{"id":5351,"date":"2026-07-09T13:28:42","date_gmt":"2026-07-09T11:28:42","guid":{"rendered":"https:\/\/nl.ai-matters.eu\/ai-quality-inspection-manufacturing-inno-group\/"},"modified":"2026-07-09T13:28:42","modified_gmt":"2026-07-09T11:28:42","slug":"ai-quality-inspection-manufacturing-inno-group","status":"publish","type":"post","link":"https:\/\/nl.ai-matters.eu\/en\/ai-quality-inspection-manufacturing-inno-group\/","title":{"rendered":"How Inno-group uses AI to drastically reduce quality errors"},"content":{"rendered":"
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Inno-Group’s Experience:<\/div>\n
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How can you test AI for quality control without immediately investing in a new production line? In this user story, we show how Inno-group, together with Blue Engineering through AI-MATTERS, tested an AI-driven vision solution for automated final inspection. By first carrying out a feasibility study, the company was able to investigate whether AI can detect and reduce human errors in complex production processes, without making major investments straight away. The results were positive and form the basis for the next step towards implementation.<\/strong><\/p>\n

Delivering quality in an environment where people make the difference<\/strong><\/strong><\/strong><\/h2>\n

Inno-group is a supplier specialising in high-quality sheet metal and welding work for, among others, the medical and laboratory sectors and mechanical engineering. The company has sites in Eindhoven and Zaandam and produces complex products with high accuracy requirements.<\/p>\n

For many customers, quality requirements apply that are comparable to those in the automotive industry. At the same time, Inno-group does not operate in a fully automated factory. The production environment is a typical high-mix, low-volume setting in which many manual operations take place. For Gertjan van den Hazelkamp, Commercial Director at Inno-group, one question was therefore essential: how can we further improve quality when human errors can never be completely eliminated from a process?<\/p>\n

The Challenge<\/strong><\/strong>: limiting human errors in complex production processes<\/strong><\/h2>\n

Gertjan: \u201cMany of Inno-group\u2019s products go through a large number of production steps before they are ready for delivery. Some products even pass through twenty different operations and are handled by employees twenty times. Despite continuous process improvements and training, human error remains possible. According to our own estimates, when manual operations are added up, something goes wrong in around 1% of these operations. This could be a forgotten operation, a moment of inattention or a minor deviation during assembly. In large volumes, this can have significant consequences. A customer receiving 6,000 products annually receives around 120 faulty products at an error rate of 2%. We need to reduce that number drastically; our customers are affected too much by this.\u201d<\/p>\n

The approach: a feasibility study through AI-MATTERS<\/strong><\/h2>\n

Gertjan came into contact with Blue Engineering via LinkedIn. In addition, the company was also alerted through its own network to the opportunities offered by Blue Engineering and collaboration around vision technology. Together, Inno-group and Blue Engineering decided to carry out a feasibility study within the AI-MATTERS programme.<\/p>\n

The aim of the study was clear:<\/p>\n