CIRP Journal of Manufacturing Science and Technology最新文献

Sintered NdFeB, owing to its outstanding magnetic properties, finds widespread applications in diverse fields. However, its susceptibility to corrosion limits its utility. To enhance its corrosion resistance, a rotating transverse magnetic field is incorporated into the electrical discharge machining milling (EDM-M) process. Comparative experiments are conducted on sintered NdFeB by EDM-M, fixed transverse magnetic field assisted EDM-M(FTMEDM-M), and rotating transverse magnetic field assisted EDM-M(RTMEDM-M). Results indicate that the RTMEDM-M process yields the least surface cracks, the least "caves", and the recast layer which is the most uniform and the most continuous. Its impedance value is the highest, self-corrosion potential is the largest, and self-corrosion current density is the lowest according to its electrochemical impedance spectroscopy (EIS). In addition, its mass loss per unit area is the least, with the latest and the weakest reaction of chemical corrosion of the workpiece surface.

Complete inspection of workpiece surface integrity invariably involves a form of destructive testing to enable the assessment of microstructural defects such as machining-induced white layers and near-surface plastic deformation. The incumbent offline and destructive microscopy inspection process is incompatible with both a digital and sustainable manufacturing vision of zero waste, as such, a non-destructive technique which utilises a novel X-ray diffraction surface integrity inspection method (XRD-SIIM) has been developed. This approach has been designed to complement traditional machinability-type assessments of tool life and machined surface topography, establishing a new process flow for validation. In this paper, for the first time, non-destructive on-machine validation of workpiece microstructural surface integrity is demonstrated, via a comparative investigation into the effect of insert grade, cutting speed and coolant delivery method on the depth of the imparted plastic deformation depth. It is shown that XRD-SIIM allows repeatable, non-destructive determination of deformed layers within a typical machining centre enclosure, with comparable findings to the incumbent cross-sectional microscopy approach. The generation of surface integrity digital fingerprints of a machining operation facilitates rapid comparison between testing variables, with a transition to an objective quantifiable assessment rather than one which open to subjectivity. In turn, XRD-SIIM expedites the development and benchmarking of new operations, tooling, materials, or coolant.

This paper presents an integrated approach for joint decision-making in reliable product design and resilient supply chain network design within a two-echelon capacitated network. Our methodology simultaneously addresses two crucial decisions faced by manufacturing industry by integrating the design processes of modular products and their supply chain networks, allowing for multiple production facilities and product variants. Through redundancy allocation, we optimize product reliability within production facilities while considering component sourcing from multiple suppliers. Our approach employs three resilience strategies—multi-sourcing, supplier fortification, and backup supplier contracting—to enhance supply chain resilience against disruptions. A case study solved using a genetic algorithm demonstrates the effectiveness of different resilience strategy combinations in achieving various levels of production resilience. This research offers insights into integrated decision-making for enhancing product reliability and supply chain resilience, thereby providing valuable guidance for industry practitioners. Furthermore, the sensitivity analysis highlights the framework’s capability to minimize total costs by prioritizing resilient designs and strategically investing in resilience strategies as costs of production shortage increase. This analysis underscores the interconnected nature of product and supply chain network design decisions in mitigating disruptions and enhancing production resilience.

The dynamics of thin-walled parts are highly affected by the clamping conditions. Clamping stiffness is a function of c lamping force and surface roughness profiles of the clamp and part. Since the surface profiles cannot be altered, estimating clamping stiffness as a function of the clamping force is essential to simulate vibrations of the machined thin-walled parts. This paper presents the modeling of clamping stiffness as a function of the applied clamping force and material properties. Surface profile parameters are estimated from the identified contact stiffnesses evaluated using the Finite Element (FE) model. The contact stiffnesses are either predicted directly from the proposed mechanics model of the part or estimated from the Fractal surface parameters. It is shown that an average clamping stiffness can be predicted from the Fractal surface parameters, or directly and more accurately from the static model of the clamped part.

High-speed milling (HSM) of Ti-6Al-4V is subjected to complex thermo-mechanical loads, leading to alteration in metallurgical conditions within the cutting deformation zones, adversely impacting the mechanical performances of manufactured products. Hence, inclusive insight into microstructural alterations within the Adiabatic Shear Band (ASB) and the milled surface becomes essential for better service performance. This study first developed a Finite Element (FE) milling model to simulate the machining process of Ti-6Al-4V. The proposed FE model is validated through experimental results regarding cutting forces (CFs), cutting temperature (CT), and chip geometry, where the absolute relative error between simulations and experiments was less than 15 %. Secondly, Zenner-Holloman (Z-H) and Hall-Petch (H-P) equations were incorporated into a user-defined subroutine to simulate dynamic recrystallization (DRX) for grain size and microhardness prediction. Simulation results revealed that the grains became finer in the ASB than on the milled surface. In particular, when the cutting speed and feed rate were increased to 350 m/min and 0.30 mm/tooth, the grain size in the ASB decreased from 14 to 0.68 and 0.44 µm, while in the topmost milled surface, it reduced to 7.06 and 6.75 µm, respectively. Conversely, microhardness exhibited an inverse correlation with grain size and increased with cutting speed and feed rate. Furthermore, the impact of increased plastic strain and temperature on the grains during chip segmentation was also examined. Finally, the proposed FE model validity was established by comparing simulated results with experimental data using advanced characterization techniques. This research significantly contributes to a comprehensive understanding of microstructural evolution and its implications for the mechanical performance of machined titanium components.

Cutting tool materials are the backbone of machining and play a vital role in the manufacturing industry. Innovation in cutting tools is important for customized and demanding applications. This state-of-the-art review is focused on innovations and future research directions for cutting tools covering i) tool materials/microstructure/property relationships, ii) coatings and their effect on tool performance, iii) cutting edge and functional surface preparation and effect on tool performance, iv) tool geometry for high performance and stable machining considering rapid machining, sustainability, and circularity aspects. The vision is to identify tool material/coating/geometry/functional surface relationships for significant improvement in machining performance. This paper includes perspectives from several research groups with a detailed discussion on current advances, capabilities, and challenges in engineered design of cutting tools, materials, coatings, structures and sets a new agenda for future tooling and research directions.

This study investigates the discharge energy distribution during Powder Mixed Electrical Discharge Machining (PMEDM) at different values of pulse duration, peak current and powder concentration. A finite element method (FEM) based numerical model has been developed to estimate the power distribution factor by reverse simulation. The developed model has been used for determining the fraction of discharge energy distributed to the electrodes. The model and experimental values of total fraction of discharge energy are in close agreement with the error varying between 0.47 % to 14.04 % for tool and 0.82 % to 9.82 % for workpiece. Parametric influence on components of discharge energy has also been discussed.

This research compares auxiliary energy-assisted friction stir welding (FSW) techniques with conventional FSW when joining dissimilar materials. Specifically, it conducts numerical modeling and experimental validation for the effectiveness of plasma-assisted FSW and induction-assisted FSW for DH36 steel and 6061-T6 aluminum alloy. Fully coupled 3D computational fluid dynamics (CFD) models, incorporating the multi-species transport method, were developed, where the species mass fractions of the workpieces are transported through diffusion, convection, and reaction sources for individual species. Based on the temperature validation, the dedicated heat flux based on the rectangular heat flux and Gaussian heat flux distribution were considered for induction coil and plasma arc heating on the DH36 steel side, respectively. The established conventional and auxiliary energy-assisted FSW models were validated against experimentally observed temperature fields and the joints’ material features. Results indicate that the assistance of plasma and induction auxiliary energy sources increased the temperature field, strain rate, and flow velocity without forming stagnant zones on the steel side caused by reduced dynamic viscosity. In plasma arc-assisted FSW, the steel could not extrude effectively from the base steel sheet due to deficient heat and flow velocity input; therefore, defect-prone coarse steel fragments were blended with the Al matrix. In induction-assisted FSW, the uninterrupted steel layer was extruded from the steel side and placed on the Al side, which was caused by enhanced heat build-up and flow velocity. Moreover, induction-assisted FSW achieved symmetric material flow on both advancing and retreating sides, resulting in defect-free welds.

This article presents a hybrid model to predict the positions of the ball screw drive system of machine tool and then modify the trajectory through constructing a pre-compensation method to reduce servo errors in machine motion axes. To achieve this objective, a flexible control model is initially developed to characterize the ball screw drive system, and by leveraging this model, a high-bandwidth controller is constructed, with its physical representation, i.e. the state-space equation, being derived. Subsequently, a data-driven hybrid model is proposed to predict the positions of the ball screw drive system concerning the next multiple time steps from the current time step, and then the predicted positions associated with these steps are utilized as initial conditions to adjust and compensate for the physical model’s prediction errors corresponding to these multiple time steps. As a result, a compensated trajectory with high tracking accuracy is generated. Finally, experiments confirm that the proposed prediction method offers superior prediction accuracy and enhanced adaptability, and the pre-compensated trajectory leads to reduced tracking errors.

This paper aims to quantitatively analyze the relationship between forces acting on the tool tip and tool movement during drilling operations. The study encompasses axial and lateral vibrations superimposed on the nominal tool movement, arising from rigid body motion (rotational and axial velocities). Specifically, only forces attributed to the cutting process are considered, excluding considerations of indentation forces around the chisel edge. The research adopts a generalized approach, spanning from tool measurements to establishing the force model. The investigation involves measuring cutting forces and correlating them with the varying rake and inclination angles of the drill’s cutting edges. An analytical model is proposed to describe the distribution of all local force components along drill edges, considering the evolution of forces and geometry. The dynamic coefficient matrix is evaluated by using the identified cutting coefficient and tool geometry. Validation of the proposed methodology is demonstrated through drilling experiments on Ti6Al4V alloy, utilizing three solid carbide drills with distinct geometries. The proposed procedure allows complete identification of the dynamic characteristics from the measurements taken at the entrance stage of hole drilling operation. Moreover, the influence of tool geometry on cutting coefficients and dynamic coefficient matrices are discussed.