[Development Case] Defective Product Elimination System
Automation has been achieved, and detection accuracy has improved! This has contributed to reducing the workload of operators and promoting labor-saving measures.
We would like to introduce a development case of the "Defective Product Elimination System," which determines defective food materials flowing on a conveyor line through image processing and eliminates them using a robot installed downstream. The results of image processing and coordinate detection are linked with the device control side to calculate the moving coordinates, taking into account the conveyor speed. After implementation, data collection and accumulation of defective products were carried out, allowing for cross-referencing with factors such as raw material origin and season, enabling trend countermeasures. 【Case Overview】 ■Industry: Food ■Field: Quality Control ■Development Environment ・OS: Windows OS ・DB: Microsoft SQL Server, CSV files, image files ・Development Language: VB.net *For more details, please refer to the PDF document or feel free to contact us.
basic information
【Introduction Effects】 ■ Automation has been implemented compared to traditional visual inspections by operators, resulting in improved detection accuracy. ■ The introduction of a robot vision system contributes to reducing the workload of operators and minimizing the need for human labor. ■ Data collection and accumulation of defective products have been carried out, allowing for trend analysis in conjunction with factors such as raw material origin and season. *For more details, please refer to the PDF document or feel free to contact us.
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For more details, please refer to the PDF document or feel free to contact us.
