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Molecular dynamics (MD) simulation, an atomic simulation technique, plays a significant role in studying mechanism of ultra-precision cutting. MD simulation of nanometric cutting with extremely high cutting speeds involves considerable computational time and significant memory usage, which can provide microscopic analysis to better understand the ultra-precision cutting process. Considerable researches relating to MD simulation might help improve manufacturing technologies, which are of particular interest to early studies. However, a number of studies embracing ultra-precision cutting with MD simulation have not been reviewed systematically before, especially for the surface generation mechanism. In this paper, the principles and fundamentals, the development and application, and advantages and current limitations of MD simulation of surface generation mechanism in ultra-precision cutting are reviewed. Relevant MD simulation studies of surface generation mechanism are summarized with a focus on (a) the minimum cutting thickness; (b) the effect of tool geometry parameters: rake angle, edge radius; (c) the influence of cutting parameters: feed rate, cutting depth and cutting speed; (d) the influence of cutting force and cutting temperature; (e) the effect of crystal orientation. This paper provides a brief review of surface generation mechanism in ultra-precision cutting with the MD simulation to preliminary understand MD simulation and how it applied in studying nanosurface generation mechanism. [ABSTRACT FROM AUTHOR]

With the introduction of new technologies, the scope of miniaturization has broadened. The conditions under which complicated products are designed, manufactured, and assembled ultimately influence how well they perform. The intricacy and crucial functionality of products are frequently only fulfilled through the use of high-precision components such as micro gears. In power transmission systems, gears are used in a variety of industries. Micro gears or gears with micro features, with tolerances of less than 5 μm, are pushing manufacturing processes to their technological limits. Monte-Carlo simulation methods enable an accurate forecast of inaccuracies in compliance. The complexity of the micro gear's design, on the other hand, increases the simulation computation and runtime. An alternative method for simulation is to create a surrogate model to predict the behavior. This paper proposes a statistical surrogate model to predict the conformity of a pair of micro gears. Afterward, the advantage of the surrogate model enables the optimal tolerance assignment while taking gear functionality and production cost into account. [ABSTRACT FROM AUTHOR]

The numerical control machine tool is an important part of manufacturing. The speed and accuracy of the machine tool simulation and the monitoring of machine physical model movement, model collision, and operation health are the most common bottlenecks. The previous studies on these problems are discrete and poor in real time. In this paper, combined with the digital twin (DT) technology, a perception-monitor-feedback system architecture is constructed. Based on the improved Gilbert–Johnson–Keerthi (GJK) distance algorithm, the collision information of tool and machine tool can be better detected during the simulation and monitoring of machine tool movement, and the more real workpiece shape can be displayed. Based on the model synchronous motion driven by the production perception data and its potential information extraction, the tool wear online monitoring is carried out. The tool wear online monitoring is performed based on the production perception data–driven model synchronous movement and extraction of its potential information. Finally, the usability and efficiency of the system are verified by an example of a typical shaft part processed by a numerical control machine tool. [ABSTRACT FROM AUTHOR]

High-velocity oxygen-fuel (HVOF) thermal spraying is a coating process involving multidisciplinary aspects, e.g., fuel–oxidant combustion, flame–particle jet, particle deposition, mass and heat transfer, and even robotic kinematics. Like most coating processes, in HVOF processes, coating thickness is a significant property determining the coating performance; hence, this property should be accurately controlled during the process. In view of green, smart, and digital manufacturing, the coating thickness prediction model is demanded to produce high-quality coatings efficiently. This paper presents an approach to parametrically simulate the coating thickness in HVOF processes via an integrated numerical model. Firstly, an axisymmetric computational fluid dynamics (CFD) model is constructed to compute the behaviors of the fuel–oxidant combustion, flame–particle jet, and particle deposition distribution. Secondly, based on the particle distribution in a 2D axisymmetric model, a 3D single coating thickness profile model is developed by constructing a circular pattern using the axis of the nozzle. Further, this profile is smoothened by a Gaussian model, and its mathematical expression is obtained. Finally, a numerical model couples spray paths with the mathematical expression to model the coating thickness distribution on a substrate surface under industrial scenarios. At the end of this paper, to verify the proposed model's effectiveness, four sets of operating parameters with a single straight path were experimentally implemented. The width and height of the bead-like shape coating were in good agreement with the simulated results. The normalized root-mean-square errors of the cross-sectional profile heights were around 10%. [ABSTRACT FROM AUTHOR]

Friction plays an important role in the injection mechanism of squeeze casting machines. To control the injection process of aluminum alloy more accurately, a novel numerical simulation method based on a friction-integrated finite element (FE) model is proposed in this paper. A friction mechanism model of the injection mechanism based on thermohydrodynamic lubrication (THDL) was developed, and with the application of a friction-generating experiment, the influences of temperature, interaction speed, and fit clearance on the friction-related characteristics of an injection mechanism were ultimately evaluated. The THDL model was integrated into a thermomechanical coupling FE model to simulate the multicycle injection process, and the simulation results were compared with those of the general model in the absence of friction. The effects of friction on the temperature, deformation, and fit clearance of the injection mechanism were analyzed. The accuracy of the friction-integrated model was also evaluated in an injection experiment. A multicycle injection experiment platform that measures the temperature and deformation of the injection mechanism online in real-time was developed. When the numerical simulation results of the two models were compared with the experimental data, the friction-integrated model achieved more reliable results than the general model. [ABSTRACT FROM AUTHOR]

The service performance and life of the aero-engine are directly affected by the blade machining accuracy. In the end milling of the flexible blade, the profile tolerance would usually be violated by the deflection errors induced by excessive static deformations under the action of milling force. In order to predict the blade deflection errors, this paper presents an iterative algorithm considering the coupling relationship between milling force and elastic deformation based on the milling finite element simulation model. Then a novel multipoint rod-shaped auxiliary support technology is proposed to suppress the blade deflection errors. Taking the influence of layout parameters on blade deflection errors into account, the layout of auxiliary support is optimized by a genetic algorithm. To verify the effectiveness of the proposed method, an auxiliary support mechanism is designed and manufactured, and the deflection errors suppression experiment is implemented. The measured results show that the prediction error of blade maximum deflection is 17.6%. Furthermore, the blade average deflection error on two measured curves reduces from 45.88 μm to 24.39 μm with the support of the designed mechanism. Thus, this auxiliary support mechanism and layout optimization method can achieve higher accuracy in blade milling. [ABSTRACT FROM AUTHOR]

This paper presents the design of a multi-agent framework that aids engineers in the adaptation of modular production systems. The framework includes general implementations of agents and other software components for self-learning and adaptation, sensor data analysis, system modelling and simulation, as well as human-computer interaction. During an adaptation process, operators make changes to the production system, in order to increase capacity or manufacture a product variant. These changes are automatically captured and evaluated by the framework, building an experience base of adjustments that is then used to infer adaptation knowledge. The architecture of the framework consists of agents divided in two layers: the agents in the lower layer are associated with individual production modules, whereas the agents in the higher layer are associated with the entire production line. Modelling, learning, and adaptations can be performed at both levels, using a semantic model to specify the structure and capabilities of the production system. An evaluation of a prototype implementation has been conducted on an industrial assembly system. The results indicate that the use of the framework in a typical adaptation process provides a significant reduction in time and resources required. [ABSTRACT FROM AUTHOR]