Automotive

One of the major issues with conventional quality control in production is substantial operational costs, mostly due to reworked parts, wasted material, reduced yield, increased work in process inventory, post-sale recalls, warranty claims, and repairs. AI has now proved to be the best and most trustworthy technology to successfully inspect the components of a vehicle. And since it’s constantly learning, its performance gets continuously enhanced as its use in industry soars.

Conventional visual inspection is performed through a manual process which is time-consuming, prone to errors, subject to operator perception and experience (impact consistency), blocked by the programming step(not flexible and cannot adapt to product changes), and can only detect a handful of defects at a time. Employing AI in QC reduces cognitive load for operators, minimizes false positives, doesn’t require programming, adapts to product changes, and can detect hundreds of areas of interest on a product in seconds.

AI-powered visual inspection helps automakers inspect foundry engine blocks (for cracks, deformations, anomalies), body shop welding seams, paint shop surfaces, press jobs (for scratches, dents, cracks, staining), and more. There are countless opportunities to leverage the power of AI-assisted systems, even in decision-making roles. Some of the use cases for AI in QC are:

1. Detecting casting defects: The engine block, intake manifold, and cylinder require different cast aluminum alloys, to form the essential components of a car’s internal combustion engine. Usually, a team of operators determines whether any engine components are defective. However, they lack consistency and defective blocks are occasionally shipped to the client resulting in heavy penalties and knock-on effects for the production facility. AI-powered systems can automatically inspect all the processes involved in turning the raw material into an engine block, and locate and classify defects on components including those the computer is seeing for the first time.
2. Detecting CNC machining defects: Since CNC machines can work with a wide range of materials, they are extensively employed in the manufacturing of automotive parts. They are also used for rapid prototyping and the production of other essential automotive parts such as starter motors. For instance, CNC machining is a great option for manufacturing gearboxes since a high level of precision is required and the slightest error during manufacturing may result in misalignment, gear wear, and failure. Nowadays, most carmakers are replacing old-fashioned gear-making processes such as hobbing, with precision CNC machining which enables them to rapidly produce high-quality gears and eliminate the need for additional post-operational tasks at the same time. The main Advantages of precision CNC Machining are high production speed, less human intervention, excellent accuracy and precision in fabricating the most complex auto part designs, and supreme repeatability without any discrepancy since CNC machines rely on 3D CAD models and computer instructions. Modern CNC machines can now be equipped with our AI-powered solutions, allowing the machines to self-diagnose faults and reduce downtime. This innovation has also improved the quality and consistency of machined car parts.