Real Time Monitoring of the CNC Process in a Production Environment- the Data Collection &amp; Analysis Phase

Downey, Jonathan; O'Sullivan, Denis; Nejmen, Miroslaw; Bombiński, Sebastian; O’Leary, Paul; Raghavendra, Ramesh; Jemielniak, Krzysztof

doi:10.1016/j.procir.2015.12.008

Cited by 37 publications

(14 citation statements)

References 17 publications

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“…In traditional manufacturing methods, process monitoring and control have been widely employed in academic and industrial applications to ensure process consistency [ 214 ]. However, in AM, the adoption of process monitoring and control have been used mainly in research [ 215 ].…”

Section: Resultsmentioning

confidence: 99%

Application of quality by design for 3D printed bone prostheses and scaffolds

et al. 2018

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3D printing is an emergent manufacturing technology recently being applied in the medical field for the development of custom bone prostheses and scaffolds. However, successful industry transformation to this new design and manufacturing approach requires technology integration, concurrent multi-disciplinary collaboration, and a robust quality management framework. This latter change enabler is the focus of this study. While a number of comprehensive quality frameworks have been developed in recent decades to ensure that the manufacturing of medical devices produces reliable products, they are centred on the traditional context of standardised manufacturing techniques. The advent of 3D printing technologies and the prospects for mass customisation provides significant market opportunities, but also presents a serious challenge to regulatory bodies tasked with managing and assuring product quality and safety. Before 3D printing bone prostheses and scaffolds can gain traction, industry stakeholders, such as regulators, clients, medical practitioners, insurers, lawyers, and manufacturers, would all require a high degree of confidence that customised manufacturing can achieve the same quality outcomes as standardised manufacturing. A Quality by Design (QbD) approach to custom 3D printed prostheses can help to ensure that products are designed and manufactured correctly from the beginning without errors. This paper reports on the adaptation of the QbD approach for the development process of 3D printed custom bone prosthesis and scaffolds. This was achieved through the identification of the Critical Quality Attributes of such products, and an extensive review of different design and fabrication methods for 3D printed bone prostheses. Research outcomes include the development of a comprehensive design and fabrication process flow diagram, and categorised risks associated with the design and fabrication processes of such products. An extensive systematic literature review and post-hoc evaluation survey with experts was completed to evaluate the likely effectiveness of the herein suggested QbD framework.

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Section: Resultsmentioning

confidence: 99%

Application of quality by design for 3D printed bone prostheses and scaffolds

et al. 2018

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“…For example, Torabi et al applied the signals obtained from dynamometer, accelerometer, and AE sensors to conduct TCM for a ball nose milling process [47]. Downey et al developed a TCM system based on AE, vibration, and cutting force signals [48]. Jahromi et al applied the signals derived from cutting force, accelerometer, and AE sensors for conducting TCM in a highspeed milling process [49].…”

Section: ) Motor Currentmentioning

confidence: 99%

Tool Wear Condition Monitoring in Milling Process Based on Current Sensors

Zhou

Sun

2020

IEEE Access

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Accurate tool condition monitoring (TCM) is essential for the development of fully automated milling processes. This is typically accomplished using indirect TCM methods that synthesize the information collected from one or more sensors to estimate tool condition based on machine learning approaches. Among the many sensor types available for conducting TCM, motor current sensors offer numerous advantages, in that they are inexpensive, easily installed, and have no effect on the milling process. Accordingly, this study proposes a new TCM method employing a few appropriate current sensor signal features based on the time, frequency, and time − frequency domains of the signals and an advanced monitoring model based on an improved kernel extreme learning machine (KELM). The selected multidomain features are strongly correlated with tool wear condition and overcome the loss of useful information related to tool condition when employing a single domain. The improved KELM employs a two-layer network structure and an angle kernel function that includes no hyperparameter, which overcome the drawbacks of KELM in terms of the difficulty of learning the features of complex nonlinear data and avoiding the need for preselecting the kernel function and its hyperparameter. The performance of the proposed method is verified by its application to the benchmark NASA milling dataset and separate TCM experiments in comparison with existing TCM methods. The results indicate that the proposed TCM method achieves excellent monitoring performance using only a few key signal features of current sensors. INDEX TERMS Tool condition monitoring (TCM), milling process, current sensor, kernel extreme learning machine (KELM), angle kernel.

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“…Fluctuations in machine tools affect the accuracy and quality of machined surfaces, the durability of tools and machine elements. One of the methods for studying vibrations is the analysis of it acoustic emission [Downey 2016], [Bejaxhin 2019]. Acoustic emission in the machining process comprises information about a cutting process, motor operation, spindle rotating, etc.…”

Section: Investigation Of Vibrations During Millingmentioning

confidence: 99%

“…For example, the information data of CNC machine tool based on the controller tuning operation are investigated for a smart productivity in position control mode [Chang 2016]. [Downey 2016] is describe the task of real-time monitoring CNC tool wear through the use of three sensor technologies: force, acoustic emission and vibration. This circumstance determines the need to develop a software and hardware complex (SHC) for the study of algorithms and processes in CNC machines, providing research directly on the process equipment.…”

Section: Introductionmentioning

confidence: 99%

Investigation of Processes in High-Speed Equipment Using CNC Capabilities

Aksonov¹,

Kombarov²,

Fojtu³

et al. 2019

MM SJ

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Improving the accuracy, reliability and performance of high-speed technological systems is one of the most pressing challenges in modern industry. The process of improvements in machine tools is permanent because of growth in requirements for the parts quality. The HSM process progress may depends on specific characteristics of particular machine. In this connection, there is a need to carry out investigations in real equipment. The possibility of in-process parameters registration using CNC capabilities is considered. Hardware and software solutions are proposed. The software capabilities for data processing, analyzing and displaying a large number of graphs are shown.

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Real Time Monitoring of the CNC Process in a Production Environment- the Data Collection & Analysis Phase

Cited by 37 publications

References 17 publications

Application of quality by design for 3D printed bone prostheses and scaffolds

Application of quality by design for 3D printed bone prostheses and scaffolds

Tool Wear Condition Monitoring in Milling Process Based on Current Sensors

Investigation of Processes in High-Speed Equipment Using CNC Capabilities

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