In the era of the “Industry 4.0” revolution, self-adjusting and unmanned machining systems
have gained considerable interest in high-value manufacturing industries to cope with the …

Abstract In the “Industry 4.0” era, autonomous and self-adaptive industrial machining attracts
significant attention in professional manufacturing. This trend originates from the rising …

This review paper summarizes the application of smart manufacturing systems utilized in
drilling and hole machining processes. In this perspective, prominent sensors such as …

Process monitoring is necessary in machining operation to increase productivity, improve
surface quality, and reduce unscheduled downtime. Tool wear and breakage are important …

Tool wear prediction was significant for improving processing efficiency, ensuring product
quality and reducing tool costs in manufacturing. In this paper, a novel deep learning …

Recently, the use of carbon fibre reinforced polymer (CFRP) composites is predominant and
will grow further. Although these fibrous composites are often manufactured near net shape …

Monitoring of tool wear in machining process has found its importance to predict tool life,
reduce equipment downtime, and tool costs. Traditional visual methods require expert …

In recent years, significant advancements have been achieved in the domain of machine
monitoring as witnessed from the beginning of the new industrial revolution (IR) known as IR …

We present a data-driven method for monitoring machine status in manufacturing processes.
Audio and vibration data from precision machining are used for inference in two operating …

Tool condition monitoring (TCM) is a very effective way to enhance productivity and ensure
work-piece quality. This paper introduces a cutting condition independent TCM approach for …