Fig 8 - uploaded by Raj Kumar
Content may be subject to copyright.
Density plot (a) Front, (b) Left and (c) Right views of cutting force measuring machine after topology optimization.
Source publication
Structural Integrity and its response to the subjected cutting forces during machining,
plays a vital role in the performance and the life of the machine tool. The machine tool must meet
the demands of the stiffness and easy maintenance; in absence of this the desired machining accuracy
during cutting operation is not achieved. While at the same ti...
Context in source publication
Context 1
... with dimension considerably less than the given value were also obtained. These members are essential for the load transmission to constrained location, hence were not completely eradicated. The mass of the structure after optimization was found out by multiplying the final volume by density. The mass of optimized part was found to be 1.93 kg. Figs. 8-10 shows the density plots for topology optimization of the stiffener plates of cutting force measuring ...
Citations
... The simulation based on a finite element platform exhibits the advantages of low testing cost, short time, and accurate results compared with the traditional strength checking or vibration analysis of machine tool parts [7]. The machine tool structure has been extensively studied based on finite element software worldwide: Sharma et al. [8] used finite element software to optimize wood-based cutting forces, which increased the natural frequency and reduced the maximum displacement under static and dynamic conditions. Garg et al. [9] proposed a simplified method based on finite element to approximate the natural frequency and vibration mode of the machine tool structure. ...
An optimization design was carried out based on a back propagation (BP) neural network and a genetic algorithm (GA) to improve the stiffness and accuracy of the self-developed MGK6030 five-axis tool grinding machine. First, finite element analysis was carried out on the whole grinding machine based on ANSYS Workbench, and the key parts were found to be the grinding wheel headstock, B axle box body, and column. Sensitivity analysis was carried out after the model parameterization, and ten parameters, which affect the quality, maximum deformation, and first-order mode, were obtained. These parameters were used as input variables. A total of 235 sets of sample data were obtained by using the optimal overall performance of the grinder for the target (large first-order natural frequency, small deformation, and mass). The BP neural network was then used to fit the nonlinear coupling relationship between the input and the output. Thereafter, the optimization function of the GA was used to perform multi-objective optimization in the specified range. Finally, the parameters are verified by software simulation and prototype test. Results showed that the maximum deformation of the optimized machine tool is reduced by 21%, and the first four order natural frequencies are increased by 6.36%, 9%, 6.4%, and 2.84%. The positioning accuracies of the linear axis and rotary axis are increased by 22% and 21%, respectively, which demonstrates the effectiveness of the optimization scheme and provides theoretical and technical support for similar optimization problems.
... By knowing the coordinates of the end-effector (T y , T z ) through Equations (25) and (34), it is possible to calculate the input angles θ 1 and θ 4 . The inverse kinematic analysis of the D2 Deltarobot is based on the coordinates of the end-effector (T y , T z ), which can be used tosolve for the rotation angles θ 1 and θ 4 . ...
... Static simulation is used to analyze the behavior of static models. It is useful for assessing the structural strength of parts and assemblies, as well as observing stresses and deformations under static conditions [25]. ...
... The advantage of motion analysis over static simulation is that it provides features such as kinematic and dynamic analysis, force and torque calculations, and collision detection. These features can be used to simulate the effects of motion, including the influence of gravity, friction, and other physical phenomena, on parts and assemblies [25,26]. Motion analysis simulation allows for identifying potential issues in designs and making necessary changes before creating physical prototypes. ...
Since the beginning of the 21st century, incremental sheet-metal-forming processes, such as single-point incremental forming (SPIF), have been the subject of extensive research. The SPIF process is highlighted as an efficient and cost-effective solution for producing complex parts with different materials and scales, surpassing conventional methods and being ideal for small series and customized products. Various machines can be used to implement SPIF, such as adapted milling machines, serial robots, and dedicated machines, each with its own advantages. However, although it requires a higher initial investment, a dedicated machine offers superior performance. The objective of this project was the creation of a compact and portable dedicated machine, which included the design of suitable kinematics, a mechanical project, and numerical control. The structural design led to the optimization of the dimensions of the robot arms. Direct and indirect kinematics were analyzed. Finally, the careful selection and adaptation of components were carried out, bearing in mind the support system of the forming punch, including the selection and sizing of motors, reducers, and linear actuators. A functional early prototype was successfully built and tested.
... Recommendations for designing CNC high-precision heavy-duty machine tool bearing systems were provided [15]. Sharma et al. (2023) conducted a study to examine structural optimization of machine tools using finite element analysis. The stability of the structure under the influence of cutting forces is crucial for achieving machining precision. ...
... Furthermore, the modal frequencies of the optimized structure increased as compared to the original structure, which increased the gap with excitation frequencies and thereby avoided resonance occurrence. That study aimed to analyze the placement of the stiffener plates using finite element analysis techniques to reduce the overall weight and enhance the stability of the machine tool structure, providing insights into the optimization of machine tool structures [16]. Kiyono et al. (2023) introduced a new approach to address stress-based topology optimization problems by utilizing a binary structural topology optimization method. ...
Machining characteristics were applied to topology optimization for machine tool structure design improvement in this study, and the goals of lightweight and high rigidity of the structure were achieved. Firstly, an ultrasonic-assisted grinding experiment was carried out on zirconia to investigate the surface roughness, surface morphology, grinding vibration, and forces. Then, the topology optimization analysis was conducted for structure design improvement, in which the magnitude of the grinding vibration was utilized as the reference for selecting the topology subsystems and the grinding force was used as the boundary conditions of the static analysis in the topology optimization. Hence, columns, bases, and saddles were redesigned for structure stiffness improvement, and the variations in the effective stress, natural frequency, weight, and stiffness of the whole machine tool were compared accordingly. The results showed that the deduced topological shape (model) can make the natural frequency and stiffness of the whole machine tool tend to be stable and convergent with a weight retention rate more than 75% as the design constraint. The subsystem structures with larger effective stress distributions were designated for stiffness improvement in the design. At the same time, the topological shape (model) was also employed in the design for weight reduction, focusing on minimizing redundant materials within the structure. In contrast to the consistency of the modal shapes before and after topological analysis, the sequential number of the modal mode of the machine tool model after topological analysis was advanced by two modes relative to those of the original situation, which means the original machine tool may be out of its inherently resonant frequency range. Also, the natural frequencies corresponding to each mode had an increasing tendency, and the maximum increase was 110.28%. Furthermore, the stiffness of the machine tool also increased significantly, with a maximum of 355.97%, leading to minor changes of the machine tool’s weight. These results confirm that the topology optimization based on machining characteristics proposed in this study for structure redesign improvement and stiffness enhancement is effective and feasible.
... The simulation based on a finite element platform exhibits the advantages of low testing cost, short time, and accurate results compared with the traditional strength checking or vibration analysis of machine tool parts [7]. The machine tool structure has been extensively studied based on finite element software worldwide: Sharma et al. [8] used finite element software to optimize wood-based cutting forces, which increased the natural frequency and reduced the maximum displacement under static and dynamic conditions. Garg et al. [9] proposed a simplified method based on finite element to approximate the natural frequency and vibration mode of the machine tool structure. ...
An optimization design was carried out based on a back propagation (BP) neural network and a genetic algorithm (GA) to improve the stiffness and accuracy of the self-developed MGK6030 five-axis tool grinding machine. First, finite element analysis was carried out on the whole grinding machine based on ANSYS Workbench, and the key parts were found to be the grinding wheel headstock, B axle box body, and column. Sensitivity analysis was carried out after the model parameterization, and 10 parameters, which affect the quality, maximum deformation, and first-order mode, were obtained. These parameters were used as input variables. A total of 235 sets of sample data were obtained by using the optimal overall performance of the grinder for the target (large first-order natural frequency, small deformation, and mass). The BP neural network was then used to fit the nonlinear coupling relationship between the input and the output. Thereafter, the optimization function of the GA was used to perform multi-objective optimization in the specified range. Finally, the parameters are verified by software simulation and prototype test. Results showed that the maximum deformation of the optimized machine tool is reduced by 21%, and the first four order natural frequencies are increased by 6.36%, 9%, 6.4%, and 2.84%. The maximum positioning accuracies of the linear axis and rotary axis are increased by 22% and 21%, respectively, which demonstrates the effectiveness of the optimization scheme and provides theoretical and technical support for similar optimization problems.
... Optimizations were carried out with a genetic algorithm, and functions of necessary constraints and objective values were obtained with artificial neural networks. Sharma et al. [36] analyzed and optimized the structure of a machine tool and found that an optimized structure with stiffeners led to a decrease in the maximum displacement, thus increasing the stiffness of the machine structure while avoiding resonance. Liu et al. [37] constructed a robust optimization research model based on scenario sets and reallocated distribution paths according to the change in demand. ...
The energy absorption structure of a train is an important part of passive safety protection during train collisions and is the last line of defense to protect both passengers and trains. In the design process of a train energy absorption structure, improved stability and greater energy absorption capacity is required. A cutting anti-climbing energy absorption structure offers good stability and energy absorption in a collision, but it can easily generate considerable heat in the energy absorption process. Therefore, it is important to conduct thermal–solid coupling simulations and crashworthiness optimization for cutting energy absorption structures. To improve the passive safety protection capability of high-speed trains, this paper experimentally and numerically explored the crashworthiness of a cutting-type energy-absorbing structure composed of an anti-creeper device, an energy-absorbing tube, cutting knives and knife-supporting tools. By adopting the Johnson–Cook material model, a finite element model was developed to study its energy absorption characteristics in a coupled heat–solid state. The effects of cutting depth (D), cutting knife front angle (A) and cutting width (W) on energy absorption (EA), cutting platform force (Fmean) and peak cutting force (PCF) were analyzed based on the validated simulation model. The results showed that EA, Fmean and PCF increase with increasing D and W, while EA, Fmean and PCF decrease with increasing A. The GRSM was employed as the optimization algorithm, and a gain matrix–cloud model optimal worst method (G-CBW) multiobjective decision algorithm was proposed to obtain the most satisfactory configurations from the Pareto front solution. The relative errors from the optimal and finite element results of EA, Fmean and PCF were 3.5%, 2.1% and 2.2%, respectively. All the crashworthiness indicators were improved considerably.
... It was MCDM problem so, (BWM) best worst technique was used to rank the various measures and TOPSIS was utilized to weight these criteria for the possible best supplier selection among the all-supplier alternatives. These techniques are also used in various field such as in banking sector, electronic sectors, thermal energy application [40][41][42][43][44][45], optimization of the different parameters in industry [46][47][48][49][50]. Anser et al. [51] proposed AHP and F-TOPSIS two MCDM approaches for the appropriate selection of site for the solar power project in Turkey. They classified different sites of Turkey based on their social, environmental & economic factors. ...
Multi-criteria decision making (MCDM) have been utilized by a variety of researchers beginning in the early 1970 s with the goal of improving decision-making in the field manufacturing industry. MCDM is an operational research method that also incorporates software. This method assists in decision making by assessing numerous contradicting criteria or objectives all at once. The MCDM approaches have evolved throughout the course of the years, and as a result, several new ways have been developed. This review article performs a literature survey of various optimization techniques that are utilized to select the best possible option among various options in various criteria such as selection of supplier, selection of best raw material and optimization of machining parameters in manufacturing processes. The analysis of a number of approaches that was carried out in the study enables a specific approach to be chosen that is appropriate for the circumstance.
