enables the processing of data where these algorithms can draw patterns and make predictions such as visual inspection, predictive maintenance, and sales forecasting.For the automotive and industrial sectors, these developments have led to greater interest and demand for more intelligent offerings and are paving the way to entirely new production and service concepts. For instance, improved connectivity and Internet of Things (IoT) applications have led to the development of remote condition monitoring and predictive maintenance. These lead to higher efficiency gains and better reliability, ultimately improving production quality. Likewise, we expect that around 30% of all new passenger cars and light commercial vehicles produced in the world will be partially automated in the automotive sector. Moreover, half of them will have the capability for highly automated driving. Creating A Robust Artificial Intelligence FrameworkIn light of these developments, there is a stronger emphasis on leveraging data science and analytics to enhance processes and productivity. To best utilize these opportunities, industrial players should implement a robust artificial intelligence framework and strategy to strategically optimize the use of AI for crucial insights and increased efficiency and agility. At Schaeffler, we have anchored our AI strategy based on six guiding principles: Organization, Talents, Ecosystem, Value, Codex (Code of Ethics), and Processes. These six guiding principles allow us to strengthen our AI capabilities, focusing on business-value delivery and requirements while establishing trust and competencies among our employees. For instance, by intelligently integrating AI and machine learning in operational processes and the cloud, we continually optimize various aspects of our plant operations, including our maintenance cycles ­ allowing us to achieve significant reductions in throughput times at our manufacturing plants. As we look to better support our employees in their daily work, we are also working on advanced, intelligent assistance functions that enable natural language interaction between humans and machines.IN MYV EWBY BOON SIEW HAN, REGIONAL HEAD OF HUMANOID COMPONENT BUSINESS & R&D (APAC & GREATER CHINA), SCHAEFFLERBoon Siew Han
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