The chemical industry is characterized by precise manufacturing processes, strict safety standards, and demanding environmental regulations. However, dealing with high-precision materials and complex structures, maintaining consistent quality during large-scale production is a challenging task.
In particular, if minute defects or material inhomogeneities that occur during the initial manufacturing stage are not effectively detected, this can lead to decreased product performance and increased defect rates. Furthermore, the quality inspection process must also simulate extreme conditions like high voltage and high temperatures, and the task of repeatedly measuring and recording this is a complex procedure that consumes excessive time and costs. These challenges affect both productivity and quality, making it one of the biggest challenges faced by the chemical industry.
SEM (Scanning Electron Microscope) offers very high resolution, enabling detailed observation of structures, and is therefore used in quality control tasks in many material and food production sites. However, SEM images are complex and contain vast amounts of information, making analysis often difficult and requiring significant manual work. For example, users perform tasks such as particle size measurement and noise removal manually, and interpreting particle structures and bonding states requires advanced expertise and a considerable amount of time.
SDT has developed an innovative solution that automates SEM image analysis to address these issues. First, SDT's SEM microscope machine vision solution automates particle size measurement, which is the starting point for industrial regulatory compliance and quality control. By utilizing the perspective data recorded during SEM imaging, it measures the particle's width, length, diagonal length, and area in real-time, creating a histogram by particle size to help users immediately grasp the status.
Moreover, SDT's SEM microscope machine vision solution automatically detects defects based on particle shape using Classification algorithms, and can detect agglomeration within 1 second after performing Segmentation, accurately distinguishing between agglomeration and overlapping phenomena in the images. This feature allows for real-time identification of quality defects during the production process and enables immediate response. SDT's automated solution saves time in the chemical and food industries while enabling more accurate quality control.
The quality manager can now conveniently download inspection data in CSV format, significantly reducing the time required for analysis and reporting tasks. Thanks to this automation and improvement in efficiency, customers have been able to enhance quality management while increasing production speed, securing a competitive edge in the market.
NodeQ serves as more than just a simple tool, enabling manufacturers to achieve innovative quality inspection processes. Now customers can ensure the highest quality even in mass production systems, building trust across the entire industry.
