Surface Inspection
Inspection of E-Modules
Maddox AI enables the reliable and automated identification of defects such as sheet metal damage, bubbles in the potting, damaged conductor paths and many more.
Product
Industry
Total savings / year
Customer Request
Our customer produces several thousand e-modules every day. Due to the complex manufacturing processes, the error rate fluctuates greatly and can be as high as 20%. The quality control of the components was previously carried out manually in a 3-shift operation by a team of five employees per shift. In addition to special (UV) light, magnifying glasses were used to detect delicate defects (such as solder joint defects). As each component is checked for over 50 different defect classes, the inspection accuracy of the different inspection employees varied considerably, which led to pseudo rejects and customer complaints with significant financial risks.
With the introduction of Maddox AI, the actual inspection process could be fully automated and thus also rationalized. Defective components are now detected precisely and reliably, meaning that it is no longer necessary to rely on the subjective assessments of employees.
Before
Previous Inspection System
After
With Maddox AI
Each day, 15 employees checked the components, which led to a high level of manual effort and associated costs.
The actual quality inspection is now fully automated, which has considerably reduced the manual effort and significantly increased the efficiency of the inspections. One person per shift is still scheduled to load the inspection device.
Due to the inaccuracy of manual checks, there were several customer complaints.
No further customer complaints have been received since the installation of Maddox AI.
No structured root cause analysis was carried out for the production of NOK parts.
Thanks to the digitalized inspection process, including the development of a defect heat map, the main causes of increased defect production could be identified.
Before
Previous Inspection System
Each day, 15 employees checked the components, which led to a high level of manual effort and associated costs.
Due to the inaccuracy of manual checks, there were several customer complaints.
No structured root cause analysis was carried out for the production of NOK parts.
After
With Maddox AI
The actual quality inspection is now fully automated, which has considerably reduced the manual effort and significantly increased the efficiency of the inspections. One person per shift is still scheduled to load the inspection device.
No further customer complaints have been received since the installation of Maddox AI.
Thanks to the digitalized inspection process, including the development of a defect heat map, the main causes of increased defect production could be identified.
reduced Personnel Costs
Traceability of each component
Investment Payback Period
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