2026-10-07T07:20:16Z https://api.figshare.com/v2/oai

oai:figshare.com:article/32640501 2026-10-01T16:30:38Z portal_1172 item_type_8 month_year_10_2026

Geometrical quality prediction of machining process by parallel kinematic machines through deformation modelling and error compensation Virajith Shakya Bandara Adhikari Vitharana (24169305) PUREID: 618245581 PKM stiffness manufacturing parallel robots machining optimisation parallel kinematic machines error compensation compliance deformation Parallel Kinematic Machines (PKMs) offer enhanced flexibility, stiffness, accuracy, and dynamic performance over traditional machine tools. While they bring advantages for high-speed, high-precision aerospace, automotive, and medical manufacturing applications, PKMs face adoption barriers due to their nonlinear kinematics, complex stiffness characteristics, and challenges in predicting machining performance. This thesis addresses these issues through three primary research goals: creating a stiffness-based deformation model, predicting machined part quality, and compensating for the errors due to compliance deformations.<br><br>A semi-analytical stiffness prediction model was developed to address the first goal, incorporating gravity effects through experimental data-based parameter optimisation. A novel experimental approach was introduced to isolate gravity-induced deformations from those caused by cutting forces. The second goal, predicting part quality, was achieved by developing a geometrical error prediction model that estimates deviations between the actual and intended geometry of the workpiece, considering the predicted stiffness and cutting forces. Finally, an error compensation method for the Exechon X-Mini machine tool was devised to counter compliance deformations and validated through slot milling experiments.<br> 2026-10-01T16:30:38Z Text Thesis 10.17034/32640501.v1 https://figshare.com/articles/thesis/Geometrical_quality_prediction_of_machining_process_by_parallel_kinematic_machines_through_deformation_modelling_and_error_compensation/32640501 All Rights Reserved