Using Automated Visual Inspections to Enhance Manufacturing Quality

We all know that quality control is a critical component of manufacturing, ensuring all products coming off the line are made correctly for the customer. One of the many ways manufacturers ensure quality is inspections: visual inspections conducted by humans, and an automated visual inspection (AVI) system powered by technology.

Visual inspection in manufacturing processes has long relied on basic human senses to visually examine materials and products to identify any anomalies or defects. Humans also report on the findings and determine next steps, often leveraging digital tools and mobile apps to input and analyze these results.

But relying on people alone is no longer practical. In this post, we focus on automated visual inspection systems: how they work, specific use cases, and how they complement human oversight to enhance manufacturing quality.

What Are Automated Visual Inspection Systems?

An automated visual inspection system can perform many inspection tasks with cameras and sensors, which are typically augmented by technologies like artificial intelligence (AI), machine learning (ML), and computer vision. These systems can automate the identification, review, and analysis of product anomalies or problems, often finding issues that manual processes may overlook.

(In the 2025 “Shaping the AI-Powered Factory of the Future” research report from the Manufacturing Leadership Council, 72% of manufacturers surveyed said they’re currently using AI solutions in the form of a vision system, which it defined as “AI that processes and interprets visual data from the world, such as images or videos, enabling tasks like facial recognition, object detection, and quality control in manufacturing.”)

While these systems can go a long way to enhance operational efficiency, increase production, improve worker safety, and reduce costs, they’re not perfect. Human inspectors continue to play a critical role in overseeing manufacturing quality control alongside these systems. 

Product inspections are essential, but not enough. Learn how process and skills verifications prevent quality escapes and accelerate continuous improvement.

How Automated Visual Inspection ​​Works

Automated visual inspection systems have existed in some form for several decades, traditionally relying on cameras and sensors to detect quality issues. Early systems were limited in their visual data processing abilities and were often costly to implement.

Today, advances in cameras, sensors, and lighting technologies, alongside AI and ML, have made automated visual inspection systems a lot more accurate and appealing to manufacturers across a variety of industries. In fact, the market for these systems is expected to reach nearly $30 billion by 2029.

Automated visual inspections involve the use of cameras, with the help of precise lighting, to capture high resolution images of a product across multiple angles. The images are processed using AI, ML, and computer vision to examine whether any anomalies or defects exist. A determination is then made on whether the product can move forward or must be scrapped.

All of this data is then fed back into the automated visual inspection system’s algorithm for continuous improvement. This data can also be incorporated into a manufacturer’s reporting and auditing dashboard to inform necessary manufacturing adjustments and proper next steps.

AVI System Components

There are several key components of an automated visual inspection system across hardware and software.

Necessary hardware components include:

• High resolution cameras for image capture.
• Infrared sensors to identify any heat abnormalities that could impact the product.
• Specialized lighting to ensure precise, quality images that are not impacted by shadows.

Necessary visual inspection software components include:

• Advanced image processing algorithms to analyze the captured images.
• Real-time data analytics to provide manufacturing insights and suggested next steps.
• ML models to improve the system over time.

These software tools are used to complete surface inspection, product measurement, and more to ensure adequate quality assurance.

These sophisticated platforms can be seamlessly integrated with existing industrial systems and are an important component of digital transformation initiatives in manufacturing. When implementing an automated visual inspection system, it’s important that the image processing algorithms are properly trained with high quality data that incorporates human oversight to refine the algorithms for ongoing learning. This ensures the accuracy and reliability of the system in properly identifying product defects or other issues.

Types of Automated Visual Inspections

Across the inspection process, there are two main types of automated visual inspections:

• Dimension inspection: These inspections involve the measurement of a product and its components. This type of inspection is fairly straightforward since it relies on a product’s specs to determine whether it has been properly manufactured. This is especially important in industries that require high precision, such as automotive, aerospace, or medical device manufacturing.
• ​​​Surface inspection: These inspections focus on identifying irregularities in, or damage to, a product’s surface area. This process requires very specific instructions on what to look for. Surface issues may include cosmetic defects like scratches, dents, or discoloration. There may also be structural defects like cracks or process issues like product residue.

Advantages of Automated Visual Inspections

Human inspectors are an invaluable resource on the factory floor, but there are several factors that may result in human error or challenge their ability to provide thorough, consistent product inspections and quality control on their own. This might include fatigue, distractions, or their own level of familiarity with the production or inspection process.

The inherently subjective nature of each person’s unique experiences and biases also can impact the results of human-led quality checks, which highlights the critical need for standardization throughout the quality control process. Additionally, potentially unsafe or undesirable conditions may compromise a person’s ability to conduct needed inspections.

Automated visual inspection systems have become a key component of Industry 4.0 and smart factories because they can often deliver more consistent quality control with greater accuracy. Additionally, automated visual inspection systems may detect anomalies that the human eye either cannot, may miss, or may identify too late in the manufacturing process. As needs scale, manufacturers may be limited by the availability of trained frontline workers to complete inspections. Automated visual inspection systems provide a reliable alternative that can be scaled up or down. They also can be deployed in environments where worker safety or wellbeing might be at risk.

Automated Visual Inspections for Many ​​Industrial Sectors

Automated visual inspection systems can be a valuable manufacturing tool across a variety of industries, especially those that require precise production with high-stakes consequences if a defective product goes undetected.

Let’s examine a few sample applications:

• The aerospace industry requires high levels of precision to ensure optimal flight performance and safety. Automated visual inspection systems can be used to detect surface level defects on plane equipment that may not be immediately apparent to the human eye.
• The home goods industry is incredibly competitive, requiring speed to market and leaving little room for quality issues. Automated visual inspection systems can check for material quality and dimensional accuracy, enabling manufacturers to identify and address issues in real time. Together with human oversight, automated visual inspection systems can ensure products are made quickly and meet increasingly high customer standards.
• The food and beverage industry must balance rigorous safety standards alongside evolving consumer preferences. Automated visual inspection systems can be used for a wide range of applications in this sector, like ensuring proper labeling, packaging integrity, or identifying contaminants on the production line.
• The pharmaceutical industry has extremely strict regulatory requirements to ensure the safety of products. Pharma companies can leverage automated visual inspections to identify labeling errors, incorrect tablet shapes, or any chips or cracks within the vial or packaging.

AVIs Are Not Entirely Replacing Humans Inspections

While the benefits of these systems are significant, human inspectors remain a critical resource for manufacturing production quality control. People have institutional experience and knowledge — often gained through years working on the manufacturing floor — that no machine can currently replicate. Humans also bring a unique ability to make nuanced judgements in the moment that automated systems may not properly identify.

The key here is making sure human inspectors follow standardized processes during inspections and that every identified issue triggers appropriate follow-up. Consistency in how inspections are performed helps reduce variability and ensures reliability across shifts, teams, and sites. Equally important is closing the loop and tracking issues through resolution to prevent repeat problems.

By combining human inspectors and standardized processes with automation technologies like AVI systems, manufacturers can be more confident about product quality, which increases customer satisfaction and, ultimately, the bottom line.