Designing optimal automatic cycles of round grinding based on the synthesis of digital twin technologies and dynamic programming method

Pereverzev, P. P.; Akintseva, A. V.; Alsigar, M. K.; Ardashev, D. V.

doi:10.5194/ms-10-331-2019

Cited by 11 publications

(6 citation statements)

References 26 publications

(28 reference statements)

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“…The collaboration and interaction of human–robot operates a closed‐loop simulation to support task allocation, work optimization, data analysis, and system testing 58 . The process evaluation and optimization considers some uncertain conditions to enable data acquisition and mapping 59 . The asset management includes visibility and traceability to improve base performance which has planning, controlling, and scheduling to offer a better decision‐making process 60 .…”

Section: Research Methodologiesmentioning

confidence: 99%

“…58 The process evaluation and optimization considers some uncertain conditions to enable data acquisition and mapping. 59 The asset management includes visibility and traceability to improve base performance which has planning, controlling, and scheduling to offer a better decision-making process. 60 The production planning exploits a paradigm of digital-twin shop floor to examine the status of real-time data including sensory, simulation, and enterprise information system.…”

Section: Intelligent Application In the Manufacturing Phasementioning

confidence: 99%

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Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition

Deebak

Al‐Turjman²

2021

Int J of Intelligent Sys

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The rapid development forms a new transition of information technologies to offer an intelligent manufacturing. The manufacturer has revolutionized the stages of product lifecycle including process planning and maintenance for the early detection of potential system failures and proactive management. Technological advancements including big data, the cloud, and the Internet of Things have applied digital‐twin for industrial practice. It has low‐power wireless‐enabled devices to play a vital role in various industrial automation systems such as industry logistics, portable equipment, and intelligent wireless monitoring. It is evident that industrial manufacturers are nowadays aiming to transform the machine into fully automated systems that not only control the operation of the equipment but also try to meet the demand of future markets effectively. One of the challenging issues in the automation of the machinery process is the deployment of reliable systems to analyze the machinery condition such as fault diagnosis. Thus, this article proposes a digital‐twin‐assisted fault diagnosis using deep transfer learning to analyze the operational conditions of machining tools. Moreover, this proposed system has developed an intelligent tool‐holder that integrates a k‐type thermocouple and cloud data acquisition system over the WiFi module. The analytical study proves that this intelligent tool‐holder provides better accuracy to demonstrate the optimization of milling and drilling operations of cutting tools.

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Section: Research Methodologiesmentioning

confidence: 99%

Section: Intelligent Application In the Manufacturing Phasementioning

confidence: 99%

Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition

Deebak

Al‐Turjman²

2021

Int J of Intelligent Sys

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“…Yong Zheng [39] established an improved cylindrical wet grinding temperature (ICWGT) model considering the lubrication effect of the grinding fluid and believed that the proposed model could more accurately predict the workpiece grinding temperature compared with a method that does not consider the lubrication effect. Pavel P. Pereverzev [40] proposed a dynamic programming method (DPM) for the design of circular grinding automatic cycle optimization based on digital twin technology synthesis, as shown in Figure 6. The optimal trajectory of the radial feed change cycle is calculated to design the optimal grinding cycle and the automatic grinding cycle method is designed with the optimal cutting condition parameters for the CNC machine tool.…”

Section: The Mainshaft Bearing Grinding Technology Based On Digital Twinmentioning

confidence: 99%

“…Figure 6. Scheme of the interaction of the system for optimizing the DPM cycle with the digital twin of the cycle testing system[40].…”

mentioning

confidence: 99%

Application of Life Cycle of Aeroengine Mainshaft Bearing Based on Digital Twin

Yan³

et al. 2023

Processes

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Aeroengine mainshaft bearings are key components in modern aeroengines, and their main functions are to support the rotation of the main shaft of the aeroengine in harsh environments, such as high temperature, heavy load, high speed and oil break; reduce the friction coefficient during the high-speed rotation of the main shaft; and reliably ensure the rotation accuracy and power transmission of the aeroengine’s main shaft during operation. The manufacture of aeroengine mainshaft bearings requires complex processes and precise machining to ensure high performance and reliability, and how to intelligently complete the production and manufacture of mainshaft bearings and ensure the strength and accuracy of the bearings, quickly distinguish the fault types of the bearings and efficiently calculate, analyze and predict the life of the bearings are the current research hotspots. Therefore, building a high-fidelity and computationally efficient digital twin life cycle of aeroengine mainshaft bearings is a valuable solution. This paper summarizes the key manufacturing technology, manufacturing mode and manufacturing process based on digital twins in the life cycle of aeroengine mainshaft bearings, including the metallurgical process, heat treatment process and grinding process of aeroengine mainshaft bearings. It presents a fault diagnosis and life analysis of mainshaft bearings of aeroengines, discussing the key technologies and research directions of the life cycle of mainshaft bearings based on digital twins.

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“…The creation of the DT became possible as a result of the implementation of a physical and mathematical model of the allowance removal by system modeling of a plenty of interrelated wide-range analytical models of the circular grinding processes (model of elastic deformations of the technological system (TS), cutting force model [11], model of the interrelation between program and actual feeds [12], model of the processing error formation [13], model of the treated surface` dimensions formation [14], etc.). These models are combined into a unified analytical model for calculating the values of actual feeds in several sections of the treated surface on each revolution of the workpiece during the entire grinding cycle for specified grinding conditions under various combinations of unstable factors values when processing the parts batch [15].…”

Section: Introductionmentioning

confidence: 99%

Modelling of layer-by-layer metal removal in the digital twin of the round grinding process performed on CNC machines

et al. 2020

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Parts’ processing on circular grinding machines is carried out according to the specified stepwise control cycles of radial and axial feeds, which are laid down in the control program (CP). Despite the precise positioning systems, modern CNC circular grinding machines have a variable compliance of the technological system along the processing length. It causes different cutting depth and occurrence of various errors in dimensions of the diametric surface. Also, the dimensions error increases due to the fact that the processing of parts batch is carried out in unstable conditions and under the influence of different variable factors, which can include allowance fluctuation, blunting of the wheel grains, changes of the wheel diameter and the contact area of the wheel with the workpiece, etc. However, there are still no means of control developed CP, which include cycles of cutting modes, to ensure the accuracy of parts batch` processing. This article describes the digital twin (DT) of the circular plunge grinding with CNC, which allows simulating layer-by-layer metal removal during the whole grinding cycle by calculating the cutting depth on each workpiece revolution under various combinations of unstable processing conditions and variable compliance of TS. Modeling of layer-by-layer allowance removal is performed in several sections of the treated surface; these sections have different compliance. At the end of the grinding cycle in the DT the processing accuracy is estimated on the basis of the obtained values of radii dimensions in all sections of the processed surface. The introduction of DT allows speeding up the CP development, reduce the time of launching CP in production, and increase the productivity of circular grinding operations with CNC by optimizing the cycles of the cutting modes while ensuring the specified processing accuracy.

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Designing optimal automatic cycles of round grinding based on the synthesis of digital twin technologies and dynamic programming method

Cited by 11 publications

References 26 publications

Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition

Digital‐twin assisted: Fault diagnosis using deep transfer learning for machining tool condition

Application of Life Cycle of Aeroengine Mainshaft Bearing Based on Digital Twin

Modelling of layer-by-layer metal removal in the digital twin of the round grinding process performed on CNC machines

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