Search Results

To support its recycling efforts, Ford Motor Company is using a Raman based instrument, the RP-1, co-developed with SpectraCode Inc. to identify unknown polymeric parts. Our recycling initiative involves detailed dismantling of our vehicles into individual parts, calculating the percentage recyclability and making recommendations for the future use of recycled polymers. While Ford has voluntarily adopted the SAE J1344 marking protocol for identifying part material composition, a large number of unmarked parts still exist and require identification. This identification is being done with the help of RP-1. To facilitate this identification, we have generated an accurate reference library of Raman spectra for comparison to those of unknown materials. This paper will describe the techniques that were used to develop and refine the RP-1 reference library to identify automotive polymers, especially black/dark plastics.

Specular-reflectance infrared spectroscopy systems can identify the polymer material of an automotive part in about 5 seconds and are currently commercially available. Issues related to the rapid identification of plastics were recently examined at the Vehicle Recycling Development Center, which is operated by the United States Council for Automotive Research (USCAR). The accuracy of identification is a crucial concern in order to minimize co-mingling or contamination of sorted plastics in dismantling-sorting-recycling operations. Accuracy reports in the literature have ranged from 70% to >99%. Our investigation of the signal-to-noise levels of spectrometers, identification algorithms, and spectral reference libraries indicated that the quality-and-completeness of the reference library is the strongest determinant of accuracy when evaluating current commercial systems. With adequate spectral libraries, identification accuracy of 99% can be achieved.