Condition Monitoring of Machine Tool Feed Drives: A Review Journal Articles

abstract

• Abstract The innovations propelling the manufacturing industry towards Industry 4.0 have begun to maneuver into machine tools. Machine tool maintenance primarily concerns the feed drives used for workpiece and tool positioning. Condition monitoring of feed drives is the intermediate step between smart data acquisition and evaluating machine health through diagnostics and prognostics. This review outlines the techniques and methods that recent research presents for feed drive condition monitoring, diagnostics and prognostics. The methods are distinguished between being sensorless and sensor-based, as well as between signal-, model-, and machine learning-based techniques. Close attention is given to the components of feed drives (ball screws, linear guideways, and rotary axes) and the most notable parameters used for monitoring. Commercial and industry solutions to Industry 4.0 condition monitoring are described and detailed. The review is concluded with a brief summary and the observed research gaps.

authors

• Gadsden, Stephen
• Butler, Quade
• Ziada, Youssef
• Stephenson, David
• Andrew Gadsden, S

status

• published 

publication date

• October 1, 2022

has subject area

• 0910 Manufacturing Engineering (FoR)
• 0913 Mechanical Engineering (FoR)
• Industrial Engineering & Automation (Science Metrix)

published in

• Journal of Manufacturing Science and Engineering  Journal

keywords

• BALL-SCREW DRIVES
• CONDITION-BASED MAINTENANCE
• CONVOLUTIONAL NEURAL-NETWORK
• EMPIRICAL MODE DECOMPOSITION
• Engineering
• Engineering, Manufacturing
• Engineering, Mechanical
• FAULT-DIAGNOSIS
• MOTOR CURRENT
• PRELOAD LEVELS
• ROTARY AXIS
• SIGNAL ANALYSIS
• Science & Technology
• Technology
• WIRELESS SENSOR SYSTEM
• machine tool dynamics
• machining processes
• monitoring and diagnostics
• sensing

Digital Object Identifier (DOI)

• 10.1115/1.4054516

volume

• 144

issue

• 10