Automated Anomaly Detection in Manufacturing

For most manufacturers, detecting issues or identifying defects in product manufacturing is a cumbersome process with a high potential for human error. As manufacturing facilities become smarter and increasingly automate their production processes, Industry 4.0 technologies are helping to improve production efficiency.

What is Anomaly Detection in Manufacturing?

Anomaly detection identifies unique deviations within data collected from systems or processes. In manufacturing, anomaly detection can help analyze events or patterns attributed to the abnormal performance of machines or processes.

From start to finish, the manufacturing process requires:

• Facilities to house manufacturing equipment
• Tools and machinery to produce parts
• Staff to operate machinery and manage production lines
• Personnel to assemble parts into products and conduct inspections

Considering the level of orchestration and process design in manufacturing, identifying anomalies early can help improve outcomes and meet the desired high-quality product specifications. Anomaly detection is also essential to preventing machinery from breaking down or staff not heeding system warning signs.

Detecting Anomalies in a Haystack of Data

You can also think of anomaly detection as the tool that helps you find a needle — the anomaly — in the haystack of data collected from multiple sources across your manufacturing facility.

As machinery and processes become more complex and automated, traditional tools like condition monitoring (CM) are insufficient to detect manufacturing anomalies robustly. CM tracks deviations in parameters like temperature, pressure, and vibration, but there’s often too much data to manage throughout the manufacturing process – that’s where real-time data collection with computer vision comes in. 

Using machine learning (ML) models, your manufacturing facility can leverage artificial intelligence to identify patterns across the data collected from each production process. You will be equipped to pinpoint anomalies and outliers across production and address them in real-time. 

In the Industry 4.0 age, automating anomaly detection takes the guesswork out of condition monitoring.

Computer Vision for Automated Anomaly Detection

alwaysAI Smart Manufacturing computer vision solutions provide automated anomaly detection. Computer vision (CV)  simplifies how manufacturers track production activities and provides greater visibility into each manufacturing stage. This is because CV’s adaptable machine learning technology can be trained to recognize or identify virtually anything.

In many cases, the cameras and sensors installed at manufacturing facilities are used retrospectively, to identify sources of safety incidents or track specific product issues. These cameras are under-utilized. Equipping them with computer vision will improve manufacturing processes in real-time.

When it comes to condition monitoring, computer vision takes object detection in manufacturing to a new level. With CV tools, manufacturers can deploy anomaly detection and simplify how they evaluate each aspect of production and manufacturing.

alwaysAI computer vision leverages artificial intelligence (AI) to train the cameras at your manufacturing facilities, dramatically improving data collection throughout production. It can help you identify issues such as:

• Labor disruptions at the production line 
• Safety issues and potential accidents within the facility (e.g., whether required personal protective equipment is worn by employees, spills that can cause injury)
• Product defects
• The health of essential production equipment 

Based on the data collected from these observations, you can make reliable decisions about improving process design or optimizing specific steps during production. For instance, with increased labor shortages, consistent staffing gaps on the production line might require redistributing personnel. Additionally, alwaysAI Smart Manufacturing can help identify equipment nearing end-of-life cycles long before they break down.

Computer vision enables anomaly detection solutions to differentiate between data pointing to pressing concerns and minor issues. And machine learning continually refines the system’s sophistication and success. As such, alwaysAI’s computer vision tools enable managers to make quick decisions and address these anomalies.

Benefits of Leveraging Computer Vision for Anomaly Detection

Although manufacturing is fairly repeatable, aspects such as designing and prototyping new products and scaling up production are constantly evolving. Data-driven insights into which improvements provide the most value will improve production efficiency and help you remain adaptable amidst all the changes.

Let’s look at two ways computer vision and Industry 4.0 technologies enable robust anomaly detection.

1. Product Quality Control

Before packaging and shipping products, manufacturers must verify that each item meets the required product standards. However, manual visual inspection can be tedious, even for the most experienced quality inspector. Robotic quality inspection may be challenging if your facility is insufficiently staffed to operate the robots.

Microscopic inspection of small product parts also takes significantly longer to complete when conducted manually than automatically. For example, complex parts like circuit boards are built from multiple components that must be assembled in a specific way for the final product to function. With automated CV visual inspection solutions, it is much easier and faster to identify product defects. 

Manufacturing quality control also extends beyond products to the packaging and labels used for each product. If you do not identify defects such as mislabeled products or damaged packaging early in the process, you risk delaying shipping to customers.

2. Productivity and Efficiency

Manufacturing is an inherently complex process involving many steps that must be continuously monitored to minimize production delays or product quality issues. 

These steps typically include:

• Delivery of raw materials to manufacturing facilities 
• Production of product parts in these facilities
• Assembly of these parts into the final product
• Inspection of products to evaluate their quality
• Packaging of inspected products in preparation for shipping
• Shipping products to customers

Computer vision anomaly detection enables you to collect real-time data on each process so you can address issues as they occur instead of causing further delays. 

CV can also help streamline ordering for raw materials and ensure a constant supply for production. Immediate alerts can notify staff when the raw materials are running low to ensure maximum efficiency. 

CV-guided anomaly detection is also useful when evaluating productivity across the assembly and production lines. Manufacturing involves multiple people, processes, and tools, making it challenging to track issues related to productivity. For instance, assembly line processes may require human labor, whereas some production stages may be automated. Understanding patterns in productivity at each process requires robust, real-time data collection and analytics.

By identifying outliers at each step of production before inspection, you can instantly optimize upstream processes without waiting until you discover significant batch quality issues.

Automate Anomaly Detection with alwaysAI

Automating anomaly detection will help your manufacturing facility improve production efficiency and reduce unnecessary costs. Adopting computer vision tools tailored to your specific production environment will help detect product defects and manufacturing inefficiencies early on, providing you with a high technology ROI.   

To learn more, speak with an AI expert today.