Title: Propeller material belt grinding parameters optimisation using Taguchi technique

Authors: Y.Q. Wang; B. Hou; H.B. Liu; F.B. Wang

Addresses: Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, 116024, China ' Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, 116024, China ' Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, 116024, China ' Key Laboratory for Precision and Non-traditional Machining Technology of Ministry of Education, Dalian University of Technology, Dalian, 116024, China

Abstract: Belt grinding has been employed to achieve the finished geometry and the surface quality of large marine propeller with manganese bronze material (ZCuAl₈Mn₁₃Fe₃Ni₂). However, it is very challenging to select a group of reasonable belt grinding parameters with the consideration of accuracy, efficiency and economy simultaneously, which is always dealt by trial-and-error actually. This research mainly focuses on belt grinding parameters optimisation utilising Taguchi technique for improving surface roughness, belt wear and material remove rate. Four main factors were taken into account, including abrasive grain size, grinding speed, feed rate and grinding depth. The influences of those factors on grinding process were analysed through S/N ratios and analysis of variance (ANOVA). A number of experiments were conducted on a five-axis computer numerical control (CNC) belt grinding machine according to the parameters orthogonal array (OA). It showed that surface roughness, belt wear and material remove rate have been improved using the optimised belt grinding parameters.

Keywords: belt grinding; parameter optimisation; manganese bronze; Taguchi methods; marine propellers; surface roughness;; surface quality; belt wear; material remove rate; MRR; abrasive grain size; grinding speed; feed rate; grinding depth; SNR; signal to noise ratio; analysis of variance; ANOVA; five-axis machining; CNC grinding; orthogonal arrays.

DOI: 10.1504/IJISE.2017.080685

International Journal of Industrial and Systems Engineering, 2017 Vol.25 No.1, pp.1 - 13

Received: 19 Aug 2014
Accepted: 27 Jan 2015
Published online: 04 Dec 2016 *

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