Cutting Force Optimization Under ANN and QRCCD

Imhade P. Okokpujie, Lagouge K. Tartibu

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


The prediction analysis of cutting force in the cutting process is very significant in the manufacturing of products for industrial use. Cutting force is one of the responses in machining operations that affect energy consumption via computer numerical control of the manufacturing process. The focus of this chapter is to employ artificial neural network (ANN) and quadratic rotatable central composite design (QRCCD) to carry out prediction and optimisation to study the cutting force to minimised the energy consumption. The data employed in this study is obtained from experimental machining operation of AA 8012 alloy under vegetable oil TiO2 biodegradable nano-lubricant for sustainable machining process. The result obtained showed that the minimum cutting force occurs at the optimal machining parameter of spindle speed of 2351 rpm, 101 mm/min feed rate, 1 mm depth of cut, 20 mm length of cut, and 60° helix angle and the minimum cutting force of 31 N with the desirability of 0.968. Also, the generated models developed for the cutting force using ANN and QRCCD predicted the experimental results with 97.5% and 95.56% accuracy under the biodegradable TiO2 nano-lubricant. This result has proven that the implementation of Heuristic and Metaheuristic Techniques for Advanced Nano-lubricant Machining Optimization is a sustainable manufacturing process.

Original languageEnglish
Title of host publicationStudies in Systems, Decision and Control
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages31
Publication statusPublished - 2023

Publication series

NameStudies in Systems, Decision and Control
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190


  • Artificial neural network
  • Cutting force
  • Nano-lubricant

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Control and Systems Engineering
  • Automotive Engineering
  • Social Sciences (miscellaneous)
  • Economics, Econometrics and Finance (miscellaneous)
  • Control and Optimization
  • Decision Sciences (miscellaneous)


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