Application of sophisticated sensors to advance the monitoring of machining processes: analysis and holistic review

Kandavalli, Sumanth Ratna; Khan, Aqib Mashood; Iqbal, Asif; Jamil, Muhammad; Abbas, Saqlain; Laghari, Rashid Ali; Cheok, Quentin

doi:10.1007/s00170-022-10771-6

Cited by 19 publications

(8 citation statements)

References 151 publications

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“…The cutting force is the basis for analyzing various physical phenomena such as cutting heat, temperature rise, workpiece deformation and tool wear during the machining process. It can provide important reference for tool design, machine tool design, and the selection of process parameters 1 . So the cutting force measurement is essential in the machining process.…”

Section: Introductionmentioning

confidence: 99%

“…With the continuous development of automated manufacturing systems, the demand for cutting status monitoring is also increasing, making the study of cutting force monitoring even more important. The traditional method of detecting cutting force is to use a force measuring instrument or force sensor, which have obvious defects: (1) when installing a force measuring instrument, the stiffness of machine tool and workpiece changes, and accurate force signals cannot be collected; (2) the installation and debugging of force measuring instrument are complex; (3) the cost of instrument is extremely high; (4) the reliability of cutting force measuring system is low. Therefore, it is not suitable for real-time monitoring of cutting force.…”

Section: Introductionmentioning

confidence: 99%

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Research on the mapping relationship between load current and cutting force of CNC machine tools

xin,

wanlin,

Hongjie

et al. 2024

Fifteenth International Conference on Signal Processing Systems (ICSPS 2023)

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To monitor the changes in cutting force during the machining process of machine tools, this article takes ZL205A aluminum alloy as the research object and builds a multi-sensor acquisition system, including cutting force signal, load current signal, and vibration signal acquisition system. Cutting experiments were conducted to obtain cutting force, load current, and vibration amplitude under different process parameters. The time-frequency characteristics of cutting force signals were analyzed. The mapping relationship between cutting process parameters and cutting force, as well as load current and cutting force, was established. This research enables indirect monitoring of dynamic cutting force signals by monitoring load current signals, providing reference and guidance for monitoring dynamic cutting force in actual machining processes and process optimization.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Research on the mapping relationship between load current and cutting force of CNC machine tools

xin,

wanlin,

Hongjie

et al. 2024

Fifteenth International Conference on Signal Processing Systems (ICSPS 2023)

View full text Add to dashboard Cite

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“…Inspecting and analyzing the geometric deviation of machined parts allows modeling of the machining error behavior, which contains all the essential information of the error sources in the machining process. Closed-loop machining employs the inspection results of the machined part in the error compensation of the finishing cuts, repetitive production, online process planning, and modification of the machining process [15][16][17]. In this way, closed-loop machining contributes to smart manufacturing [18][19][20] by increasing the productivity, reliability, and sustainability of the machining process.…”

Section: Introductionmentioning

confidence: 99%

Skin Imaging: A Digital Twin for Geometric Deviations on Manufactured Surfaces

Ghanbary Kalajahi,

Mahboubkhah,

Barari

2023

Applied Sciences

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Closed-loop manufacturing is crucial in Industry 4.0, since it provides an online detection–correction cycle to optimize the production line by using the live data provided from the product being manufactured. By integrating the inspection system and manufacturing processes, the production line achieves a new level of accuracy and savings on costs. This is far more crucial than only inspecting the finished product as an accepted or rejected part. Modeling the actual surface of the workpiece in production, including the manufacturing errors, enables the potential to process the provided live data and give feedback to production planning. Recently introduced “skin imaging” methodology can generate 2D images as a comprehensive digital twin for geometric deviations on any scanned 3D surface including analytical geometries and sculptured surfaces. Skin-Image has been addressed as a novel methodology for continuous representation of unorganized discrete 3D points, by which the geometric deviation on the surface is shown using image intensity. Skin-Image can be readily used in online surface inspection for automatic and precise 3D defect segmentation and characterization. It also facilitates search-guided sampling strategies. This paper presents the implementation of skin imaging for primary engineering surfaces. The results, supported by several industrial case studies, show high efficiency of skin imaging in providing models of the real manufactured surfaces.

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“…DTs use real-time data to optimize throughput by adjusting controllable parameters [14]. They also react in real time to disturbances on the shop floor [15].…”

mentioning

confidence: 99%

“…The DT for manufacturing usually consists of a physical element, a virtual element, and a real-time information exchange between them, assisted by the IoTs, data collection and storage tools, big data analytics, and ML [15]. Making the privacy and security of data a top priority still stays.…”

mentioning

confidence: 99%

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

El Bazi,

Laayati,

Darkaoui

et al. 2024

Designs

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While digital twins (DTs) have recently gained prominence as a viable option for creating reliable asset representations, many existing frameworks and architectures in the literature involve the integration of different technologies and paradigms, including the Internet of Things (IoTs), data modeling, and machine learning (ML). This complexity requires the orchestration of these different technologies, often resulting in subsystems and composition frameworks that are difficult to seamlessly align. In this paper, we present a scalable compositional framework designed for the development of a DT-based production management system (PMS) with advanced production monitoring capabilities. The conducted approach used to design the compositional framework utilizes the Factory Design and Improvement (FDI) methodology. Furthermore, the validation of our proposed framework is illustrated through a case study conducted in a phosphate screening station within the context of the mining industry.

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Application of sophisticated sensors to advance the monitoring of machining processes: analysis and holistic review

Cited by 19 publications

References 151 publications

Research on the mapping relationship between load current and cutting force of CNC machine tools

Research on the mapping relationship between load current and cutting force of CNC machine tools

Skin Imaging: A Digital Twin for Geometric Deviations on Manufactured Surfaces

Scalable Compositional Digital Twin-Based Monitoring System for Production Management: Design and Development in an Experimental Open-Pit Mine

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