Manufacturing Process Research Articles

Laser additive manufacturing of Ti and Ce co-modified 2195 difficult-to-process aluminum alloy: Grain refinement, cracking suppression and enhanced mechanical properties

High cracking susceptibility of Al-Li alloys with Ti/CeB6 addition is thoroughly suppressed in laser powder bed fusion (LPBF) processing of Ti/Ce co-modified 2195 alloys at relatively high scan speeds, while the cracking suppression mechanism and phase formation in these composites are not clarified. In this work, microstructure evolution and mechanical performance of the LPBF-fabricated Ti/Ce co-modified 2195 are investigated to reveal their cracking suppression and strengthening mechanisms. The results show that apparent grain refinement of the composites is ascribed to high supercooling from rapid formation of constitutional supercooling zone in front of solid-liquid interfaces by high-Q-value Ti solute, and heterogeneous nucleation of in situ formed Al3Ti and Al11Ce3 precipitates. Their synergistic interactions promote formation of fine equiaxed grains and thus inhibit crack initiation. The composites exhibit high microhardness of 100±5 HV0.2, nano-hardness of 1.6±0.1 GPa and elastic modulus of 97±3 GPa, where the elastic modulus increases by ∼27% and ∼31% compared to those of LPBF-processed and conventionally manufactured 2195 alloys, respectively. A tensile strength of ∼336 MPa and an elongation of ∼3% are obtained from in-situ synchrotron X-ray diffraction measurement. The improved properties are derived from grain refinement and Orowan strengthening. Based on the optimal processing parameter and composition, a bracket component filled with lattice structures is designed and manufactured with good manufacturing quality and processing accuracy.

Extension of paperboard modelling with Föppl–von Karman terms for improved stress state under suction pressure

A practical method for solving the bending stiffness of a thin orthotropic plate based on measured deflection and known loading was studied. The target application was paperboard manufacturing and related process control. Here, finite element (FE) method was used to create virtual paperboard and its deflection data. The accuracy of the linear Kirchhoff plate model used in the practical method was tested against the FE model with known load and material properties. It was found that in the case of significant deflections, the linear Kirchoff model was not accurate. The non-linear Föppl--von Kàrmàn model takes into account the occurring membrane stresses and extends on the Kirchhoff model, allowing for larger deflection. The non-linear Föppl--von Kàrmàn model was found to successfully describe the simulated situation and could be used to better solve for the paperboard's bending stiffness values over two axes.

Safety evaluation of the food enzyme endo-1,3(4)-β-glucanase from the non-genetically modified Talaromyces versatilis strain PF8.

The food enzyme endo-1,3(4)-β-glucanase (3-(1-3;1-4)-β-d-glucan 3(4)-glucanohydrolase; EC 3.2.1.6) is produced with the non-genetically modified Talaromyces versatilis strain PF8 by Erbslöh Geisenheim AG. The food enzyme was free from viable cells of the production organism. It is intended to be used in four food manufacturing processes. Dietary exposure to the food enzyme-total organic solids (TOS) was calculated to be up to 0.110 mg TOS/kg body weight (bw) per day in European populations. Genotoxicity tests did not indicate a safety concern. The systemic toxicity was assessed by means of a repeated dose 90-day oral toxicity study in rats. The Panel identified a no observed adverse effect level of 2229 mg TOS/kg bw per day, the highest dose tested, which when compared with the estimated dietary exposure resulted in a margin of exposure of at least 20,264. A search for homology of the amino acid sequence of the food enzyme to known allergens was made and four matches with respiratory or contact allergens were found. The Panel considered that the risk of allergic reactions upon dietary exposure cannot be excluded, but the likelihood is low. Based on the data provided, the Panel concluded that this food enzyme does not give rise to safety concerns, under the intended conditions of use.

Addressing Model Uncertainties in Finite Element Simulation of Electrically Stimulated Implants for Critical-Size Mandibular Defects.

Electrical stimulation is known to enhance bone healing. Novel electrostimulating devices are currently being developed for the treatment of critical-size bone defects in the mandible. Previous numerical models of these devices did not account for possible uncertainties in the input data. We present the numerical model of an electrically stimulated minipig mandible, including optimization and uncertainty quantification (UQ) methods that allow us to determine the most influential parameters. Uncertainties in the optimized finite element model are quantified using the polynomial chaos method that is implemented in the open-source Python toolbox Uncertainpy. The volumes of understimulated, beneficially stimulated, and overstimulated tissue are considered quantities of interest because they may significantly impact the expected healing success. Further, the current is a substantial quantity, limiting the lifetime of a battery-driven stimulation unit. With sensitivity analyses, the most critical parameters in the numerical model can be identified. Thus, we can learn which parameters are particularly relevant, for example, when conceptualizing the stimulation unit or planning the manufacturing process. The results of this study show that the parameters of the electrode-tissue interface (ETI), as well as the conductivity within the defect volume, have the most significant impact on the model results. The UQ results suggest that careful characterization of the ETI and the dielectric tissue properties is crucial to reduce these uncertainties. The numerical model regarding uncertainties yields important implications for reliable implant design and clinical translation.

Microhole Creation in FDM-Printed Sheet Polymers: A Punching Process Approach

Fused deposition modeling (FDM) 3D printing is one of the additive manufacturing processes that can make components with complex shapes, require no tools, are cheap, safe, and have minimal waste. Despite all the advantages of the FDM process, the inability of this technique to create holes on a micro scale can be a problem and limits its application. In this research, a combination of FDM and machining processes was carried out, where micro holes in FDM printed components were created using a punching process. The punching process is carried out by varying pressure and speed. Furthermore, the diameter of the hole and the quality of the sheared edge of the hole resulting from the punching process were evaluated through observation using an optical microscope. The results show that the holes resulting from the punching process have a better shape and diameter than the FDM process. Then, the analysis of the sheared edge from punching shows that pressure and speed significantly affect the surface quality of the resulting sheared edge, where the quality increases with increasing pressure and speed. In the end, the punching process was proven to create micro-scale holes in FDM-printed polymer, especially at minimum thickness.

Influence of bottom supporting columns and cooling rate on the surface shape characteristics of sapphire substrates

The manufacturing process of sapphire substrates involves several key steps, including epitaxy, annealing, cutting, and processing. Among these, epitaxy and annealing are particularly crucial. The temperature variances along both the longitudinal and transverse axes within the furnace during the crystallization process play a significant role in determining the crystallization rate and internal structure of sapphire crystals. Furthermore, annealing sapphire serves to alleviate internal stress, enhance crystal structure, optimize physical properties, improve optoelectronic characteristics, enhance surface quality, and increase overall yield. This step is paramount in enhancing the performance and application value of sapphire materials. In order to investigate and optimize the effects of different thermal conductivities of support columns at the base and various annealing procedures on the surface characteristics of sapphire substrates, thereby improving product quality, this study conducted research by utilizing support columns made of different materials and carefully controlling the cooling rate parameters for sapphire. The findings revealed that using graphite as the base support column for the crystal furnace can reduce both the longitudinal and transverse temperature gradients within the furnace, consequently promoting crystal growth and enhancing the quality of sapphire ingots. Additionally, sapphire chips annealed using the rapid one-step annealing program exhibited the highest average warpage and bending rate variation, reaching 2.0 μm, and the average dislocation density was half that of conventionally produced chips, at 108.89 pits/cm2.

Extending cutting tool remaining life through deep learning and laser shock peening remanufacturing techniques

Predicting and extending the remaining life of cutting tools during machining processes is crucial for sustainable manufacturing. Traditional prognosis methods often struggle to adapt to diverse working conditions throughout the machining process lifecycle. This paper introduced a comprehensive framework that effectively addressed the challenges by integrating multi-source data and using deep learning techniques. The system integrated power and vibration data collected from LGMazak VTC-16A and IRON MAN QM200 machines with the following innovations: (1) A standardized data fusion method was developed to integrate multi-source data sources, the hybrid graph convolutional network (GCN) with attention mechanisms was employed to improve the prognosis accuracy of cutting tool remaining life, best accuracy of 98.56% and average accuracy of 97.71% were achieved. (2) The optimization of laser shock peening (LSP) remanufacturing parameters using the bees algorithm showed good performance, a fitness value of 0.95 was achieved with convergence within 15 iterations. (3) Monitoring of the LSP remanufacturing process was designed based on sound and vibration data for optimal remanufacturing performance. (4) The remanufacturing approach in extending the remaining life of cutting tool was validated through FEA analysis and experimental testing, cutting tool life was extended by 29.32% to achieve a sustainable manufacturing process.

Extrusion‐based additive manufacturing of alumina ceramics through controlled extrusion pressure

AbstractThe development of dense alumina ceramics through additive manufacturing necessitates the careful analysis of various parameters. The extrusion pressure during printing is a crucial but often overlooked factor in the literature. This study investigates the impact of extrusion pressure on the densification and mechanical properties of alumina ceramics. The primary objective is to analyze extrusion pressure to achieve superior physical and mechanical characteristics while maintaining minimal shrinkage. All other printing parameters were kept constant, and the extrusion pressure was varied from 1 to 2.85 bar during the extrusion‐based additive manufacturing of alumina green bodies. The printed and sintered samples were analyzed for linear shrinkage, density, compressive strength, and microhardness. The results indicate that an extrusion pressure in the 2.2–2.5 bar range leads to alumina ceramics with the best combination of densification and other mechanical properties. Additionally, the interparticle bonding mechanisms contributing to the improved properties of the alumina ceramics were examined. This study provides valuable insights into the role of extrusion pressure in the additive manufacturing process, underscoring its significance in achieving high‐quality alumina ceramics.

Laser powder bed fusion in-situ alloying of W-Y alloy: microstructure, mechanical properties and cracking suppression

The microcracks caused by impurity oxygen are recognized as one of the main challenges in additive manufacturing of tungsten. In this study, yttrium was incorporated into the tungsten matrix to suppress crack formation, and W-Y alloys with minimal cracks were successfully obtained by laser powder bed fusion (LPBF). It is found that during the LPBF process, yttrium combines with impurity oxygen to generate intergranular and intragranular precipitated particles in situ, which effectively suppress cracking behavior due to impurity oxygen. Furthermore, these intracrystalline nanoprecipitate are cubic Y2O3 particles that have formed a semi-coherent interface with the tungsten matrix. These dispersed particles significantly improved the mechanical properties of W-Y alloy. The results offer a corresponding strategy for crack suppression of tungsten alloys in laser additive manufacturing processes, and would provide a benificial additive manufacturing strategy to other refractory alloys.

Successful generation of fully human, second generation, anti-CD19 CAR T cells for clinical use in patients with diverse autoimmune disorders

BackgroundB-cell targeting chimeric antigen receptor (CAR) T-cell therapies, which lead to profound B-cell depletion, have been well-established in hematology-oncology. This deep B-cell depletion mechanism has prompted the exploration of their use in B-cell driven autoimmune diseases. We herein report on the manufacturing of KYV-101, a fully human anti-CD19 CAR T-cell therapy, derived from patients who were treated across a spectrum of autoimmune diseases. MethodsKYV-101 was manufactured from peripheral blood-derived mononuclear cells of 20 patients across 7 autoimmune disease types (neurological autoimmune diseases, n=13; rheumatological diseases, n=7). Patients ranged from 18–75 years of age. Duration of disease ranged from <1–23 years since diagnosis. Patients were heavily pretreated, and most were refractory to prior immunosuppressive treatments. Apheresis was collected across 9 sites, cryopreserved, and shipped to the manufacturing facility. Healthy donor apheresis samples were collected for manufacturing comparison. Manufacturing was performed using the CliniMACS Prodigy system. Cells were enriched for CD4+/CD8+ T cells, transduced with a 3rd generation lentiviral vector encoding the CAR, expanded in vitro, and harvested. Percent cell viability, T-cell purity, cellular expansion, and transduction efficiency were assessed. Activity was assessed using cytokine release assays for KYV-101 CAR T cells co-cultured with different CD19+/– target cell lines. ResultsKYV-101 was successfully manufactured for 100% of patients. Transduced cell populations were highly viable, with expansion ranging from 11–66 fold at Day 8, and were comparable across disease types. Healthy donor-derived controls displayed similar expansion ranges. High CAR expression and transduction rates were observed, ranging between 37–84% with low variation in transgene copy number (2 to 4 per cell). Cell viability of the final KYV-101 drug product ranged from 87–97%. KYV-101 displayed robust CD19-dependent and effector dose-related release of the pro-inflammatory cytokine IFN-γ. ConclusionsKYV-101 manufacturing yielded a CAR T-cell product with high viability and consistent composition and functionality, regardless of disease indication, pre-treatment, and heterogeneity of the incoming material. Cryopreservation of the apheresis and final drug product enabled widespread distribution. These results support the robustness of the manufacturing process for the fully human KYV-101 anti-CD19 CAR T-cell therapy drug product for patients across diverse autoimmune disease types.

Simultaneous carbon fiber layer thickness and direction measurement and identification using a novel eddy current sensor and simplified multi-scale 1D-ResNet network

A novel eddy current sensor, featuring a triangular excitation coil and three rectangular receiving coils, is proposed for simultaneously detecting carbon fiber layer thickness and directions in the manufacturing process of carbon fiber reinforced polymer (CFRP) materials. It can disclose various carbon fiber layers and directions based on the signals obtained from the three receiving coils. However, classification of carbon fiber layers and directions proves challenging due to the complexity of signal features resulting from different combinations of carbon fiber layers and directions. To address this issue, we propose the use of a simplified multi-scale 1D-ResNet network. Comparative analysis reveals that our proposed network achieves higher train and validation accuracy compared to single-scale 1D-ResNet networks and different layers 1D-ResNet networks. Furthermore, the proposed simplified network not only achieves high classification accuracy with 100% and 99.7% for carbon fiber layers and directions, respectively, but also requires less training time compared to multi-scale 1D-ResNet networks. The novel eddy current sensor proposed in this study enables accurate recognition of carbon fiber layers and their directional orientation through the implementation of a simplified multi-scale 1D-ResNet network in the manufacturing process of CFRP materials. This innovation significantly enhances the quality of CFRP materials during manufacturing, ensuring their strength aligns with predetermined orientations.

Body heat energy driven knitted thermoelectric garments with personal cooling

Wearable, thermoelectric (TE) devices have gained significant interest in recent years as they can both generate output power from converting body heat into electrical energy and be utilized in personal cooling through the Peltier effect. Currently, researched wearable TE cooling devices focus on devices that can be attached to the human body in specific locations and use heat sinks or elongated thermoelectric pillars to increase their effectiveness, making them hard and bulky. In addition, these devices are attached, not integrated, to wearable garments, making their manufacturing a multi-step process. To address this issue, we developed a knitted TE garment through a single-step manufacturing process that offers energy generation and personal cooling capabilities. The functioning of the cooling device was mathematically modelled and analyzed to understand its scalability, optimization, and to show its potential. This garment features excellent thermoelectric generation of 7.48 mV and 0.46 mA on the human body, and the ability to cool the human body up to 1.5 °C. The observations proved that the mathematical model could predict the behavior of the TE device closely. The results showed that the proposed method of knitted TE cooling garment manufacturing is a viable and scalable process.

PROSES PEMBUATAN THUMB SCREW DENGAN MENGGUNAKAN MESIN CNC BUBUT SERTA PEMBUATAN ULIR SECARA KONVENSIONAL DI PT. AMANAH JAYA PERSADA

Thumb Screws are multi-purpose fasteners designed to be tightened and loosened by hand. They are primarily used to secure cable panel covers, safety covers, battery compartments, and other parts or components that may need to be removed and reinstalled frequently. The screw system is known and has been used by humans for several centuries. The aim of creating this screw system is basically to find an easy way to combine or connect two components so that this combination becomes a single unit that is useful in accordance with its function. The Thumb Screw manufacturing process uses a CNC lathe and conventional tapping. A CNC lathe is used to make the Thumb Screw using Alumunion copper alloy series 2000 material in the form of a long pipe with a length of 26.50 mm and a diameter of 15.20 mm and a tap is used to make the thread hole. Then measure the material dimensions again as the final finishing stage

Metode Pelaksanaan Pembuatan PC Spun Pile dengan Mutu F'c 52 MPa Pada PT. Wijaya Karya Beton Tbk PPB Majalengka

A concrete plant, also known as a batch plant or batching plant or a concrete batching plant, is equipment that combines various ingredients to form concrete. This implementation aims to determine the manufacturing process and quality control of concrete product production. The method used in this implementation is descriptive quantitative. Steps include operational variables to determine the problem and indicators of the cause of the problem. Data collection through observation and documentation. The results of this implementation show that the implementation of manufacturing at PT WIKA Beton Tbk PPB Majalengka aims to make good concrete products, the factors for making PC Spun Pile products are made based on work instructions or standard operational procedures.

A hybrid continuum-beam optimisation model: the virtual extensometer method for efficient optimisation of lattice materials

AbstractAdditive manufacturing (AM) enables the fabrication of complex lattice structures that are infeasible with traditional manufacturing processes. These structures are typically implemented with constant cross-sectional strut elements; this strategy is expedient but leads to sub-optimal structural efficiency. Numerical continuum models allow robust mechanical modelling of complex lattice geometry but provide equally complex data fields that are ill-suited for traditional optimisation techniques. By contrast, numerical beam models represent the fundamental tensile and bending stress states but are incapable of capturing nuanced geometrical effects that lead to local stress concentrations. In this research, a hybrid continuum-beam method is proposed for the systematic optimisation of strut cross section: a representative unit cell is simulated by continuum elements, and the local strut stress tensor is acquired by embedded beam elements that act as virtual extensometers. By integrating a computationally inexpensive beam model into a more robust continuum model, the volume and the quality of data returned are significantly increased whilst being provided in a readily usable format for optimisation techniques, for a trivial increase in computational cost. The presented method is generalised and can be applied to any strut-based lattice structure. Body-centred cubic (BCC) and BCC with z-strut (BCCZ) lattice structures optimised by the proposed method are fabricated using laser-based powder bed fusion (LB-PBF) in AlSi10Mg and are mechanically evaluated. On average, performance for BCC lattice structures improves by 33% and 26% for relative yield strength and relative Young’s modulus respectively. BCCZ lattice structures saw a performance improvement of 25% and 19% for relative yield strength and relative Young’s modulus respectively, thus confirming superior performance at lower relative densities when compared to incumbent designs.

Pemilihan komponen dan pembuatan alat destilasi minyak sereh dengan kapasitas 10 kg

This research aims to design and manufacture a citronella oil distillation device with a capacity of 10 kg. The component selection process involves analysis of various factors such as efficiency, cost, material availability, and ease of maintenance. The main components selected include extraction tubes, condensers and heating systems. Choosing the right material, such as stainless steel for corrosion resistance, is one of the main focuses to ensure tool durability. The design of this distillation tool takes into account aspects of ergonomics and user safety. The manufacturing process involves several stages, starting from detailed design, material procurement, to assembling and testing the equipment. The test results show that this distillation equipment is capable of producing lemongrass oil with quality that meets standards, as well as better time efficiency compared to traditional methods. Thus, it is hoped that this distillation equipment can increase lemongrass oil production, especially for farmers and small and medium industries.

Low-damage optical manufacturing via plasma finishing and figuring

Precision optical components have stringent requirements on surface roughness, form error, and subsurface damage for superior performance. However, conventional grinding, lapping, and polishing processes of fused silica inevitably introduce subsurface damage (SSD) due to the use of abrasives. Thus, this paper proposes an abrasive-free, low-damage manufacturing process for fused silica optical components, which combines inductively coupled plasma (ICP) for SSD recovery and capacitively coupled plasma (CCP) for form error correction. This paper mainly aims to reveal the advantages and challenges of the combined plasma process. The SSD recovery capability of ICP finishing was first verified. The comparison of surface morphology after buffered oxide etch (BOE) etching and CCP etching revealed that extensive surface roughening is caused by plasma etching rather than SSD. Experimental studies on the combination of ICP and CCP demonstrated that ICP finishing can not only recover SSD but also inhibit the surface roughening by plasma etching. The investigation of form error after ICP finishing revealed that the induced form error consists of workpiece distortion and localized deformation with a crater-like structure, affecting the precision and duration of CCP figuring. The combined plasma process was conducted and a low-damage surface with roughness less than Sa 0.3nm and form error less than RMS 20nm was achieved.

Development of a high-fidelity digital twin using the discrete element method for a continuous direct compression process. Part 1. Calibration workflow

In this work, a high-fidelity digital twin was developed to support the design and testing of control strategies for drug product manufacturing via direct compression. The high-fidelity digital twin platform was based on typical pharmaceutical equipment, materials, and direct compression continuous processes. The paper describes in detail the material characterization, the Discrete Element Method (DEM) model and the DEM model parameter calibration approach and provides a comparison of the system’s response to the experimental results for stepwise changes in the API concentration at the mixer inlet. A calibration method for a cohesive DEM contact model parameter estimation was introduced. To assure a correct prediction for a wide range of processes, the calibration approach contained four characterization experiments using different stress states and different measurement principles, namely the bulk density test, compression with elastic recovery, the shear cell, and the rotating drum. To demonstrate the sensitivity of the DEM contact parameters to the process response, two powder characterization data sets with different powder flowability were applied. The results showed that the calibration method could differentiate between the different material batches of the same blend and that small-scale material characterization tests could be used to predict the residence time distribution in a continuous manufacturing process.

Mass Balance Analysis for Therapeutic Peptides: Case Studies, Applications, and Perspectives

The concept of mass balance is discussed as it pertains to the pharmaceutical development of therapeutic peptides. Case studies are presented demonstrating how to perform a mass balance assessment on solid drug substance and solution drug product, and the role of mass balance in the context of the overall product control strategy is discussed. Utilizing mass balance as a specification test where the result is calculated from other critical quality attribute tests, each with their own specification, offers little value as a formalized quality acceptance criterion and may create more deviations, non-value added investigations, and potential batch failures. While useful in characterizing the performance of analytical methods and as part of a rigorous understanding of the manufacturing process and control strategy development, mass balance should not be required as a specification control and should instead be demonstrated during method development and through well-designed forced degradation experiments. Analytical method variability is discussed in relation to the analytical target profile, and the overall impact of sources of variability on the mass balance calculation is described in support of this position.

An image-based nonparametric multivariate EWMA control chart for metal additive manufacturing process monitoring

Additive manufacturing offers considerable promise in terms of manufacturing flexibility, but print quality remains a major obstacle to its widespread adoption. Consequently, timely and accurate detection of process variations or anomalies is critical for implementing corrective actions. Melt pool characteristics are crucial to final product quality, and current state-of-the-art studies on melt pool image flow have primarily focused on in-situ sensing, feature extraction, and their relationship with process settings and material properties. This study aims to develop a statistical process control approach to detect process variations immediately using a predefined distribution of monitoring statistics. Two main challenges are addressed: 1) the unknown distribution of melt pool image features, rendering traditional parametric control charts unreliable and 2) the autocorrelation of melt pool image flow features, violating the traditional control chart assumption of independent and identically distributed monitoring data. To overcome these challenges, we propose a multivariate nonparametric Exponential Weighted Moving Average (EWMA) control chart that can appropriately accommodate stationary serial data correlation to monitor process stability by tracking physical features extracted from the original images. Key features of the proposed control chart include its ability to eliminate serial correlation effects and its distribution-free nature, requiring no prior information about the data distribution. Comparative analysis of simulated and real data demonstrates that the proposed approach outperforms baseline methods in anomaly detection accuracy. An actual case study in laser metal deposition (LMD) further validates the effectiveness of the proposed method.