4.5 Article

New insights into the methods for predicting ground surface roughness in the age of digitalisation

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.precisioneng.2020.11.001

Keywords

Industry-4,0; Digitalisation; Quality; Prediction; Digital manufacturing; Precision grinding

Funding

  1. National Natural Science Foundation of China [51875078, 51991372]
  2. Science Fund for Creative Research Groups of NSFC of China [51621064]
  3. UKRI [EP/L016567/1, EP/S013652/1, EP/S036180/1, EP/T001100/1, EP/T024607/1]
  4. Royal Academy of Engineering [IAPP18-19\295, TSP1332, EXPP2021\1\277]
  5. EU Cost Actions [CA15102, CA18125, CA18224, CA16235]
  6. Newton Fellowship award from the Royal Society [NIF\R1\191571]
  7. European Regional Development Funds (ERDF)
  8. Isambard Bristol, UK [e648]

Ask authors/readers for more resources

Grinding is a widely used material removal process in various industrial sectors, and the surface roughness it generates can influence the performance of ground components. Predicting surface roughness is beneficial for improving production efficiency and guiding the adjustment of grinding parameters to reduce costs.
Grinding is a multi-length scale material removal process that is widely employed to machine a wide variety of materials in almost every industrial sector. Surface roughness induced by a grinding operation can affect corrosion resistance, wear resistance, and contact stiffness of the ground components. Prediction of surface roughness is useful for describing the quality of ground surfaces, evaluate the efficiency of the grinding process and guide the feedback control of the grinding parameters in real-time to help reduce the cost of production. This paper reviews extant research and discusses advances in the realm of machining theory, experimental design and Artificial Intelligence related to ground surface roughness prediction. The advantages and disadvantages of various grinding methods, current challenges and evolving future trends considering Industry-4.0 ready new generation machine tools are also discussed.

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