At the height of the 2020 supply chain crisis, 75% of organizations faced disruptions in their supply chains. 44% of organizations had no clear strategy to manage these disruptions. 

With their global reach, modern supply chains have become large and complex. And Gartner reports that 50% of business enterprises have not yet prepared an effective roadmap to transform their supply chains. 

In the digital age, companies need a 360-degree view of their entire supply chain network. This includes automatic tracking of raw materials or components (from global suppliers) and delivery of the finished product to the customer. Organizations must address any visibility-related challenges in their supply chains to achieve maximum efficiency.

Can Computer Vision (CV) technology improve modern supply chains? Let’s discuss this in this article.

How Is Computer Vision Transforming Supply Chains?  

Powered by Artificial Intelligence (AI) technology, CV is transforming how enterprises manage their supply chains. Using both image and video analysis, CV can identify supply chain problems and optimize the process for maximum efficiency. Valued at $5.6 billion in 2021, the global market for AI in the supply chain is projected to reach nearly $21 billion by 2028.

Using AI technology, computer vision is used to train machines to identify real-world objects using connected cameras and sensors. CV-enabled systems can perform multiple tasks, including the following:

• Detecting physical objects and movement
• Classifying images based on data labels
• Segmenting images based on selected criteria (for example, color or size)
• Recognizing images based on variables like objects, location, and more.

How do AI-enabled computer vision technology benefit supply chains? Here are a few benefits:

• Improved operational efficiency through real-time tracking
• Reduced costs due to supply chain automation
• Acceleration in manual processes across the supply chain, thus improving speed in delivery
• Complete operational visibility and transparency over the entire supply chain network

Next, let’s look at five real-life use cases of computer vision in supply chains.

1. Workplace Safety

Worker safety is of paramount importance in manufacturing-based supply chains. CV-enabled cameras can detect if workers are wearing their personal protective equipment (PPE), like safety helmets and protective glasses. And CV systems can immediately notify floor managers if workers are not following safety norms.

AI-enabled CV enables geofencing (or virtual boundaries) around dangerous equipment and facility areas. It can also raise alerts when unauthorized personnel enter or come too close to these areas. Using connected cameras, CV technology can help supply chain operators to optimize their workflow, thus reducing worker injuries and boosting workplace safety.

2. Equipment Monitoring 

The AI-based visual inspection enables manufacturing companies to improve their defect discovery by 90%. As compared to manual maintenance by human engineers, CV systems enable automatic monitoring of manufacturing equipment around the clock. This enables maintenance engineers to pre-emptively fix equipment defects.

CV technology also enables predictive maintenance that eliminates the costs of machine downtime due to malfunctioning. Additionally, proactive monitoring saves supply chain companies from high maintenance costs and downtime.

3. Shipment Tracking

Smart tracking application (along with computer vision technology) can track shipments and logistics. It can accurately track shipped goods, containers, vehicles, and the personnel (in charge of delivering the product). Using optical codes and barcodes, CV systems can track shipments through image processing algorithms.

Similarly, using the camera data at various locations, CV solutions can also count the inventory being received. At any given time, CV solutions are more accurate and reliable than human personnel.

Also Read: 7 Applications for the Power of Computer Vision in Modern Retail Operations

4. Inventory Management 

With more demand fluctuations, organizations are adopting AI-based solutions to address any issues in inventory management. The current global uncertainty is likely to cause more disruption in supply chains and inventories.

CV-enabled solutions can bring more visibility into inventory management. CV-connected cameras can easily scan images of inventory stocks and assess the product’s condition and shelf life. Through barcodes, CV tools can minimize inventory losses and track the movement of inventory across the supply chain.

5. Product Quality 

Manufacturing and supply chain operators incur high production costs and inefficiencies for defective or low-quality products. This, in turn, can adversely impact operational efficiency.

Manufacturers can now deploy CV-powered cameras to capture real-time video images and thermal imagery of their production lines. Computer vision platforms can aggregate and analyze production data to determine the “root cause” of the low-quality product. Using AI models, manufacturers can leverage real-time data to check if any production equipment is working slowly or is malfunctioning.

Conclusion

With every passing year, computer vision is slowly changing the face of supply chain companies. Using computer vision technology, manufacturing companies can navigate through uncertainties of modern supply chains and stay ahead of market demand. Intelligent camera-powered solutions can increase visibility over supply chain operations.

KamerAI provides a real-time computer vision-based automation platform for business enterprises, including supply chain companies. At KamerAI, we have the technology to make sense of your visual data. 

Explore how our Computer Vision solution can transform your supply chains. Contact our KamerAI consultant today!