Since the start of the pandemic, adoption of artificial intelligence (AI) for enterprise business has skyrocketed. Factories in the automotive sector are uniquely positioned to enjoy the benefits of emerging technologies, from predicting machine failures to monitoring supply chain breakdowns. Given this advantage, it’s not surprising 76 percent of manufacturing executives have reported increased adoption of disruptive technologies, including AI and facial recognition technology (FRT), during the pandemic. Today, automotive factories are using FRT to streamline quality control and worker health processes, and meet increased demand amid converging challenges.
A recent White House report noted the automotive supply chain is fragmented across many countries and firms. Transporting some 30,000 parts while ensuring strict quality control measures are met also creates an ongoing challenge. FRT can play a major role in auto manufacturing quality control, because it helps streamline the verification of employees at each stage of the assembly line.
On the factory floor, it’s crucial to verify the correct task is assigned to each employee. FRT supports this need by allowing employees to sign into their designated station with their face. The technology can also restrict access to certain areas or tasks where a specific training requirement is needed. In this way, factories can be certain the right people are working on the right projects. Additionally, FRT can help managers see who might need more training, and, in some areas, ultimately boosting quality of work.
Yet, quality control pales in comparison to employee health, which is key to delivering good products on time. To mitigate transmission of pathogens such as the COVID-19 virus, FRT enables contactless temperature detection, assures proper mask wearing, and conducts health monitoring, allowing auto factories to meet demand at the dealership and safely avoid plant shutdowns. Temperature readings can be done when employees check in, and quickly alerts them if they should go home, removing any doubt they or their employers might have.
In one automotive factory, the manufacturer was looking for a safe way to verify employees’ identity to make quality checks at each step of the production line more accurate and efficient. In the traditional system, employees needed to log in with an ID card when each task was completed before the next car was dispatched to be checked. Unfortunately, the ID card mechanism was easy to cheat, which made it difficult to know which employee was responsible for which task. Even for employees using the right key card, it was a cumbersome, time-intensive process.
As a solution, the manufacturer deployed FRT to automate the process and identify employees along the production line. This was especially challenging to implement when every employee wore a helmet and goggles. Mask mandates, which resulted in even more facial covering, further complicated things.
To overcome this challenge, the company integrated CyberLink’s FaceMe SDK into handheld devices set up at each quality check area. Based on machine learning and deep neural networks, FaceMe delivered an accuracy rate (True Acceptance Rate) TAR of 98.21 percent through masks. It also helped the automotive factory enforce employee safety by not only detecting if a mask was worn but if it properly covered someone’s nose and mouth.
Facing mounting challenges, automakers must look to emerging technologies to ease labor, technological and supply chain pain points. FRT is an easy way to improve safety, security, and ultimately the quality of work to ensure production runs as smoothly as the cars being built.
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