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Near infrared spectroscopy (NIRS) is based on molecular overtone and combination vibrations. It is di±cult to assign speci¯c features under complicated system. So it is necessary to¯nd the relevance between NIRS and target compound. For this purpose, the chondroitin sulfate (CS) ethanol precipitation process was selected as the research model, and 90 samples of 5 di®erent batches were collected and the content of CS was determined by modi¯ed carbazole method. The relevance between NIRS and CS was studied throughout optical pathlength, pretreatment methods and variables selection methods. In conclusion, the¯rst derivative with Savitzky-Golay (SG) smoothing was selected as the best pretreatment, and the best spectral region was selected using interval partial least squares (iPLS) method under 1 mm optical cell. A multivariate calibration model was established using PLS algorithm for determining the content of CS, and the root mean square error of prediction (RMSEP) is 3.934 gÁL À1 . This method will have great potential in process analytical technology in the future.

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：Titanium alloy Ti6Al4V is widely used in the aviation and aerospace industry. However, this material is typically difficult-to-machine due to its intrinsic characteristics, such as poor thermal conductivity, high strength at elevated temperature, etc. A novel method is proposed to predict tool wear in machining of the titanium alloy. In this method, a thermo-mechanically-coupled tool wear model, consisting of abrasion, adhesion and diffusion mechanisms, is implemented in the Simulink software. The geometric features of a worn-tool are updated at different wear stages in the simulation. Tool wear prediction is conducted and validated by milling experiments under various milling conditions. The results show that the proposed method can well predict the extent of the tool flank wear, and the relative error between the experimental and the prediction results is within 22%. This study offers a guidance to the determination of tool life and optimization of process parameters in a machining process.

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