Hyperspectral Image acquired on LRI curing process

This dataset was generated within the framework of the EU-funded FLASH-COMP project, which aims to develop a human-oriented solution for the early identification of defective composite parts in manufacturing. The overarching goal is to enhance composite manufacturing processes by enabling zero-defect production and reducing material waste generation. A key enabling technology in the project is Hyperspectral Imaging (HSI). This dataset contains hyperspectral images acquired during the production of two composite parts manufactured using the Liquid Resin Infusion (LRI) process. The data is intended to support research and development on process monitoring and quality assurance in advanced manufacturing. Data Structure: sampleA_hsi_reflectance.npy:Contains the raw reflectance hypercubes of all acquisitions (N) during the curing phase of Sample A, saved in .npy format. sampleA_auxiliary_data.zip:Contains: Reference cure degree values: One vector of N values for each sensor used, saved in .npy format. Sensor positions within the hyperspectral image: Defined using Regions of Interest (ROI) in [x1, y1, x2, y2] format. Each ROI is stored in a .npy file as an [N, 4] matrix, where N is the number of acquisitions. sampleB_hsi_reflectance.zip:Contains the raw reflectance hypercubes of all acquisitions during the curing phase of Sample B, saved in .npy format. Note: This dataset is currently under embargo and will be made publicly available upon acceptance of the associated peer-reviewed article.