Among all the beneficiaries of Artificial Intelligence, the automotive industry is the one that has harnessed the latest technology to bring efficient, innovative and safe vehicles to market. Also, the industry continues to cut manufacturing costs while using AI in its applications.

From autonomous cars to robots serving factory floors, AI underpinned with other technologies has transformed the industry for better. AI is and will continue to transform major aspects of the auto-manufacturing process including research and design, project management, business support functions, and significant others.

The changes are approaching fast and manufacturers should understand that they need to start developing necessary capabilities to drive an AI-enabled culture for their smart factories.

The technology is used by many manufacturing plants to attain a wide range of predictive capabilities that can enable personalization in the driving experience.

The AI-enabled advancements in computing power will provide machines with capabilities to understand and organize unstructured data including photos, speech, recognize patterns and to learn from past experiences. Through these experiences, they can improve their future performance.

Additionally, advanced algorithmic research along with extremely powerful computer hardware can empower AI to demonstrate autonomy and creativity. It is believed that AI-fueled machines possess the ability to go beyond than just following rules. Such machines can sort out ways to create a solution for complex problems within a provided situation.

The automotive industry seeks ways to discover and increase its operational efficiency to free up capital for smart manufacturing. AI has become a key to streamline business, automating and optimizing manufacturing processes and enhance the efficiency of the supply chain. The use of computer vision, which is one of the technologies that lie under the umbrella of AI, can serve a great purpose in anomaly detection.

Also, AI can enable less equipment failure. In any circumstances a machine fails in the manufacturing process, the cost can be calamitous which can lead to a situation where whole manufacturing plants can be thrown into dishevel. In such a condition, AI-based algorithms can predict the breakdown of a machine by diagnosing the problem through analysis of vibration sensors and other sources, detect anomalies, separate errors from background noise.

At times it can be hard to gauge research and development progress and understand the right time to drop the project in order to free up resources for significant ones. This uncertainty and unclarity can lead to zombie projects which can further burn the money and inflate total R&D costs. Here, AI methodologies can help improve project prioritization and enhance performance within a certain project. Subsequently, budgets will be liberated and overall efficiency will be increased.

As aforementioned, advancements in AI subsets like computer vision can drive better prospects. It can enable progressive collaboration between intelligent robots and humans. Better algorithms and enhanced computing power can lead to the development of flexible, non-special-purpose robots. These robots can work with humans.

Thus, AI-enabled applications deployed in the automotive manufacturing floor can create schedules and manage workflows, enable robots to work safely alongside humans and identify flaws in components going into vehicles. Such capabilities help manufacturers reduce costs and downtime in production lines.

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