Hybrid model based on energy and experimental methods for parallel hexapod-robotic light abrasive grinding operations

Latifinavid M., KONUKSEVEN E. İ.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, cilt.93, ss.3873-3887, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 93
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1007/s00170-017-0798-8
  • Dergi Adı: INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.3873-3887
  • Anahtar Kelimeler: Grinding force model, Regression, Robotic grinding, Data mining, FORCE MODEL, PREDICTION
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

Automatic grinding using robot manipulators requires simultaneous control of the robot endpoint and force interaction between the robot and the constraint surface. In robotic grinding, surface quality can be increased by accurate estimation of grinding forces where significant tool and workpiece deflection occurs. The small diameter of the tool causes different behavior in the grinding process in comparison with the tools that are used by universal grinding machines. In this study, we develop a robotic surface grinding force model to predict the normal and tangential grinding forces. A physical model is used based on chip formation energy and sliding energy. To improve the model for robotic grinding operations, a refining term is added. The stiffness of the tool and setup is inherently included using penetration test results and estimating the refining term of the model. The model coefficients are calculated using a linear regression technique. The proposed model is validated by comparing model outputs with experimentally obtained data. Evaluation of the test results demonstrates the effectiveness of the proposed model in predicting surface grinding forces.