Stringent regulatory norms imply potentially higher liability for any production errors. Quality control is an important aspect of the pharmaceutical industry and has been one of the biggest concerns for manufacturers.
AI in manufacturing uses machine vision technology to detect defects and reduce wastage to zero. These use advanced technologies, such as high-end cameras, deep learning, and data analytics to detect defects with almost 100 per cent accuracy.
Like several other digital technologies, machine vision (MV) is an important component driving Industry 4.0. The high volume of data accessed via visual equipment is able to quickly detect faulty products by recognizing defects, thereby enabling efficient and rapid intervention in Industry 4.0.
Quality issues in these products may range from small surface defects to major issues that may affect the performance, safety, and functioning of the products. Injection molding defects may arise due to materials used, molding procedure, tooling design, or a combination of all three.
AI-based vision inspection systems can detect unnoticed defects within seconds, which makes them more accurate, consistent, quick, and detailed. Moreover, unlike human fatigue, machine vision systems tirelessly perform 100% accurate inspections improving quality.
An alternative that is gaining popularity is the automatic counting and packing machine, which guarantees 100% accuracy. This alternative not only ensures exact control leading to higher customer satisfaction but also improves ROI due to lower wastage and/or extra products.
As an FMCG manufacturer, what comes to your mind when you think about a defect detection system. Manual inspection can be inaccurate and error-prone. Even the most experienced defect detector can miss or misidentify the accuracy of the products.