A Review on Sensors for Real-time Monitoring and Control Systems on Machining and Surface Finishing Processes

Abstract

One of the key components in real-time monitoring and control on machining and surface finishing processes are sensors. The advances of such system have triggered interesting questions on sensor selection that act as the fundamental before starting a project. This paper is made to review and answer the questions surrounding sensor selection. The paper first explains on the type of sensors commonly used in practice for real-time monitoring and control systems. After which, the paper discusses on how often the sensors are used on several machining and surface finishing processes and what are the reasons for the sensor selection. Thereafter, a review on the type features commonly analysed through these sensors is discussed. The paper expects reader would decide better upon selecting sensors and has a better direction in their project. Thus the paper works to guide reader to improve based on what has been completed before.

Adaptive neuro-fuzzy inference system for deburring stage classification and prediction for indirect quality monitoring

“…The literature review of sensors selection which is reported in [2] narrows down 7 types of sensor suitable for monitoring, namely acoustic emission (AE) sensor, accelerometer, force sensor, dynamometer, proximity sensor, thermometer, and strain gauge. The first four sensors are more common to be used than the last three.…”

“…The grading is concluded based on extensive reading and comparison on various papers done in different surface finishing processes. The study for the grading can be found in the paper reported in [2]. Grading of each sensors type is stated in Fig.…”

“…Subsequently, a machine learning method plays an important role to build the direct monitoring system in terms of providing the decision or current condition based on sensor data analysis. A preliminary study of sensor selection has been conducted by Wijaya et al [2].…”

In-process tool condition monitoring in compliant abrasive belt grinding process using support vector machine and genetic algorithm

“…Correlation between tool vibration based on contact conditions can be used to verify the state of the tool during grinding. AE, force and accelerometer sensors show greater sensitivity at ultra-precision machining regime which is a typical characteristic of any abrasive machining process [46,47]. Complimentary multi-sensor integration system incorporating force, accelerometer and AE has been proposed as a strategy to estimate the values of physical variables being measured to give a complete picture of the tool condition state of abrasive belt grinding process which is difficult to understand.…”