On-Line Surface Roughness Prediction by Using a Probabilistic Approach for End-Milling

Oguz Kayabasi,Senol Erturk

doi:10.1109/access.2019.2944769

Abstract

An effective and efficient methodology is proposed to predict surface roughness by online monitoring of surface quality using accelerometer signals. A probabilistic approach, Monte Carlo Simulation, was researched and developed to create an automated tool for on-line prediction of surface quality. Data from 3-axis vibration (Vx, Vy, Vz) signals were used to predict on-line surface roughness. According to an experimental design with four cutting parameters (Cutting speed (Vc), Feed per teeth (Sz), Dept of cut (Dc), Width of cut (Wc)), three-axis vibration signals were used to combine data into a probabilistic model for development of an on-line surface roughness prediction system. Once the probability model was established by using a data set consisting of 71 experiments, the model was tested for 10 different cutting conditions. The probability model shows that the results have convergence values that are close to each other, by as high as 96.37%.

Highlights

Surface finish quality is an essential requirement of a machined product in today’s competitive manufacturing industry
EXPERIMENTAL SETUP The main aim of this study is to identify an appropriate technique for surface quality monitoring during milling by utilizing sensory signals
Off-line direct surface quality inspection techniques need time-consuming and labor-intensive setup requirements that are sometimes unacceptable due to the fact that they slow down the productivity of the manufacturing process

Summary

Introduction

Surface finish quality is an essential requirement of a machined product in today’s competitive manufacturing industry. During manufacturing processes, machined part surfaces get damaged more or less depending on the machining procedure that is implemented. This damage is decisive for the subsequent properties of the manufactured part such as sliding, lubricating, contact and straightness. To ensure that functional characteristics can be maintained as an important customer request, the surface quality must be checked and classified. For this reason, surface roughness has been one of the most frequently studied subjects in metal cutting by many researchers as a result of industrial quality requirements

Objectives

Methods

Conclusion