✓ Gain cost savings by decreasing the need for manual repetitive tasks
✓ Optimize quality standards and remove manual errors
✓ Automate processes by connecting to systems and machine interfaces
Inspecting object surface to identify possible anomalies or deviations. Works on different surface properties from painted materials, to wood and metal.
Analyzing the dimensional measurements, volume or geometries in real-time can provide big cost saving in the process either by removing waste or increasing the quality.
Making sure all objects are correctly placed, positioned or packaged during the process and autonomously react on deviations.
Identifying and categorizing different materials based on their chemical composition with hyperspectral vision.
Replace time consuming data collection and manual processing by real-time and automated solutions.
In manufacturing, data is collected from multiple sources and data collection is still often based on inspections made by an expert. Therefore, results are not immediately available to relevant stakeholders. Combining existing data with real-time sampling from the production process enables new findings. Also detecting small quality deviations becomes faster, which may prevent larger batches going sour or stopping the production line.
With the help of machine learning and vision, there is less need for manual inspection and in some cases, they can be removed from the process completely.
Replacing repetitive manual inspection tasks with automated solutions lets engineers to focus on more valuable work tasks. This increases the accuracy of defect detection and makes the whole process faster. Select the best technologies depending on the use cases; whether it is stereo cameras, hyperspectral vision or something else. We have the competence to recommend best option based on your business requirements.
Slowly occurring deviations in the production process might be hard to identify but are highly valuable to understand.
When there is a growing number of warranty or maintenance requests, slowly occurring systematical changes might be hard to detect. When quality inspections are done manually and without automation, accurate and reliable data sources might be missing. Having historical manufacturing data available, understanding trends and combining data from multiple sources might help to highlight valuable changes.
Do you already have a specific area in your mind that would like to improve in your QA processes? Describe your challenge to us, and we will get back to you with a proposal for solution! Below you can book a call with Janne Honkonen 👇
Edge AI is the new buzzword of the information world. In this article, I will explain what the hype is all about and present four use cases of Edge...
The possibilities for Edge AI are almost unlimited – applications vary from smartwatches to production lines and from logistics to smart buildings...
European manufacturing has a window of opportunity right now. Since the COVID-19 Coronavirus pandemic laid bare the industry’s vulnerability to...