This article will discuss how Virtual Inspection AI will help improve the productivity of a manufacturer.
Companies involved in manufacturing tech or any form of commodities at a large scale often need an inspection that can detect even the minute defect during the process of production. The reason behind this is to ensure that the final product has zero defects and has a smooth running of the product when the end user is using the product. To ensure that even the smallest of defects is being attended to by the manufacturer. Use of visual inspection artificial intelligence comes into use. This deduces the generation of poor quality products, scraps and the financial cost related to these factors. It also increases the productivity of an organization’s process inventory, post-sale recalls, warranty claims and repairs.
Google has developed a technology that will help companies achieve these goals in a cost-efficient and accurate production. Google has launched a Visual Inspection AI solution that will take the help of Google’s artificial intelligence and computer vision technology to help companies solve problems related to production scale. In this article, we will look in detail at how Visual Inspection AI helps companies solve problems related to production.
How does Visual Inspection AI work?
Google’s Visual Inspection AI makes the inspection process automated as it uses AI and computer visual technology that helps the manufacturer quickly detect any defect that occurs during the process of assembly and other steps when the product is being manufactured in a factory outlet. Google has built this technology to meet the needs of quality, test, manufacturing, and process engineers whose work is made easy as they can use AI to inspect the production process of a product in less time. There are some of the benefits that are found when AI is used in the production process. These benefits are mentioned below:
- Inspection process is automated: Visual Inspection AI can be run by the manufacturers on-premises or on the network edge of the factory outlet. They can run the inspection either in Google Cloud or can also opt for full automation.
- Flexible Time: Manufacturers can deploy the inspection in weeks or days. This gives manufacturers the freedom from the traditional monthly quality checks that were used for traditional machine learning solutions. This technology does not require an experience of traditional machine learning or computer vision experience as interactive user interface guides are there to help the users in every step.
- Cutting Edge Computer Vision and AI Technology: According to Google Cloud’s article on Visual Inspection AI, this technology has improved accuracy by up to 10X than the use of general-purpose machine learning approaches. This data is based on several Google Cloud’s customers. It is able to detect any kind of defect with the support of high-resolution images (100M pixels) and cutting-edge computer vision technology.
- Easy to Start and Setup: Visual Inspection AI is capable of building with up to 300x fewer human-labeled images of defects than general machine learning models. This is another feature that can help increase the production rate and increase the quality of the product.
- Detects Multiple Defects and Lessens Human Intervention: This technology has a deep learning ability that helps customers train models that detect and classify multiple defects by scanning a single image. It also allows AI to automatically perform follow-up processes in the production line without any human intervention.
Industries That Can Use Visual Inspection AI to Improve
The technology used in creating Visual Inspection AI has made this product a flexible product that can cater to various industries that need large-scale and medium-scale production lines to fulfil the never-ending demand for the products they offer. Due to this feature, there are various industries and companies that have already adopted this technology and are witnessing a change and improvement in their production lines. Some of the industries that are using Virtual inspection AI in their factory outlet to improve their product testing department:
- Automotive Manufacturing: The Auto industry use this technology for paint shop surface inspection, body shop welding seam inspection, and press shop inspection such as scratches, dents, cracks, and straining. Foundry engine block inspection specifically for cracks, deformation, and anomalies.
- Semiconductor Manufacturing: Semiconductors, a crucial part of any technology also use Visual Inspection AI for wafer-level anomaly and defect localization, die crack inspection, pre-place inspection, SoC packaging inspection, and board assembly inspection.
- Electronic Manufacturing: Electronic manufacturers have also adopted this technology. They use this technology in the field of defective or missing Printed Circuit Board (PCB) components (screw, spring, foam, connector, shield and other components.), PCB soldering and gluing (insufficient solder, Icicle, shift, exceeding tin), product surface check (glue spill, mesh deformation, scratches, bubbles).
- General-purpose manufacturing: AI inspection is used even in the final stage of the production line. It is used for packaging and label inspection, fabric inspection (mesh, tear, and yarn), metal and plastic welding seam inspection, and surface inspection.
Virtual Inspection AI can be used by customers to run any kind of inspection on any level of their production line and witness an improvement in their production facility.
What Do the Clients Say About Virtual Inspection AI?
There are different clients that are using Virtual Inspection AI in their production line and here are some words from the company’s managers about this technology and how it has improved their production and also reduced waste in their production line.
FIH Mobile, a subsidiary of Foxconn is the global leader in headset and wireless devices manufacturing and services. They have been using Virtual Inspection AI since 2021 and according to Sabcat Shih, Senior Associate Manager at FIH Mobile “it’s been amazing to work with Google Cloud to bring innovative machine learning and computer vision technologies to our quality processes,” he further adds “Engineers from FIH Mobile trust Google Cloud and we are achieving considerable product improvements through our collaboration with your teams. We cannot wait to roll the Assembly Inspection solution further across our extensive PCB manufacturing operations”.
There is another company called Kyocera Communications Systems, a system integrator offering various IT solutions, which has collaborated with Google Cloud and has also shared their experience using Virtual Inspection AI and here is what they have to tell about it. Through the use of Virtual Inspection AI, the company has been able to scale its AI and ML expertise. Masaharu Akieda, Division Manager, Digital Solution Division, Kyocera Communication Systems says “With the shortage of AI engineers, Visual inspection AI is an innovative service that can be used by non-AI engineers, we have found that we are able to create highly accurate models with as few as 10-20 defective images with Virtual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers’ digital transformation projects to success.”
With introduction of AI by Google Cloud to simplify the training process of the machines involved in the production line and also increase the productivity of manufacturers is a revolutionary step that can help improve the production rate and reduce the waste generated in the process of producing a product. It will also reduce the time taken to manufacture a product and also ensure good quality of products. This is all you need to know about Virtual Inspection AI.