Getting started with AI-supported inspection

To counteract this, significantly reduce costs and achieve improved quality in the long term, AI-supported inspection processes are future-proof and should be part of companies' data and AI strategy. Instead of measuring physical values, AI models scan for good and defect patterns in the product, which significantly increases the detection rate (DR) while minimizing the false rejection rate. This approach enables a more accurate and efficient inspection process by detecting even the smallest deviations or defects from the norm that may not be visible through traditional, physical measurements.

For this purpose, AI models are trained with large data sets, whereby the quality and relevance of the data are crucial for the accuracy and effectiveness of the resulting models. To ensure the highest quality of training data, experts with in-depth knowledge of pharmaceutical products and manufacturing processes are involved in the creation. They identify the relevant defects and impurities that need to be detected and develop the criteria for labeling the data – always with the individual production line in mind.

AI models are trained with advanced algorithms that enable them to recognize patterns and make accurate predictions, based on the input data. The trained models then are integrated into automated visual inspection (AVI) systems to detect defects and contaminants even better than with the conventional approach, by keeping up the same inspection speed.

Faster time to market and cost reduction through increased efficiency

The result of implementing AI-powered inspection solutions within a company's own production operations are remarkable. The deployment can reduce the false reject rate (FRR) by up to 90 percent, while increasing the detection rate by up to 40 percent. This not only results in more good products within a batch, but also in improved inspection efficiency and a less time-consuming workflow.

And faster time to market is not the only benefit. Using AI in visual inspection can also lead to significant cost savings. For example, pharmaceutical companies save up to $750,000 per year by avoiding a false reject rate of just 5% (based on an annual production volume of 10,000,000 containers and a production cost of $1.50 per container). In addition, companies can save up to $940,000 by eliminating the need for semi-automatic inspection machines for post inspection, assuming two inspection machines were previously used. With these cost savings, the return on investment (ROI) for AI-powered inspection solutions can be achieved in as little as one year.

Why choose Körber as a strategic partner for implementing AI in the pharmaceutical industry?

We understand the critical importance of visual inspection and the unique needs and constraints of the pharmaceutical industry. With our many years of experience, we offer a modular and scalable approach that allows our AI solutions to be fully integrated into existing vision systems without having to adapt the machine floor plan - regardless of the manufacturer of your inspection line. Our AI models and solutions stand for reliable, trustworthy, and compliant project execution and assure you of the highest data security in compliance with GxP regulations.

Don't let false rejection rates cost your business millions annually. Choose AI-powered solutions for accurate and efficient visual inspection.

Get in touch with us for your path to digital production