DESIGN MODELING AND SIMULATION OF BLADES FOR PLASTIC SHREDDING
Abstract
This project investigates the structural performance and cutting efficiency of various plastic shredding blade designs using SOLIDWORKS Simulation. Four common plastic types—PET, PP, HDPE, and PS—were analyzed under different cutting forces to determine the optimal combination of blade configuration, material, and thickness for effective shredding operations. A total of 40 simulation cases were conducted, evaluating single-blade, double-blade, and 4-blade configurations made from mild steel, high carbon steel, stainless steel, and D2 tool steel at thicknesses of 4 mm, 6 mm, and 8 mm.Results show that blade configuration significantly influences performance, with the 4-blade design consistently providing the lowest stress distribution, minimal displacement, and the highest safety factors across all plastic types. Material selection also played a major role, as stainless steel (440C) and D2 tool steel demonstrated superior structural integrity and wear resistance, especially at 8 mm thickness. In contrast, single-blade configurations and 4 mm thick blades exhibited high stress concentrations and low safety margins, making them unsuitable for industrial shredding. The study concludes that the most efficient shredding blade design is an 8 mm thick, 4-blade configuration made from stainless steel or D2 tool steel, offering excellent durability, load distribution, and cutting stability. These findings provide valuable insights for the design and manufacture of high-performance plastic shredding machines used in recycling and waste-processing industries.
Full-Text Access Notice
In accordance with the NERD Policy on promoting peer-reviewed publication, public access to the full text of a project, thesis or dissertation is restricted for three years, allowing the author and supervisors sufficient time to pursue peer-reviewed publication.
During this period, researchers with legitimate academic or research purposes may request authorisation directly from the author to enable NERD to release the indexed full texts of the work using the form below.