This paper introduces a new geometric error modeling approach for multi axes system (MAS) based on stream of variation (SOV) theory, especially for multi-axis precision stage. SOV is used for ...measuring product quality for some complicated multi operations system, which is widely used in error propagation in engineering field. This paper introduces SOV concept into geometric error modeling for MAS. Instead of different process in manufacture, the new error modeling approach regards each axis as a station in MAS, and calculates the deviations after each station which is considered as upstream factor to next station. It is clear to observe how geometric errors give influence and how deviations accumulate. Different with conventional methods which are only used for error compensation in machine tools, the new error model is beneficial for sensitive error control and optimal configuration selection in design part. In addition, the new error modeling has some merits such as debugging easily due to observe the deviations after every station. A case study of new error modeling procedure for six-axis stage (SAS) in optoelectronic packaging system (OPS) is developed, and applications related to error reduction order and optimal configuration selection are processed based on the new error model.
•This new geometric error modeling approach based on SOV can understand how errors propagate and how deviations accumulate, which is beneficial for debugging in design part.•Sensitivity analysis based on the new error model is more efficient than conventional method.•A case study of new error modeling is introduced, and applications related to error reduction order and optimal configurations selection is processed.
The additive manufacturing research confides in developing three-dimensional (3D) printing routes for the fabrication of devices with multifunctional materials in various interesting application ...areas such as self-healing, energy conversion/storage/harvesting, and sensing platforms. This paper reports the design optimization, fabrication, and characterization of a multi-axis pressure sensor with temperature compensation using fused filament fabrication (FFF) 3D printing of conductive carbon-based composites. Additive manufacturing offers a faster fabrication of complex structures with multiple properties such as electrical, mechanical, or thermal properties. The complex and costly metal printing can be neglected, as the 3D printing of a conductive polymer is a promising technology to utilize the electrical properties of the printed materials along with mechanical flexibilities. The present work focuses on the development of a multi-axis pressure sensor integrated with a temperature-sensing element. The pressure-sensing mechanism is based on piezoresistive behavior while temperature sensing relies on temperature-dependent resistance shift of the carbon composite. The pressure sensing part comprises a hollow structure to ensure mechanical deformation upon applied pressure while the temperature sensor is buried inside the housing material. Herein, the conductive three-dimensional printable polymer is synthesized by solution casting method with Polylactic acid (PLA), multi-walled carbon nanotubes (MWCNTs), and dichloromethane (DCM) solvent, which is transformed into filament for printing. The direction of pressure and magnitude of temperature can be evaluated separately by calibrating the responses of an applied force and temperature. Moreover, an integrated temperature sensor calibrates the shift in the electrical resistance of the pressure sensor due to the alteration in environmental temperature. The additive manufactured dual pressure and temperature sensor could open up broad applications such as human motion monitoring systems and force sensing.
•Constructing the MBS model of a multi-axis CNC machine tool based on FMA method.•Establishing pose transformation matrix of motion shaft in twist exponential form.•The POE model of machining system ...is established based on the screw theory.•Proposing the error evaluating indicators based on meta-action layer.•We deduce the general mathematical expression of machining allowance error.
This paper presents the solution to evaluate and predict machining precision of a multi-axis computer numerical control (CNC) machine tool. The “function-motion-action” method is used to describe the motion relationships of a multi-axis CNC machine tool, and the multi-body system structure model of the machining system is further constructed. By analyzing the motion process of the machine tool based on the meta-action layer and considering the motion transfer relations in meta-action chains, the kinematic models of each motion shaft are established in twist exponential form. According to the structural and kinematic relationships of these motion shafts, the kinematic and kinematic error models of the machine tool can be easily obtained. Then, the distance error formula is used to deduce the general model of machining allowance error. A simulation test and practical experiment are performed on a type of CNC controlled 5-axis machining center. The experiment results show that the proposed method is universal, and it can greatly simplify the kinematic analysis of multi-axis CNC machine tools.
Abstract
Multi axis CNC machine tool has good linkage processing effect. Through the application of integral impeller in CNC machine tools, to improve the adaptability of CNC machine tools to complex ...surface processing parts, to improve the accuracy of multi axis CNC machine tools. The first part of this paper introduces the integral impeller and its machining characteristics; the second part introduces the basic NC machining process of integral impeller; the third part discusses the application of impeller in multi axis CNC machine tools from the creation of guide track, the simulation of integral impeller, software processing and generation. The purpose is to provide some reference for the processing and production of integral impeller.
Tool path planning is critical to fully realise the producing capabilities of multi-axis machine tools and improve the precision and efficiency in multi-axis machining. Up to now, more than 400 ...articles have been published for tool path planning of multi-axis machine tools. Among them, most of the articles mainly focus on the topology of tool path while few studies are conducted for planning of tool orientation. Moreover, the factors that affect the planning of tool orientation are derived from multiple aspects, such as interference, collision and cutting strip width, which poses great challenges on tool orientation planning. To generate a time-optimal tool path with high machining precision, there is an urgent need to ascertain the influences of tool orientation arrangement on the multi-axis machining process. Therefore, in this work, a literature review on tool orientation planning of multi-axis machine tools is implemented. The main factors that influence the planning of tool orientations are systematically summarised, and the advantages and disadvantages of the corresponding methods related to these factors are discussed. Some research issues and challenges encountered in the tool orientation planning are identified. Furthermore, the methodologies that have potential to address the research issues in the future are prospected.
In this study, we focus on topology optimization considering the accessibility constraint, which is a constraint that removes inaccessible regions from multiple linear directions. To detect ...inaccessible regions, we propose a method using a fictitious anisotropic diffusion equation. The proposed equation can simultaneously consider access from a bi-direction, which means one access direction and its 180-degree rotated direction, contributing to computational efficiency improvements. Additionally, we formulate a representative optimization problem with the accessibility constraint from multiple bi-directions and perform sensitivity analysis based on a coupled fictitious physics model. The model can resolve the difficulty in converging to a single optimal shape in the previous formulation method. Furthermore, through various numerical examples, we verify whether the numerical result converges to the optimal structure satisfying the accessibility constraint.
The stress nonuniformity on the loading neck is an important factor leads to the local force error of an individual multi axis force sensor in a distributed multi axis force sensing system. The ...stress correlation coefficient is used to characterize the stress nonuniformity. The stress correlation coefficient decreases with the increase of the loading offset. A full-constrained high-relative-stiffness-ratio structure is important for a multi-axis force sensor to obtain a good stress correlation coefficient on its loading neck under various external loads. An individual MAFS with two loading necks is employed in the sensing system to increase the relative stiffness ratio. A thin loading neck, a long loading neck distance, and a high stiffness loading frame are important for the high-relative-stiffness-ratio structure. A local high-relative-stiffness-ratio structure is valuable for a large-scale DMAFSS. The mechanical hinge on the loading neck is useful to realize a large-scale lightweight DMAFSS. The extreme load including the load outside the reference loading zone and the concentrated torque affects the stress correlation coefficient apparently which should be specified in the future standards.
The timely identification of diseases in maize leaf offers several benefits such as increased crop productivity, reduced reliance on harmful chemicals, and improved production of healthy crops, ...resulting in enhanced economic returns. Computer-aided systems (CAD) play a crucial role in agriculture by enabling timely and efficient disease identification in plant leaves. Deep learning-based CAD systems facilitate accurate and rapid diagnosis of maize leaf diseases. In this research, we introduce an advanced vision transformer model that achieves exceptional accuracy and inference speed in detecting diseases in maize leaves. To begin with, we adapt the Multi-axis vision transformer (MaxViT) model to a 4-class maize dataset, creating a lightweight structure that offers improved accuracy and inference speed. Furthermore, we enhance the accuracy by replacing the conventional convolutional structure in the MaxViT architecture's Stem with a Squeeze-and-Excitation (SE) block. In addition, to boost accuracy further, we employ the Global Response Normalization (GRN)-based MLP from the ConvNexTv2 architecture instead of the MLP in the MaxViT architecture. Notably, we combine the PlantVillage, PlantDoc, and CD&S datasets from the literature, resulting in the creation of the most extensive dataset available. This dataset is then divided into three sets: training, validation, and testing, enabling the evaluation of the generalization abilities of the deep learning models. Our study goes beyond previous research by offering a comprehensive comparison of the performance of over 28 CNN models and more than 36 vision transformer models on the newly created dataset. By achieving a remarkable accuracy rate of 99.24% and a high inference speed, the proposed method outperforms all existing deep learning models in the literature. Therefore, it has been demonstrated that this advanced vision transformer model, based on MaxViT, is exceedingly effective for practical applications in agriculture.
The measurement and identification of the four position-independent geometric errors (PIGEs) and six position-dependent geometric errors (PDGEs) in the rotary axis are necessary to reduce their ...contributions to the overall machining errors of a multi-axis machine tool. In this paper, a new geometric error identification method using a tracking interferometer is presented by considering the rigid-body motion constraint in multilateration. The rigid-body motion constraint is introduced to establish a new coordinate calculation model for the measurement points, and an identification process is presented to separately identify the PIGEs and PDGEs by deriving identification models based on established geometric error models. The main novelty of the proposed method lies in the consideration of the rigid-body motion constraint, which makes the identification more robust against random factors. Monte Carlo simulations and verifying experiments were performed for validation. The results show that the PIGEs and PDGEs in the rotary axis can be successfully separated and identified by the new method. Improved identification accuracy compared with the traditional method is achieved. The maximum angular positioning error was reduced by 84% after compensation. A lower uncertainty in the identified errors compared with those obtained by the traditional method and instrument software is achieved. The proposed method is validated by comparing the identification results with those obtained by the instrument software and laser interferometers.
Display omitted
•Compared with the widely adopted traditional mathematical model, the new mathematical model uses the rigid-body motion constraint to reduce the effects of random factors.•PIGEs and PDGEs defined by ISO 230–7 are implicitly separated based on the new identification model.•The feasibility and effectiveness of the proposed method are verified by Monte Carlo simulations and measurement experiments.
This article presents an investigation into the life of the torus milling cutter with round cutting inserts when multi-axis milling process in high-speed cutting conditions of Inconel 718 under ...various of kinematic variants of multi-axis machining. The experiments were performed at varying tool axis orientation parameters of; lead angle: 1.37–20° and tilt angle: −18.86–20°. A new research approach was introduced to evaluate the possibility of extending the life of the torus milling cutter by changing the tool axis orientation in multi-axis machining. The analysis performed includes the tool life, tool wear patterns, and mechanisms as well as its relationship with the chip and machined surface morphology and kinematics variants of multi-axis cutting. The experimental results showed that tool wear has begun with smooth abrasion and chipping around the depth of cut line, which then progressed into flank wear and finally notching and flaking via mechanisms of abrasive and adhesive wears. However, for each of the analyzed kinematic variants of multi-axis cutting, the above processes proceeded in a completely different way. Thus, by changing the tool axis orientation in a controlled manner, it is possible to influence the cutting conditions in the tool-chip and chip-workpiece interfaces; hence, efficiently displace the point of contact and thus offset the negative impact of the concentration of tribological interactions at that point. Consequently, it was possible to slow down the tool wear development and prolong the torus milling cutter life to a maximum 78%. There was also a strong influence of multi-axis cutting conditions and tool wear patterns on the morphology of the chip and the machined surface. In conclusion, the kinematic variant of multi-axis cutting (i.e. axis orientation) using the torus milling cutter of Ni-based superalloys plays an important role in the possibility of extending tool life.
•The kinematic variant of multi-axis cutting of a Ni-based superalloy has a significant impact on the torus milling cutter life.•The differences in wear of each individual round cutting insert of the torus milling cutter are due to their radial run-out.•Different forms of tool wear, chip morphology and machined surface were found for each of the multi-axis cutting variants analyzed.
PDF
