E-commerce logistics
Problems with palletizing in e-commerce
Repeated faults and stoppages in automated processes lead to frustration and loss of valuable production time. This is regardless of whether it is about manufacturing or packaging, the automotive industry or e-commerce.
A not uncommon error in e-commerce is problems with palletizing. The purpose of a palletizer is to automate the manual work of stacking products on pallets. But if something goes wrong in the automated flow, no one sees what actually happened
Time-consuming with a regular camera
Troubleshooting then requires both time and knowledge. Popular methods are the root cause analysis, the 5-Why method and fishbone diagrams. However, all principles require underlying information about what actually happened. The visual information can be provided by video recording. Recording systems are an excellent tool to capture the error and review the problem as many times as necessary to find a solution.
Many then mount a GoPro camera. Most likely, it will help to find the error, but it is a cumbersome and time-consuming process to search in a long video. First, you need to transfer the large video file to computer. Then search through the video for the relevant section. In some cases, you may have eight hours of footage that needs to be scanned without any clear information about when the error occurred.
Eye at Production provides answers immediately
The Eye at Production camera system combines the intelligence of a vision system with the flexibility of a GoPro camera. The system records a video of the entire process but registers and marks deviations, stops and other details based on how you chose to set up the application. Instead of manual monitoring or hours of footage to go through, you'll find what you're looking for right away.
How it works
1. Mount
Mount Eye at Production where you assume the cause of the error occurs. The system is easy to handle and install. The camera has an IP68 rating against drops and dust.
2. Monitor:
Select the mode, for example to detect all stops in the production flow longer than a certain time. Put the system on play.
3. Analyze: