Subsequent Machining Research Articles

Oscillating laser-arc hybrid additive manufacturing of aluminum alloy thin-wall based on synchronous wire-powder feeding

Synchronous wire-powder feeding was adopted to overcome the poor mechanical properties of aluminum alloy thin-wall caused by limited filling composition in wire-based laser-arc hybrid additive manufacturing. The results showed that the optimized Mg powder feeding improved the droplet transfer into a fine spray mode with reduced transition time by 18 %. Moreover, not only the effective width coefficient of thin-wall increased from 89 % to 95 %, but also the subsequent machining allowance reduced from 1.25 to 0.48 mm. The synchronous wire-powder feeding improved the formation accuracy by 61.6 %. Although the deposition microstructure was mainly composed of dendrites with obvious direction and increased average grain size by 54 %, a new Mg2Si strengthened phase was also found. The ultimate tensile strength of thin-wall was increased by 12 % from 227.3 to 255.5 MPa. The related evolution mechanisms of deposition stability and mechanical properties by optimized powder feeding on the hybrid additive manufacturing were mainly discussed.

Improving the technology for restoring worn parts based on cold plastic deformation

Technological control scheme for forming worn parts during their restoration by deforming broaching is proposed. Particular attention is paid to the study of the stress-strain state, which provided the conditions for creating the necessary plastic flow of the product material towards the worn areas and made it possible to compensate the wear amount in these areas of the product and provide an allowance for subsequent machining. Taking into account the peculiarities of parts restoration technological process, the relationship between the required circumferential strain of the outer surface and the total tension on the hole is established. The influence of the number of deforming elements that perform the required deformation on the accumulated strain on the inner surface of the part was investigated. This made it possible to establish that the maximum accumulated strain of the inner surface is provided by the maximum number of elements with a minimum tension on the element. On the outer surface, the value of the accumulated strain does not depend on the number of deforming elements, but is determined only by the total tension and the workpiece thickness. Based on the simulation of deforming broaching in a wide range of changes in operating parameters, tool geometry and workpiece thickness, an analytical dependence was obtained to determine the angle that ensures the absence of axial strains when the workpiece is deformed. The necessary broaching modes and tool geometry were determined, which will ensure the required dimensions of the machined or restored part.

Impact of melt pool geometry variability on lack-of-fusion porosity and fatigue life in powder bed fusion-laser beam Ti–6Al–4V

Powder bed fusion-laser beam (PBF-LB) parts experience a significant decline in fatigue performance when process-induced defects are present. In this work, a decline in 4-point bend fatigue life was observed in PBF-LB Ti–6Al–4V coupons fabricated at constant power with increasing scanning velocity and which underwent subsequent stress relief and surface machining. Specifically, the presence of pores that resemble lack-of-fusion (LoF) and a decline in fatigue life were observed at scanning velocities lower than that expected from prior published work. It was hypothesized that this unexpected presence of LoF pores resulted from melt pool geometry variability that was not considered in prior work when the LoF criterion was implemented. Further, these pores can be small in size and infrequent in their occurrence when the melt pool geometry variability is not severe. Such sparse pores are challenging to characterize using conventional 2D characterization methods. This work leverages tall and narrow coupon geometry and high-resolution X-ray micro computed tomography (X-μCT) to capture LoF porosity. The results show that a modified melt pool overlap-based LoF criterion considering melt pool geometry variability captures the unexpected occurrence of LoF pores observed in X-μCT. In addition, the LoF percent metric displays a strongly negative correlation with fatigue performance. The insights from this work provide guidance on characterizing melt pool geometry variability across scan lines to systematically evaluate processing parameters that generate LoF pores, which, in turn, could lower fatigue performance.

Wire and arc additive manufacturing for strengthening of metallic components

Wire and arc additive manufacturing (WAAM), also known as wire arc directed energy deposition (WA-DED), offers valuable capabilities not only for manufacturing but also for strengthening and repairing aging components. This paper employs the finite element (FE) method to investigate the influence of deposition parameters on the strengthening efficiency of damaged steel plates strengthened by WAAM material. The study calibrates the inherent strain method (ISM) with thermo-mechanical analysis to accurately predict residual stresses (RS) in manufactured samples, demonstrating that the ISM enhances computational efficiency while effectively predicting RS. It thoroughly examines key parameters such as the deposition direction, maximum thickness, and the geometric configuration of the WAAM material, including shapes and in-plane dimensions. The results indicate that deposition perpendicular to the loading direction provides better performance compared to deposition along the loading direction as it induces less normal and through-thickness stresses. Furthermore, this research determines the optimal maximum thickness for the WAAM material, showing that an increase in thickness can lead to higher maximum tensile stresses at the interface between the newly WAAM material and the underlying base plate. The study also establishes the optimal in-plane dimensions for the WAAM material. The results suggest placing the maximum thickness of WAAM material near the damaged area and gradually decreasing it in two directions to ensure sufficient stiffness around the cracked area, while avoiding an abrupt change in stiffness. This approach generates appropriate compressive stresses around the crack tip and decreases maximum tensile stresses in the plate. The study further illustrates that employing a proper printing strategy without a subsequent machining process can effectively reduce the maximum tensile stress in the steel plate while minimizing material usage.

Multi-objective optimization of high-power fiber laser cutting process using data augmentation-based ANN-Adam model

During fiber laser cutting of sheet metal, excessive heat-affected zone (HAZ) and recast layer thicknesses (RLT) can adversely affect subsequent precision machining and welding processes on the parts. As a result, it is necessary to optimize the process parameters to control the HAZ and RLT. In this work, laser power, gas pressure, focal plane position (FPP), and cutting speed are selected as input parameters. The cutting experiments are conducted using response surface methodology, and the factors that significantly affect the cutting quality are identified by analysis of variance (ANOVA). To improve the generalization ability and robustness of the model, a data augmentation-based artificial neural network (ANN) model is developed to achieve accurate prediction of cut quality characteristics. Further, this study performs a multi-objective optimization of the cutting process parameters using the Adam optimizer. The research results show that the mean relative errors of the ANN model in predicting the HAZ and RLT are 2.44 % and 1.55 %, respectively. The determination coefficients R2 are 0.9542 and 0.9779, respectively. The optimal combinations of process parameters obtained through optimization are laser power 8.9 kW, gas pressure 0.8 bar, FPP 11.8 mm, and cutting speed 1.3 m/min. Experimental validation shows that the relative errors between the predicted and the experiment values of the cut quality characteristics are kept within 5 % under the optimal process parameters. This fully verifies the effectiveness of the optimization model in guiding the selection of laser-cutting process parameters and improving cutting quality.

The effects of deposited layer thickness on the material and geometrical properties of L-DED processed AISI D2 tool steel

ABSTRACT This research focuses on the influences of the deposited layer thickness upon the material characteristics, dimensional accuracy, and also the surface roughness of AISI D2 tool steel processed by laser directed energy deposition (L-DED); while layer thickness was varied, the remaining L-DED system parameters were retained at fixed values. After laser deposition, the D2 specimens were assessed without applying any subsequent machining steps. Sample dimensional accuracy was assessed through both manual measurement and computational methods, with the latter using confocal laser scanning microscopy (CLSM). It was shown that increasing the layer thickness decreases the extent of sample overbuilding. The use of lower layer thicknesses reduced the top surface roughness. However, a monotonic effect was not observed for side surface roughness in relation to the deposited layer thickness. In addition, the microstructures of the L-DED samples were evaluated using a combination of scanning electron microscopy (SEM) with associated energy dispersive X-ray spectroscopy (EDS), and X-ray diffraction (XRD). It is shown that a dendritic morphology is formed for the L-DED processed samples, with a columnar grain structure. Furthermore, the primary crystalline phase generated with the dendritic structure was found to be austenite. The indentation hardness values for the L-DED fabricated parts were noted to be larger for thinner deposited layer thicknesses.

Fast and accurate Zero-defect manufacturing using collaborative real-time photogrammetry

Abstract. For the machining of industrial components, their accurate alignment on operative machines is a crucial step with significant impacts on the whole process, especially when dealing with large-scale elements. To achieve this alignment, a trained operator is needed along with expensive equipment, such as laser trackers, whose correct use requires the measurements of many significant points and is time-consuming. The lack of a precise alignment comes with possible incorrect parts machining, resulting in quality concerns and potentially expensive rework. To face this problem, collaborative real-time photogrammetry is an effective solution for guiding untrained users in correctly positioning various measured and codified components to generate the best solution for machining high-volume parts. The solution proposed in this contribution is part of the TACCO project, co-financed by EIT Manufacturing (co-funded by the EU). It takes advantage of the TACCO system, where auxiliary components (scale bars, dome-shaped components, coded targets and a cross-reference system) are placed on the object to be measured for their correct positioning in order to obtain an optimal photogrammetric reconstruction. This allows the reduction of the error ellipsoids on several uncoded targets, which are calculated through an iterative simulation carried out in a MATLAB environment. Unskilled operators are then guided through an Augmented Reality headset for their correct placement on the real-world object and for defining the positions and orientations from which to acquire images. This methodology will lead to an accurate measurement of the target points to be machined and, thus, a precise alignment process for the subsequent machining operations.

Research progress on nanoparticles reinforced magnesium alloys

Magnesium alloys, acknowledged as the environmentally-friendly engineering material of the 21st century, are ideally suited to fulfill the requirements of lightweight manufacturing. However, the poor plasticity of magnesium alloys hampers their further application. Subsequently, development of nanoparticle-reinforced magnesium matrix composites has been proven to be a promising way to enhance the comprehensive performance of magnesium alloys. The exceptional performance achieved even by very small number of reinforcements stimulated innovation in preparation techniques and in-depth analysis of reinforcement mechanisms. This paper provides a review on key challenges related to their processing, the profound impact of different micro-nanoparticle reinforcements on the microstructure and properties of magnesium matrix composites during solidification and subsequent deformation machining. Additionally, the reinforcement mechanisms of the excellent mechanical performance of the composites are also discussed. This study can provide valuable insights for the understanding of the selection of appropriate reinforcements and processing to optimize the performance nanoparticle-reinforced magnesium matrix composites.

Multi-camera joint calibration algorithm for guiding machining robot positioning considering ambient light and error uncertainty

Multi-camera guided robotic machining is widely used in the removal of flash and burrs on the complex automotive castings and forgings. The multi-camera calibration process, however, is easily affected by the ambient light and uncertain error, thereby resulting in the undesired robot positioning accuracy. To overcome the challenging problem, this paper proposes a multi-camera joint calibration (MCJC) algorithm by considering both the ambient light and error uncertainty to optimize and compensate the positioning error of the image-guided machining robot. The high dynamic range imaging is used at first to obtain stable calibration image data for countering the effects of ambient light changes. Then the uncertainty error in camera self-calibration process is removed by the confidence threshold filtering. The hand-eye calibration matrix is corrected finally using the deviation feedback optimization for positioning accuracy enhancement of the image-guided machining robot. Taking the automotive flywheel shell as the experimental object, the results demonstrate that the average absolute positioning error is controlled within 1.3 mm, the optimum can reach 0.43 mm, and the average relative positioning error is smaller than 0.5 mm. Compared with the existing state-of-the-art algorithms, the proposed algorithm shows high positioning accuracy and strong algorithm robustness, and can meet the requirements for the subsequent image-guided robotic machining.

Analysis of the machining process of short carbon fiber-reinforced polyamide additive manufactured parts

In recent years, additive manufacturing technologies have revolutionized the production of parts, particularly in the aeronautical sector. This new manufacturing paradigm has created significant challenges and opportunities for researchers in materials and manufacturing processes. One important aspect is the development of optimal strategies for finishing-oriented machining of parts produced through additive manufacturing.This article focuses on the analysis of reinforced polyamide materials and the integration of large-scale additive manufacturing using Big Area Additive Manufacturing (BAAM) technology, along with robotic systems for subtractive machining. The aim is to explore the potential of integrating additive and subtractive processes to produce high-quality, large-scale components.The study examines the production and subsequent machining of reinforced polyamide parts using BAAM technology, showcasing the advantages and promising results observed. By combining additive manufacturing with subtractive machining, this research contributes to the ongoing advancements in the field of manufacturing, particularly in relation to reinforced polyamide materials. The findings presented in this article shed light on the potential of integrating additive and subtractive processes in the manufacturing industry, paving the way for more efficient and high-quality production methods.

Dimensional Characterization and Hybrid Manufacturing of Copper Parts Obtained by Atomic Diffusion Additive Manufacturing, and CNC Machining.

The combination of Atomic Diffusion Additive Manufacturing (ADAM) and traditional CNC machining allows manufacturers to leverage the advantages of both technologies in the production of functional metal parts. This study presents the methodological development of hybrid manufacturing for solid copper parts, initially produced using ADAM technology and subsequently machined using a 5-axis CNC system. The ADAM technology was dimensionally characterized by adapting and manufacturing the seven types of test artifacts standardized by ISO/ASTM 52902:2019. The results showed that slender geometries suffered warpage and detachment during sintering despite complying with the design guidelines. ADAM technology undersizes cylinders and oversizes circular holes and linear lengths. In terms of roughness, the lowest results were obtained for horizontal flat surfaces, while 15° inclined surfaces exhibited the highest roughness due to the stair-stepping effect. The dimensional deviation results for each type of geometry were used to determine the specific and global oversize factors necessary to compensate for major dimensional defects. This also involved generating appropriate over-thicknesses for subsequent CNC machining. The experimental validation of this process, conducted on a validation part, demonstrated final deviations lower than 0.5% with respect to the desired final part, affirming the feasibility of achieving copper parts with a high degree of dimensional accuracy through the hybridization of ADAM and CNC machining technologies.

ОПТИМИЗАЦИЯ РЕЖИМА 3-D ПЕЧАТИ ТУРБИННОЙ МЕШАЛКИ ДЛЯ ДИСПЕРГИРОВАНИЯ РАСТВОРОВ ПОЛИМЕРНЫХ КОМПОЗИТОВ

The design of the turbine stirrer is characterized by a rather complex shape of working surfaces and during its manufacture by traditional methods unique molds are required for each type of stirrer, increased material and labor costs are required. The use of 3D printing allows you to obtain products with a complex surface configuration, with minimal costs and which do not require subsequent machining. Analysis was carried out and selection of 3D printing type and material of turbine stirrer intended for mixing of elastomeric nanocomposite solutions components was carried out. FDM (Fused Deposition Modeling) is the most suitable type of 3D printing for solving design and technological problems in the manufacture of turbine stirrers. Plastics of the brands ABS, PLA and PETG have become very widespread in this type of 3D printing. The highest mechanical properties, chemical resistance and the lowest price of the materials under consideration are PETG plastic, which was chosen for the manufacture of a turbine stirrer designed to mix and disperse solutions of elastomeric nanocomposites. An active experiment was implemented according to the В2 plan. The samples are PETG plastic plates printed on a Flying Bear Ghost 5 3D printer. The main mode parameters of 3D printing by FDM type, which determine the strength of samples and printing performance, are: the number of concentric lines that make up the wall of the printed product and the line width. A regression model of the dependence of strength of samples made of PETG plastic on the number and width of lines in 3D printing was obtained. The optimal 3D printing mode of the turbine stirrer is set, providing high strength of the product and performance of the technology.

Suppression of cutting vibration in side milling of laser cladded layer on thin-walled parts with interfacial structures

Laser cladding is being employed for repairing high-end components including thin-walled parts. The heterogeneous interface between cladding layer and substrate can exacerbate cutting vibration during subsequent machining, becoming a bottleneck in remanufacturing thin-walled parts. This paper focuses on exploring the effect of interfacial structures on cutting vibration suppression in side milling of laser cladded layer on thin-walled parts. First, the interfacial structure was proven to be effective for suppressing cutting vibration by increasing modal damping, although the stiffness shows a decreasing trend. Among different interfacial structures, triangular structure showed the best role in cutting vibration suppression, followed by rectangular, semi-circular, and trapezoid. Then, the effects of different structural parameters on cutting vibration suppression were further analyzed based on a Taguchi design. The results showed that the cutting vibration decreases with the smaller interfacial shape factor, larger depth and smaller spacing of interfacial structures. The interfacial structure would be optimal when the interfacial shape factor is 0.06, the interfacial depth is 3.0 mm, and the spacing is 0 mm. As a result, the cutting vibration during milling was reduced by 55.28 %. These findings provide a theoretical basis for high-quality remanufacturing of the thin-walled parts.

The effect of surface finish and post-processing on mechanical properties of 17-4 PH stainless steel produced by the atomic diffusion additive manufacturing process (ADAM)

This study investigates the influence of surface finish and post-processing conditions on the mechanical properties of 17-4 PH stainless steel (SS) produced using the atomic diffusion additive manufacturing process (ADAM). Diverse sample orientations, including horizontal (0°), 30°, 60°, and vertical (90°), were examined, with selected samples undergoing post-processing through machining, polishing, and heat treatment. Tensile strength testing, surface roughness measurement, and hardness measurement were conducted to assess the effect of surface finish conditions and post-processing on mechanical properties. The results reveal significant variations in the tensile strength of the samples based on the build orientation (183.5 to 1034.5 MPa), and subsequent machining. Notably, post-built machining is found to enhance both the absolute ultimate tensile strength (UTS) and the isotropy of the material. Further improvements are attainable through heat treatment. A microstructure analysis, in conjunction with tensile testing outcomes, demonstrates the potential for refining the properties of ADAM-printed samples through suitable machining, heat treatment, and geometry modifications. This study identifies avenues for ongoing process development and outlines possibilities for enhancing mechanical properties of additive manufactured parts, particularly through ADAM process.

Dry and Minimum Quantity Lubrication Machining of Additively Manufactured IN718 Produced via Laser Metal Deposition

Inconel 718 (IN718), a Ni-based superalloy, is immensely popular in the aerospace, nuclear, and chemical industries. In these industrial fields, IN718 parts fabricated using conventional and additive manufacturing routes require subsequent machining to meet the dimensional accuracy and surface quality requirements of practical applications. The machining of IN718 has been a prominent research topic for conventionally cast, wrought, and forged parts. However, very little attention has been given to the machinability of IN718 additively manufactured using laser metal deposition (LMD). This lack of research can lead to numerous issues derived from the assumption that the machining behavior corresponds to conventionally fabricated parts. To address this, our study comprehensively assesses the machinability of LMDed IN718 in dry and minimum quantity lubrication (MQL) cutting environments. Our main goal is to understand how LMD process variables and the cutting environment affect cutting forces, tool wear, surface quality, and energy consumption when working with LMDed IN718 walls. To achieve this, we deposited IN718 on SS309L substrates while varying the following LMD process parameters: laser power, powder feed rate, and scanning speed. The results unveil that machining the deposited wall closer to the substrate is significantly more difficult than away from the substrate, owing to the variance in hardness along the build direction. MQL greatly improves machining across all processing parameters regardless of the machining location along the build direction. Laser power is identified as the most influential parameter, along with the recommendation for a specific combination of power feed rate and scanning speed, providing practical guidelines for optimizing the machining process. While MQL positively impacts machinability, hourly energy consumption remains comparable to dry cutting. This work offers practical guidance for improving the machinability of LMDed IN718 walls and the successful adoption of LMD and the additive–subtractive machining chain. The outcomes of this work provide a significant and critical understanding of location-dependent machinability that can help develop targeted approaches to overcome machining difficulties associated with specific areas of the LMDed structure. The finding that MQL significantly improves machining across all processing parameters, particularly in the challenging bottom region, offers practical guidance for selecting optimal cutting conditions. The potential economic benefits of MQL in terms of tool longevity without a substantial increase in energy costs is also highlighted, which has implications for incorporating MQL in several advanced manufacturing processes.

Experimental study of distortion in side grinding of thin glass lenses

ABSTRACT The production of non-circular thin optical lenses involves initial processes such as circular cutting, grinding, lapping, and polishing. However, shaping the lenses into non-circular forms requires a final cutting process. This study focuses on addressing the distortion of BK7 thin glass parts during side grinding. Two clamping methods were examined to fix the components. The first method, commonly used in the industry, involves bonding the workpiece to a base using resin and subsequent machining, followed by separating the samples from the base by heating the resin. In contrast, this research explores an alternative approach using vacuum clamping. The components’ distortion was measured using an interferometer. The results show that the vacuum clamping method produces more uniform surface parameters for the polished components compared to the typical resin bonding method. Additionally, the analysis reveals that surface parameter variations are more pronounced during square side-grinding compared to circular side-grinding.

Real-time pose correction and registration of complex workpiece in robotic machining considering normal consistency constrains

Efficient and precision model registration of complex workpiece with arbitrary pose is a challenging task that determines the effects of intelligent robotic machining. Aiming at the problems of limited field of view of 3D vision sensors such as surface structured light and the complexity of scanning-splicing-registration algorithm, in this paper a real-time pose correction and registration algorithm of complex workpiece in robotic machining considering normal consistency constrains is proposed. Specifically, the operations on ellipse feature detection and center point extraction are performed based on the arc-support line segment, and then the actual three-dimensional coordinate of the ellipse is obtained by the camera conversion matrix. Furthermore, considering the constrained normal consistency of the center points set of ellipses on the model surface, the pose of the target workpiece is corrected in real-time by the improved ICP registration algorithm. Taking the automotive flywheel shell as a typical application object, the experimental results demonstrate that the registration correction time of the proposed algorithm is 0.5 s, and the registration accuracy can reach 0.35 mm. The repetitive correction time of the algorithm after arbitrarily changing the workpiece pose is less than 1 s, and the positioning accuracy of the guiding robot is less than 1.5 mm. On the premise of satisfying the robotic machining quality requirements, the pose of the complex workpiece model can be corrected in real-time for subsequent robotic machining.

Evaluation of a hybrid cold spray and machining method for fabrication of parts with high surface integrity

Cold spray technology has been proven to have various engineering and manufacturing applications, including the capability to restore previously unrepairable parts. However, like most additively manufactured parts, it will likely require post-processing, such as machining, to improve surface finish and dimensional accuracy. In addition, cold spray deposits are typically porous. The porosity may be detrimental to the mechanical performance of the component. This paper presents a systematic evaluation of cold spray using readily available nitrogen as carrier gas, subsequent machining utilizing negative rake angle tools, and the effect of this novel hybrid fabrication method on subsurface porosity. The machining is optimized via finite element analysis (FEA) and the optimum is verified by experiments. The analysis informs the engineering of the proposed hybrid cold spray/machining method.

Study of arc behavior and machining effects of the novel magnetic field assisted blasting erosion arc machining method

Electrical Arc Machining (EAM) is a high-efficiency, cost-effective method for machining electrical conductive materials especially difficult-to-cut ones. Because this thermal process relies on high-density energy to melt and remove material, effective arc control is crucial to maintain stable machining without overheating the workpiece. However, due to the limited discharge gap, it is difficult for the existing arc breaking methods to manage the arc plasma in a timely and uniform manner. This paper proposes a novel method named Magnetic Field Assisted Blasting Erosion Arc Machining (M-BEAM). This method introduces a magnetic field to enhance the control effect on arc plasma by directly influencing charged particles. Initially, the arc control and material removal mechanisms were revealed through an analysis and experiments of single arc discharge. Both simulated particle trajectory and high-speed photographs demonstrated that the arc plasma deflects much earlier in the magnetic field than that of traditional BEAM. Moreover, the expulsion effect of molten metal was significantly improved, resulting in a larger volume crater. Building on this, the magnetic-assisted arc control mechanism was utilized to enhance the performance of BEAM. Experimental results indicate that compared with traditional BEAM, Magnetic Field assisted BEAM increases its Material Removal Rate (MRR) by 10.09% while significantly reducing the Tool Wear Ratio (TWR) by 29.02%. Additionally, surface roughness (Sa) is decreased by 47.73%, and the thickness of the recast layer is decreased by 78.54%. Therefore, M-BEAM can further improve the machining performance and build a good foundation for subsequent machining.

A supplementary processing method of residual material in impeller plunge milling

Plunge milling is highly suitable for processing deep groove type parts. In recent years, it has been gradually employed in the machining of integral impeller runners. However, when dealing with impeller runners that exhibit a significant blade twist, there tends to be a considerable amount of residual material left after the plunge milling process. The absence of an accurate computational model to depict these residual materials makes it challenging to plan the subsequent machining path, thereby adversely affecting processing efficiency. To address this issue, a geometric model of the material residual ridge is established. By solving the numerical equation governing the boundary characteristic curve of the residual material, a differential discretization method is employed to discretize the boundary feature curves. These curves are then connected to form a unit straight-line surface, thereby constructing an envelope model of the residual material. In order to carry out the supplementary processing of the residual material, a method is proposed based on the geometric parameters of the material residual envelope model. This method automatically divides the machining area of the residual material and plans plunge milling tool path. Simulation results demonstrate that the established residual material envelope model accurately represents the geometry of the residual material, with a volume error of less than 10 %. The supplementary processing tool path generated using the geometric parameters of the material residual material envelope model removes over 80 % of the material residual material volume. Remarkably, the supplementary processing time accounts for only 10 % of the total time required for the whole runner plunge milling process.