At present, the manufacturing industry uses a minuscule of data collected. Still, with the adoption of IoT coupled with Big Data capabilities, the AI transformation processes are changing the landscape of Automotive Manufacturing significantly.
It's important to understand that when algorithms are self-learning, the data is an asset. Therefore, the role of data is now more critical than ever, and it can potentially create a competitive advantage.
The new era of technological advancement is here, and the technology that is making it possible is Artificial Intelligence (AI), which has the potential to change every field and industry in the coming years.
Artificial Intelligence (AI) has already touched all of us in one way or another, whether it's Google Maps, Spotify, or Alexa. Although AI as a technology has been in the works for decades, it has been in recent years that it has started to make its impact felt in every industry. This has been possible only because of technological advancements in computational powers and the designing of new machine-learning platforms.
AI has enormous potential to transform every industry by automating repetitive learning and discovery through data. Instead of just automating manual tasks, AI performs frequent, high-volume, computerized tasks. And it does so constantly, reliably, and without any sort of fatigue. AI adds intelligence to existing products by getting the most out of data. This holds true for the automotive manufacturing industry also. Although automation has been a part of the Automotive Industry for decades with AI, it is different works based on data, machine learning, and algorithms that help produce the desired outcomes.
Artificial intelligence (AI) holds the promise of revolutionizing the manufacturing process in several key ways, bringing in a new era of efficiency and innovation on factory floors. Traditionally, the manufacturing sector is slow to adopt new technologies but is now realizing the immense potential of AI and has started adopting it and integrating it with their processes gradually.
Automotive Industry has traditionally been labor-intensive, with the manufacturing of hundreds of various parts consisting of different materials, shapes, and sizes.
AI can drastically improve overall efficiency and produce superior results by employing a mix of robotics, human-machine interactions, and quality assurance parameters. This would affect the working of entire production and Assembly lines in the Automotive Manufacturing industry.
Use cases of AI in the Automotive Manufacturing Industry
1. Automation of manufacturing process
collaborative robots work in conjunction with humans in the shared assembly space. Robots can easily handle manual, labor-intensive tasks like welding, painting, and component assembly with great speed, precision, and safety. These robots can also identify defects and irregularities in materials and components used for production and raise alerts if necessary.
2) Enhanced quality control
AI systems closely and continuously inspect and analyze finished products and identify defects with pinpoint accuracy. This ensures the production of only high-quality products while reducing the risk of faulty items reaching customers. By focusing on data rather than complex AI systems, manufacturers can enhance their operations significantly. AI can continuously monitor data from factory operations, enabling real-time analysis and early detection of anomalies and patterns that might be imperceptible to human operators.
3) Maintenance predictions
AI's ability to monitor equipment and machinery through Data Analysis can predict equipment failures and maintenance requirements well in advance, reducing downtime.
4) Warehouse sorting & management
The addition of robots in the warehouse has enabled them to automate a considerable part of the logistics network where these machines can track, lift, and sort items. It is instrumental in reducing costs and improving quality control, besides maintaining traceability.
5) Fleet monitoring system
AI can collect and compile complex data from various sources to figure out patterns not possible by ordinary human beings to automate and enhance the decision-making process regarding fleet management.
6) Shop floor monitoring system through AI-based video analytics
AI-based video analytics has many more use cases beyond just building surveillance and security purposes. In fact, with new integrated computer vision, surveillance systems, along with AI, can take smart and immediate actions, making the shop floor a much more safer place for the technicians and workforce. For this, AI systems have transformed data into operable entities by assigning intelligent attributes; the algorithm can undertake data segmentation and establish patterns from the derived data sets. These systems use real-time feed and historical data to understand ideal behavior and violations and, in case of any variations, can raise an immediate alert, thereby drastically reducing any chances of accidents or mis-happenings on the shop floor or in the entire assembly lines.
In conclusion, artificial intelligence is reshaping manufacturing by improving the overall design processes, automating labor-intensive tasks, predicting maintenance needs, ensuring product quality, and warehouse management, among others.
Artificial Intelligence has come as a blessing for multiple industries, including the automotive industry, and the way it is evolving and transforming the manufacturing landscape, it can be safely implied that it is no longer optional for the Manufacturing Industry to adopt it, but they are forced to do so, for their own survival.
The author is AVP (IT) at Imperial Auto Industries Ltd., leads key IT projects, including SAP S4 Hana and cloud-based solutions.
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