Quality Control & Inspection

Monitoring CO₂, fine particulate matter, and other relevant parameters with an air quality meter helps identify changes that may be difficult to detect through human senses alone.

CO2 is colorless and odorless but can accumulate in enclosed spaces. Use a CO2 gas detector to monitor air quality fluctuations and proactively ensure safety.

Elitech iCold is a cloud-based platform designed to support remote monitoring and management across temperature-sensitive cold chain operations.

The E04 error on a refrigerant pressure gauge may be related to abnormal pressure conditions. Electrostatic interference and moisture ingress are two possible causes mentioned in the relevant guidance. When the error appears, continuing to use the instrument may result in unreliable readings. Therefore, it is recommended to stop the measurement and troubleshoot the issue step by step.

A systematic troubleshooting guide for checking a refrigerant pressure gauge that does not respond during the vacuuming process, focusing on connections, reset procedures, and zero-point calibration.

Metamerism can cause fabric samples to appear color-matched at the factory but show noticeable color differences in stores or under natural daylight. Evaluating colors under multiple light sources helps control this risk by providing objective color data standard.

In quality inspection and material analysis, a multispectral camera captures surface images and records spectral information at each pixel. The acquired data can help identify material or structural differences that are difficult to detect with the naked eye, analyze subtle details, and store data for further research.

Fabric UPF is shaped by the combined effects of color, density, weave or knit construction, and fiber material. Understanding these variables helps textile teams make more informed development and quality-control decisions.

CHN SPEC’s hyperspectral UAV nest system combines automated drone operations with the FS60C hyperspectral camera to support ecological monitoring workflows.

In the textile raw material quality control process, determining the composition of goose down and duck down mixtures is important for assessing product quality and ensuring transparency. Hyperspectral cameras can capture spectral data, extract relevant features, and build analytical models to quantitatively determine the composition of goose–duck down mixtures