Accuracy investigation of Fused Deposition Modelling (FDM) processed ABS and ULTRAT parts.

This paper aims to assess the dimensional deviation of Fused Deposition Modeling (FDM) processed ABS and ULTRAT parts using a new geometrical model which can evaluate three types of dimensional deviation: along the z-axis, along external and internal dimensions, and through diameters. The methodology involves a step-by-step procedure wherein after establishing the experimental plan and manufacturing the specimens, the measurements taken are analyzed via Grey Relational Analysis (GRA) to find out the optimal combination of parameters leading to the minimum deviation in all dimensions of parts for both materials. Statistical techniques such as Analysis of Variance (ANOVA) and Signal to Noise (S/N) ratio were also used. Subsequently, a confirmation test was carried out to validate the results obtained. The findings of the ANOVA and the S/N ratio were in good concordance with those of GRA.

Enhanced Micro-Electric Discharge Machining-Induced Surface Modification on Biomedical Ti-6Al-4V alloy

In the midst of a huge demand for high-precision miniaturized medical implants made up of potential biomaterials, the biomedical Ti-6Al-4V alloy meets the uncompromising standards for longevity, biocompatibility, and sterilizability required to interact with living cells in medical settings. This research tailored the existing capabilities of a traditional micro-electric discharge machining (μ-EDM) setup by adding 0, 2, 4, 6, 8, and 10 g/l bioactive zinc powder-particle-concentrations (PPCs) to the dielectric. A copper and brass micro-tool electrode (C-μ-TE and B-μ-TE) were employed in association with each PPC, and experiments were executed using one-variable-at-a-time (OVAT) approach. Machining time and dimensional deviation were chosen as the response variables of Zn powder mixed-micro-EDM (Zn-PM-μ-EDM). According to the analytical findings, the combination of C-μ-TE and 6 g/l Zn PPC achieved 23.52 %, 3.29 %, and 17.96 % lesser machining time, dimensional deviation, and recast layer thickness, respectively, compared to the B-μ-TE. The detailed study of this surface endorsed a significant modification in terms of improved recast layer thickness (26.44 μm), topography (Ra = 743.65 nm), and wettability (contact angle < 90°), suggesting its dental application. Additionally, the observation of ZnO and TiO in X-ray diffraction and appealing in vitro cytocompatibility encourage the subsequent biological and therapeutic studies to validate the anticipated anti-viral activity of the modified Ti-6Al-4V alloy surface against coronavirus (COVID-19).

A Predictive Model of Dimensional Deviation Based on Regeneration PSO-SVR with Cutting Feature Weight in Milling

Support vector regression (SVR) optimized by particle swarm optimization (PSO) has low predictive accuracy and premature convergence in milling. To solve this problem, A PSO-SVR model combined with the cutting feature weight was proposed in this paper. Firstly, basing on the SVR, the feature weight was integrated with the kernel function, and added the premature judging to the PSO to improve the global searching ability. Secondly, the mathematical model composed of the cutting force, temperature and cutting vibration was built based on the datasets obtained by experiment. The covariance was calculated to get the characteristic weights of process parameters, which promoted the incremental data in turn. Finally, the predictive model of the dimensional deviation was established based on the promoted PSO-SVR and the result was compared with the general PSO-SVR. The accuracy of the predictive model reached 97.5%. And compared with the predictive model of the general PSO-SVR without feature weighting, the dimensional deviation predictive accuracy and generalization ability of the regeneration PSO-SVR predictive model with feature weighting was improved by 37.75% and 24.5%.

Classification of Dimensional Deviation in Additive Manufacturing LPBF Process for AlSi10Mg Alloy According to ISO 286 and ANSI B4.2

Additive manufacturing (AM) processes are gaining popularity and are currently used in many research activities including the biomedical applications, the automotive industries and the aerospace. Laser powder bed fusion (LPBF) is an important AM process. Metallic LPBF process is experiencing significant growth, but one of the difficulties facing this growth is limited knowledge of its dimensional and geometrical performances, in addition to the inability to predict it. In this paper, we present the dimensional deviations of some LPBF-manufactured parts selected for this investigation. a uniform method was developed regarding relevant test specimens to examine dimensional deviations in order to derive dimensional tolerance values. The manufactured test specimens were measured to examine the process dimensional deviations behavior. These parts were manufactured from AlSi10Mg powder using an EOSINT M280 printer. The results show possible dimensional tolerance values that were classified from IT1 to IT11 according to the international standard ISO 286.

A Practical Numerical Approach to Characterizing Non-Linear Shrinkage and Optimizing Dimensional Deviation of Injection-Molded Small Module Plastic Gears

This paper was aimed at finding out the solution to the problem of insufficient dimensional accuracy caused by non-linear shrinkage deformation during injection molding of small module plastic gears. A practical numerical approach was proposed to characterize the non-linear shrinkage and optimize the dimensional deviation of the small module plastic gears. Specifically, Moldflow analysis was applied to visually simulate the shrinkage process of small module plastic gears during injection molding. A 3D shrinkage gear model was obtained and exported to compare with the designed gear model. After analyzing the non-linear shrinkage characteristics, the dimensional deviation of the addendum circle diameter and root circle diameter was investigated by orthogonal experiments. In the end, a high-speed cooling concept for the mold plate and the gear cavity was proposed to optimize the dimensional deviation. It was confirmed that the cooling rate is the most influential factor on the non-linear shrinkage of the injection-molded small module plastic gears. The dimensional deviation of the addendum circle diameter and the root circle diameter can be reduced by 22.79% and 22.99% with the proposed high-speed cooling concept, respectively.

Titanium Ti-6Al-4V Alloy Milling by Applying Industrial Robots

Robotic machining is an alternative to manufacturing processes that combines the technologies of a high-performance machine tool with the flexibility of a 6-axis jointed arm robot. With their large working area, industrial robots are of particular interest for processing large-volume components and large structures, like aircraft components. An influencing variable, which is particularly relevant for milling processes with industrial robots are the cutting force F and the resulting dimensional deviation D. Milling tests of titanium alloys were carried out with an industrial robot and the results compared with a conventional machine tool. Due to the low thermal conductivity and high chemical reactivity of the Ti-6Al-4V alloy, heat is generated and increases the temperature in the contact region of the cutting tool/work piece. That has an impact on the cutting tool wear and increases the cutting force F, and consequently, the dimensional deviation D and the machined surface quality. The aim of the investigations is to find a suitable parameter selection and machining strategy for machining titanium alloys with minimal deviation D and an appropriate surface finish.

Melting Cell Based Compensated Design Method for Improving Dimensional Accuracy of Additively Manufactured Thin Channels

Powder-bed fusion additive manufacturing technology makes it possible to produce parts with complicated geometry and high accuracy. However, dimensional deviation caused by powder overmelting and dross formation is still a challenge for manufacturing thin channels. In this study, the origins of the overmelting of printed thin channels were analyzed and a concept called “melting cell” is proposed to describe and quantify the geometric error. Based on the geometrical relationship between the melting cell and target channel, a method for predicting and optimizing the final geometry of thin channels is outlined. In order to verify the method, geometries of thin horizontal circular channels in various sizes are studied as examples. The predicted results by the proposed method show a remarkable agreement with available experimental results. Moreover, a new egg-shaped compensated design, which is able to improve the dimensional accuracy of thin horizontal circular channels, is presented. The proposed method is simple yet very effective. It can be easily extended to the manufacturing of thin channels with various shapes, materials, and different powder bed fusion processes.

Effect of Minimum Quantity Lubrication System for Improving Surface Roughness in Turning Operation

Due to increase in temperature at the cutting zone, the tool wear and surface roughness along with the non-uniform chip formation and the dimensional deviation of the job by using the conventional cutting fluid, the machining operation experts have directed their concentrations in order to achieve a smooth machining operation by using minimum quantity lubrication (MQL). As a consequence, numerous efforts can be seen for not only having the optimum cutting parameters but also other parameters that enhance the product quality and the surface roughness. In this regard, relevant experimental and numerical data outcomes not only MQL but also conventional cutting fluid (CCF) in the turning operation of 50HRC steel has been investigated experimentally. It is revealed that the surface roughness becomes optimal and significantly reduced for the condition of MQL with that of dry and conventional flood lubrication.