Sintered mixed materials are essential to the sintering process, and the precision of their component detection significantly influences outcomes. LIBS technology utilizes laser spectroscopy to analyze the elemental composition and concentration of these materials, offering real-time data. However, its quantitative detection capabilities still fall short compared to other laboratory methods. This study introduced a remote sensing LIBS device for detecting components in sintered mixed materials. By combining Partial Least Squares Regression (PLSR) and Principal Component Analysis (PCA), it quantitatively assessed TFe, CaO, SiO₂, and MgO concentrations. Analysis of spectral data with delay times of 1.28 μs and 5 μs showed notable differences in R² values for various substances. For low-concentration SiO₂ and MgO, the 1.28 μs delay yielded R² values of 0.937 and 0.985, respectively. Conversely, a 5 μs delay produced better results for higher concentrations, with TFe's R² increasing from 0.903 to 0.987 and CaO's from 0.816 to 0.980. This approach enhanced detection accuracy by utilizing optimal delay times for different substances, streamlining the detection process and providing valuable insights for the sintering process.