Milling Machine Research Articles

Friction stir process parameters optimization in the fabrication of agate particle reinforced AA6061-T6 aluminum alloy surface composite

The main objective of this study was to optimize the friction stir process parameters to fabricate agate particle reinforced AA6061-T6 Aluminum alloy surface composite for hardness and tensile strength. The surface composite samples were made using a CNC milling machine based on Taguchi’s mixed L16 orthogonal array. The process parameters such as tool rotational speed, traverse speed, percent of reinforcement, number of passes and pin profiles were selected in this study. The optimal properties for the developed surface composite were obtained when surface composites having 18% reinforcement were fabricated by a two-pass FSP using a squared pin tool with a rotational speed of 1400 rpm and traverse speed of 60 mm/min. At the optimal process parameters, the tensile strength and hardness of the fabricated surface composite were found to be 312.23 MPa and 74.82 HRB respectively. ANOVA analysis performed at a 95% confidence level revealed that all process parameters were significant and the contribution of the number of passes on the properties of surface composite was higher than other process parameters. Microstructural analysis revealed that medium rotational speed and high traverse speed produced a uniform distribution of agate particles which helped to improve the properties.

An Algorithm for Coding an Additive Manufacturing File from the Pressure Distribution of a Baropodometric Board for 3D Printing Customised Orthopaedic Insoles

Customised orthotic insoles play a critical role in addressing foot pathologies and improving comfort and biomechanical alignment for patients with specific needs. The use of 3D printing technology for the manufacturing of orthotic insoles has received considerable attention in recent years due to its potential for customisation, rapid prototyping, and cost-effectiveness. This paper presents the implementation of an algorithm purposely developed to generate an Additive Manufacturing File (AMF) containing the geometry of a patient-specific insole and the stiffness distribution based on pressure analysis from a baropodometric board. The generated file is used to 3D print via Fused Deposition Modelling an insole with a variable infill percentage depending on the pressure distribution on the patient’s foot. Three inputs are used as source data for the AMF file coding: (i) the 3D model that defines the geometry of the insole designed by the orthopaedist; (ii) the pressure map of the patient’s feet obtained with a baropodometric board; and (iii) the stiffness of the material that will be used to fabricate the insole. The proposed approach allows the fabrication of a patient-specific insole, capable of restoring the correct pressure distribution on the foot by varying the infill percentage. Two types of insoles were successfully fabricated using the implemented algorithm: the first was 3D printed, adding a top layer to be ready-to-use; the second was 3D printed without a top surface to be further customised with different coatings. The method described in this paper is robust for the fabrication of customised insoles and aims at overcoming the limitations of the traditional approach based on milling machining (e.g., time, costs, and path planning) since it can be easily integrated into any orthopaedic workshop.

Effect of Feed Rate on Shear Strength and Macrostructure of Friction Stir Welding Dissimilar High Density Polyethylene-Polypropylene Joint

The connection of dissimilar materials is complicated, too. This connection is due to differences in physical and mechanical properties, but with the development of technology, dissimilar materials can be joined using solid-state welding methods. Dissimilar joints can produce a good combination of structure and mechanical properties. One of them is friction stir welding, which is used to connect sheet materials. The welding process of this research uses a conventional vertical milling machine. This study aims to determine the maximum shear strength and welding defects against variations in the feed rate of lap joints dissimilar high-density polyethylene with polypropylene. The machining parameters used in this experiment were 4 mm pin tool diameter, 2360 rpm rotation speed, 9 mm/min, 12 mm/min, and 16 mm/min feed rate. The results showed that the highest shear strength was obtained using the 12 mm/min feed rate variation of 3.11 N/mm. It can be seen in the macrostructure that the incomplete defects produced are less than the other welding process variations.

EVENT-TRIGGERED CONTROL OF MILLING PHOTOELECTRIC TRACKING SERVO SYSTEMS BASED ON MULTI-INNOVATION INTEREST PARAMETER IDENTIFICATION

Given the coupling of speed and current and the nonlinearity of electronic devices, the photoelectric tracking servo system for milling machines make it difficult to determine the model parameters, and traditional proportional–integral (PI) control hardly meets the high-performance requirements of milling machine optoelectronic tracking servo systems, especially in the development of system networking. In this study, an event-triggered intelligent PI position control strategy based on a multi-innovation identification model was proposed to improve the low control accuracy and dynamic performance caused by the strong coupling and nonlinearity in the optoelectronic tracking servo system of computerized numerical control (CNC) milling machines. A discredite model of the system was established through a multi-innovation identification model, and the PI control parameter was quickly determined using an improved multiverse optimization (IMVO) algorithm. At the same time, an event-triggering mechanism was introduced, thus reducing the number of controller triggers and saving system resources while ensuring the dynamic performance of the system. Finally, experiment results were compared with typical second-order system engineering design PI (SSED-PI) control, pole placement PI (PP-PI) control, and multiverse optimization (MVO)-PI control. Results demonstrate that the proposed multi-innovation stochastic gradient identification model fully utilizes the historical turning angle information of the optoelectronic tracking servo system and has higher accuracy than traditional stochastic gradient identification (parameter accuracy improved by 6.9 times, quantization error reduced by 6.7 times). The proposed event-triggered IMVO-PI (ET-IMVO-PI) has a triggering frequency of 3.5% compared with time-triggered IMVO-PI, with an overshoot of less than 0.5%, which can meet the needs of most engineering practices (less than 5%). Compared with event-triggered SSED-PI, PP-PI, and IMVO-PI, ET-IMVO-PI has higher dynamic performance and fewer triggering times, which can effectively meet the requirements of high-performance network control. The proposed method serves a crucial theoretical guide and important reference for the upgrading and transformation of the photoelectric tracking servo system of CNC milling machines. Keywords: Event-triggered control, Multiple innovative parameter identification, Multiverse optimization PI, Optoelectronic tracking servo system

Numerical modelling and experimental investigation of incremental sheet metal forming of Aluminum Alloy Al 3003-O

Abstract Incremental sheet forming (ISF) is an unconventional sheet metal forming technique that can be widely used in the automotive, medical, and aerospace industries. The final product is achieved by moving a rotating tool along a defined spiral or profile tool path controlled by a CNC milling machine. A truncated cone shape was modeled in single point incremental forming (SPIF) to investigate the influence of step size, and sheet initial thickness parameters on the forming force components Fx , Fy , Fz during the forming process.

Evaluation of Surface Quality and Productivity in Conventional Milling of Copper Beryllium Using Minimum Quantity Lubrication

Copper Beryllium (C17200) has ideal physical and mechanical properties of high fatigue strength, thermal conductivity, and hardness, making the alloy ideal for various high-reliability applications in aerospace, producing inserts and tooling for hazardous environments. However, surface quality and productivity challenges are prominent when processing the alloy due to its properties. This study evaluates the surface quality and productivity in end-milling of Copper Beryllium by analyzing the effects of feed rate, minimum quantity lubrication (MQL) flow rate, and cutting depth on surface roughness (Ra) and material removal rate (MRR). The experiment was designed using the Box-Behnken design, and the samples were machined on a CNC milling machine. The results showed that the MQL flow rate was significant to surface roughness, while the cutting depth was significant to MRR. The optimum parameters were determined as a feed rate of – 60 mm/min, an MQL flow rate of – 80 ml/hr., and a cutting depth of – 0.511 mm, which yielded a surface roughness of 0.12 µm and MRR of 10.19 g/min. The study's novelty is that it considers MQL flow using vegetable oil-based cutting fluid (CF) as an input parameter in machining, offering insight into eco-friendly and cost-effective machining practices. Finally, the significance of the study lies in investigating the machinability of Cu-Be alloy material, addressing challenges related to surface quality and productivity during milling operation.

Wear and corrosion properties of mechanically coated 316 stainless Steel-TiC nanocomposites

The mechanical coating (MC) method was used to deposit 316 stainless steel (SS316), TiC, and SS 316-TiC nanocomposite coatings on SS 316 substrates using a ball mill machine at milling durations of 1, 2, 5, 10, and 15 h using relatively cheap and abundant raw material. The chemical composition of the SS 316, TiC, and SS 316-xTiC (x = 20, 50, 80 wt%) nanocomposite coatings deposited by the mechanical coating method has been investigated and the hardness values and the wear and corrosion mechanisms were presented. Dense and uniform coatings were obtained using a ball-to-powder weight ratio (BPR) of 20:1 and an MC duration of 5 h. Among the samples, the SS316-20 wt%TiC coating exhibited the best wear and corrosion resistance. The least mean coefficient of friction was 0.3 for the SS316-20 wt%TiC deposited sample while the largest mean coefficient was for the SS316-80 % TiC sample to be 0.76. The SS 316-20 wt% TiC sample had the lowest wear rate where the highest value was for the %100SS 316 sample being 0.36 × 10−6 and 19 × 10−6 (mm3/Nm), respectively. Corrosion tests revealed that the SS316-20%TiC sample had the best corrosion resistance among the composite samples having a corrosion resistance of 4.9358 μm/Y. The corrosion resistance decreased with the increase of TiC whereas the 80 % TiC coating had severe pitting. Cracks and pores present in the non-uniform 100 % TiC coating resulted in lower corrosion resistance compared to the 100 % SS 316 and composite coatings.

Evaluation of dry sliding wear characteristics of hybrid a356 composite

As advancements in lightweight and synthetic materials have evolved, our ability to tailor materials to meet societal demands has expanded. Aluminium alloys, known for their high strength-to-weight ratio and cost-effectiveness, are extensively utilized in engineering applications, including structural casting and automotive components. This study employed the stir casting method to investigate the impact of silicon carbide (SiC) and graphite (Gr) on a hybrid A356 composite, aiming to enhance its tribological applicability. SiC and Gr particles were processed using a vibratory ball milling machine for two hours, followed by composite fabrication with varying particle sizes. Microstructural investigation using optical microscopy revealed maximum hardness values of 127 BHN and 125 BHN for A356 composites reinforced with 12.50% SiC, 15.50% Gr, and 11.43% SiC, 15.86% Gr, respectively. Wear rate analysis demonstrated that reinforced A356 composites exhibited higher wear resistance compared to unreinforced alloys. Notably, the sample reinforced with 11.43% SiC and 15.86% Gr displayed exceptional wear resistance. Photo micrographs of A356-SiC-Gr samples at different sliding distances, velocities, and loads revealed minimal plastic deformation during wear testing, resulting in abrasive and cohesive wear. Overall, this study underscores the effectiveness of graphite (Gr) and silicon carbide (SiC) as reinforcement materials for enhancing the tribological properties of A356 composites.

Evaluation of the effect of thermocycling on the trueness and precision of digitally fabricated complete denture bases

BackgroundWhile many denture base materials are currently available on the market, little data exists regarding their dimensional stability after exposure to the oral environment. This study aimed to evaluate the effect of thermocycling on the trueness and precision of milled, 3-dimensional (3D)-printed, and conventional digitally fabricated complete denture bases (CDBs).MethodsA completely edentulous maxillary stone model was scanned to generate a standard tessellation language (STL) file; this was imported into metal-milling-machine software (Redon Hybrid CAD-CAM metal milling machine, Redon, Turkey) to produce a metal model for fabricating 30 CDBs. These were divided into three groups (n = 10 in each) according to the construction technique: group 1, CAD-CAM milled CDBs; group 2, 3D-printed CDBs; and group 3, conventional compression molded CDBs. All CDBs were scanned after fabrication and evaluated before and after thermocycling using superimposition. The data were analyzed using a one-way ANOVA, Tukey’s post hoc test, and a paired t-test.ResultsThe level of trueness between the CAD-CAM milled, 3D-printed, and compression molded CDBs showed significant differences before and after thermocycling (P < 0.05). Group 1 showed the highest degree of trueness before and after thermocycling, group 3 exhibited a higher degree of trueness than group 2 before thermocycling, and group 2 had a higher degree of trueness than group 3 after thermocycling. There was a significant difference in the precision for each CDB type before and after thermocycling (P < 0.05).ConclusionThe trueness of the CAD-CAM milling system in complete denture (CD) fabrication is superior to that of the 3D printing and conventional compression molding systems before and after thermocycling. Thermocycling had a significant effect on the precision of all CDB types. The compression molding system in CD construction is the most negatively affected via thermocycling with regard to the measures of trueness and precision.Clinical trial numberNot applicable, no human participants were involved.

Development of Electric Control Panel to Control a CNC Thread Milling Machine

Development of Electric Control Panel to Control a CNC Thread Milling Machine

Analysis Of Cutting Parameters Affecting The Surface Roughness Value Of Amutite Steel With A 50 Mm Diameter Facemill On The Fu100 Lagoon Milling Machine Using Statistical Methods

The Lagun FU100 Milling Machine (LFR 26) is a type of milling machine located at the Bandung Manufacturing Polytechnic. There is a surprising opinion that the Lagun Milling machine is rarely used, both for student academic activities and production purposes. Generally milling machines can achieve a surface roughness of 0.32-25 µm. Appendix 3 shows the results of the surface roughness of the grinding results. So this research was carried out to prove that this machine can reach surface roughness standards, and also to state that this machine is still suitable for use for production activities or student academic activities and to prove that this machine can still produce products of good quality. In this study, the three parameters evaluated were cutting speed, feed rate, and depth of cut. Through experiments and statistical analysis, it was found that RPM at a medium level produced the lowest roughness value of 0.340, while cutting depth at a high level produced the smoothest surface roughness with a value of 0.330. Feed rate at the medium level also shows the lowest surface roughness results with an average of 0.330. The research results show that the smoothest surface that can be produced is 0.2883, this value is at level N4. In addition, the Lagun FU100 milling machine was declared suitable for use in achieving the desired roughness value, demonstrating the ability of this machine to produce surfaces with the expected quality standards.

Thermo-mechanical characterization of pinless friction stir welding in AA6060-T4 thin sheets

Friction Stir Welding (FSW) is a solid-state welding method, offering superior weld quality for aluminum alloys. Despite its advantages, the thermo-mechanical characteristics of pinless FSW, especially for AA6060-T4 aluminum thin sheets, remain underexplored. This study aims to fill this gap by examining the effects of different welding parameters on the mechanical properties and thermal distribution in pinless FSW of 2 mm AA6060-T4 sheets. Experimental welding tests were conducted using high alloy steel tools and a modified milling machine, with variations in rotation and feed rates. The results show that higher rotation speeds correlate with lower maximum temperatures, and increased feed rates further reduce temperatures. Optimal welding parameters achieved efficiency coefficients as high as 84%. Microhardness profiles indicated minimum hardness in the Thermo-Mechanically Affected Zone (TMAZ) and a significant increase on the advancing side. These findings enhance the understanding of pinless FSW, emphasizing the interaction between welding parameters and mechanical properties. This research advances the application of AA6060-T4 in various industrial sectors by providing valuable insights into optimizing weld quality and mechanical performance.

Frequency Shift in Microwave Circuits Manufactured with Circuit Board Plotters: Case Study of a Parallel Coupled Lines Filter

Board milling is one of the most widespread methods for manufacturing printed circuit boards from low frequencies to the microwave and millimeter wave range. In this contribution, the detrimental effect of defects typical of printed circuit board plotters has been investigated. In detail, a systematic frequency shift in the circuit performance has been observed both in terms of S21 and S11 parameters. The performance degradation has been analyzed and attributed to the inaccurate milling depth, which is typical of many plotters, particularly for less recent models. After the conductor removal step, the unwanted milling of dielectric material changes the electrical properties of the microstrip structure, in turn affecting the circuit performance. This circumstance has been investigated by means of electromagnetic simulations performed on the real case study of a parallel coupled lines filter. Therefore, a filter prototype has been realized and measured to confirm the simulated results. This study can be beneficial to those professionals involved in the design and realization of microwave and millimeter waves circuits with board milling machines.

Analysis of machinability in milling of high-strength brittle thin plates of γ-TiAlNb intermetallic compound

Analysis of machinability in milling of high-strength brittle thin plates of γ-TiAlNb intermetallic compound

Entropy‐based sampling for efficient training of deep learning on CNC machining dataset

AbstractIn the domain of modern manufacturing, computer numerical control (CNC) milling machines have emerged as instrumental assets. However, the data they generate is of vast amount, but usually contains redundancies and displays consistent patterns, making it inefficient for deep learning training. This paper proposes a novel sampling algorithm tailored for CNC milling machine data, emphasizing both diversity and efficiency. The proposed method leverages the entropy concept from the information‐theoretic perspective to evaluate and enhance data diversity, aiming to achieve efficient learning with high accuracy. This in turn enables to not only facilitates a deeper understanding of CNC data characteristics but also contributes significantly to the optimization of deep learning training processes in the context of CNC milling data.

Pulling Out All The Stops

KERAjet has boosted its productivity and increased processing capacity and capabilities with a new large-capacity, gantry-type milling machine

Achieving new excellence in an augmented reality dental education system

Background/purposeSimEx-Plus (EPED. Inc) was already a mature augmented reality (AR) dental training simulator that allowed students to have a high quality dental education practice. Now the EPCAD software has been further developed into a comprehensive computer-aided design software. It helps relevant professionals learn how to create digital fixed prosthesis in a virtual environment. This study used the newly developed EPCAD software that was integrated within the SimEx-Plus to design dental restorations then digital output milling restorations. We hope that the SimEx-Plus AR dental training simulator can achieve the multi-purpose function in one machine. Materials and methodsA right maxillary central incisor was prepared in the standard dental model. The restorations were designed by EPCAD software integrated with the SimEx-Plus and milled by a 4-axis dental milling machine (N4+, vhf camfacture AG). The internal gap of the restoration was evaluated. ResultsThe internal gaps of the crowns set on the right maxillary central incisor were among 68.27–89.80 μm. The different setting for digital output did not influence the internal gap (P 0.05, One-Way ANOVA). However, the internal gap on the palatal side was larger than that on the labial, mesial, distal, and incisal surfaces (P < 0.05, One-Way ANOVA). ConclusionThe new software EPCAD that was integrated within the SimEx-Plus AR dental training simulator could design restorations, and the designed restorations had good internal gap for clinical use. The professionals can learn tooth preparation and digital restoration fabrication by the SimEx-Plus AR dental training system.

Synthesis and Characterization of Red Pigment from Acid Regeneration Plant (ARP) By-product Via Rod Milling Process

Iron o xide waste from acid regeneration plants (ARP) is often discarded due to its non-profitability. This research aims to introduce a value-added process to convert iron oxide waste into red pigment via rod milling process. The iron oxide waste collected from ARP was grinded with a rod milling machine at 30 rpm for 24 hours. The ground product was then mixed with industrial-grade red pigment in various ratios. The mixed samples were then rod-milled again into ultra-fine particles. A total of seven samples were prepared, applied onto a canvas and analysed by energy dispersive X-ray spectroscopy (EDX) and X-ray diffraction (XRD) methods. From the analyses, the existence, composition, and orientation of iron oxide were established. The waste-derived red pigments were subsequently subjected to particle size analysis on a scanning electron microscopy (SEM) platform, with results showcasing the efficiency of the rod milling process. Colour-related properties of the samples before and after canvas application were investigated using the L*a*b* system with a chromameter. Empirical outcomes indicated that the a* value plays an important role in determining the redness of the sample. Overall, the a* values obtained were above 15 and gradually increased in accordance to the amount of industrial-grade red pigment added. The oil absorptivity of red pigments was also tested via an oil absorptivity test. Notably, the assay signified that particle size and porosity affect the amount of oil that can be absorbed by the pigment.

Gluing of thermally modified silver fir wood planed by horizontal milling machine

This study was conducted to provide information regarding the quality of gluing of Silver fir wood (Abies alba Mill.) planed at different feed speeds after thermal modification. Four groups of sixteen air-dried fir samples were prepared. Three groups were thermally modified at different temperatures (160°C, 190°C, and 220°C) for 3 hours. The processes that followed included planning with two feed speeds (half of the samples at 3m/min and the other half at 10 m/min), the gluing, and finally, conducting mechanical tests to assess shear strength and wood failure. The gluing shear strength underwent a progressive decrease with increasing modification temperature for both feed speeds, with reductions ranging from 1.37% to 14.63% compared to natural wood. Wood failure did not show a linear relationship, with a decrease at 160°C but an increase at higher temperatures compared to natural wood. The feed speed had a significant effect on gluing shear strength, with higher feed speed resulting in decreased strength for natural wood but increased strength for thermally modified wood. Thermal modification of fir wood at temperatures of 220°C had a detrimental effect on the gluing shear strength and wood failure. This was caused by the deterioration of wood components and alterations in mechanical properties. The results of this study offer significant knowledge for improving the gluing process and establishing appropriate parameters for thermally modified fir wood. This type of wood has potential uses in the wood sector, specifically in the manufacturing of engineered wood products

Enhancing mechanical performance of polypropylene bio-based composites using chemically treated date palm filler

Utilizing agro-residues as organic fillers instead of wood is considered a sustainable option for preserving forestry. Recently, we successfully developed a new chemical treatment method to extract rich cellulosic microfibers from agro-residues of date palm trees. The treated fibers exhibited an improved performance, thus demonstrating the prominent potency of the new method. For further confirmation, in this study, we have applied the technique to treat raw microfibers and examine their performance as reinforcing elements in both virgin polypropylene (PP) and recycled post-consumer polypropylene (rPP). The chemically treated fibers were initially pulverized to a powder form using a ball milling machine and then blended with PP or rPP to make bio-composites. Specimens were fabricated at melt state using a single-screw extruder followed by compression molding. Then, a series of mechanical and physical tests were conducted on the specimens following ASTM standards. Results revealed that incorporating treated fillers into either PP or rPP has enhanced the mechanical properties of the bio-composite compared to the ones with untreated filler. Owing to the treatment, the rise in tensile strength of recycled polymer-based bio-composites was higher than that of virgin polymer-based bio-composites where treated fillers acted effectively as a nucleation agent to rPP. Additionally, a pronounced drop in water absorption and boost in crystallinity of both bio-composites were attained. However, thermal degradation was not dramatically altered. Therefore, this study showed that reinforcing rPP with treated date palm filler to make bio-composites is a reliable route for designing products across a wide range of industries.