Large-scale Manufacturing Research Articles

Exploring tribological properties in the design and manufacturing of metal matrix composites: an investigation into the AL6061-SiC-fly ASH alloy fabricated via stir casting process

This study investigates a novel methodology to intricately craft a HAMMC and thoroughly examine its multifaceted mechanical and tribological characteristics. By combining silicon carbide (SiC) and fly ash as reinforcements, a unique identity is bestowed upon this hybrid composite, enhancing its structural integrity and functional attributes. Stir casting is the chosen methodology for fabricating this composite, favored for its economic viability and suitability for large-scale manufacturing. In this research, the emphasis is on developing a cost-effective composite that not only meets stringent economic considerations but also exhibits improved material properties. Within the realm of hybrid metal matrix composites, the well-regarded Al6061 takes on the role of the matrix material, while the synergistic inclusion of fly ash and SiC serves as reinforcing constituents. Three specimens with compostion 90% Al6061 + 5% SiC +5% Fly ash, 90% Al6061 + 10% SiC +6% Fly ash and 90% Al6061 + 15% SiC +7% Fly ash were fabricated. To unravel the intricacies of the fabricated Al6061 metal matrix composite, comprehensive tests are employed. These tests, including the Pin-on Disc test, Scratch test, Rockwell Hardness test, and Charpy Impact test, collectively work to unveil the nuanced tribological and mechanical behaviors encapsulated within this innovative alloy. The results indicated significant improvement in wear resistance in specimen comprising 78% Al6061 + 15% SiC +7% Fly Ash and volumetric loss found to have 0.96 g. Superior hardness characteristics and enhanced abrasion resistance found in 78% Al6061 + 15% SiC +7% Fly Ash than other two specimens. The highest impact strength exhibited in 90% Al 6,061 + 5% SiC +5% Fly ash specimen.

HTERT-Immortalized Mesenchymal Stem Cell-Derived Extracellular Vesicles: Large-Scale Manufacturing, Cargo Profiling, and Functional Effects in Retinal Epithelial Cells.

As the economic burden associated with vision loss and ocular damage continues to rise, there is a need to explore novel treatment strategies. Extracellular vesicles (EVs) are enriched with various biological cargo, and there is abundant literature supporting the reparative and immunomodulatory properties of stem cell EVs across a broad range of pathologies. However, one area that requires further attention is the reparative effects of stem cell EVs in the context of ocular damage. Additionally, most of the literature focuses on EVs isolated from primary stem cells; the use of EVs isolated from human telomerase reverse transcriptase (hTERT)-immortalized stem cells has not been thoroughly examined. Using our large-scale EV-manufacturing platform, we reproducibly manufactured EVs from hTERT-immortalized mesenchymal stem cells (MSCs) and employed various methods to characterize and profile their associated cargo. We also utilized well-established cell-based assays to compare the effects of these EVs on both healthy and damaged retinal pigment epithelial cells. To the best of our knowledge, this is the first study to establish proof of concept for reproducible, large-scale manufacturing of hTERT-immortalized MSC EVs and to investigate their potential reparative properties against damaged retinal cells. The results from our studies confirm that hTERT-immortalized MSC EVs exert reparative effects in vitro that are similar to those observed in primary MSC EVs. Therefore, hTERT-immortalized MSCs may represent a more consistent and reproducible platform than primary MSCs for generating EVs with therapeutic potential.

Toward sustainable process industry based on knowledge graph: a case study of papermaking process fault diagnosis

Process industry suffers from production management in terms of efficiency promotion and waste reduction in large scale manufacturing due to poor organization of the intricate relational databases. In order to enhance the suitability of intelligent manufacturing systems in process industry, this study proposed an innovative top-down structure Knowledge Graph (KG) for process fault diagnosis, and papermaking was taken as a case study. The KG consists of a normalized seven-step-built ontology, which extracted instances of papermaking knowledge via Protégé software. The exported OWL file was imported into Neo4j software for visualization of the KG. The application in papermaking drying process for fault diagnosis shows that it can depict the material and energy flows throughout the process with a clearer relationship visualization than traditional measures. They also enable rationale search for faults and identification of their potential causes. The built KG efficiently manages the vast knowledge of the process, stores unstructured data, and promotes the intelligent development of process with high reusability and dynamicity that can rapidly import new production knowledge as well as flexibly self-updating.

Large-scale manufacturing of functional single-atom ink for convenient glucose sensing

Large-scale manufacturing of functional single-atom ink for convenient glucose sensing

Crystallisation Dynamics in Large-Scale Extrusion Additive Manufacturing: An Analysis with and without Temperature Modification.

Large-Scale Material Extrusion (LS-MEX) is increasingly being used in small-scale production and prototyping due to its ability to create components in new temporal and spatial dimensions. However, the use of this manufacturing process poses microscopic and macroscopic challenges not encountered in previous small-scale production systems. These challenges arise primarily from the prolonged retention of heat in the material, which leads to insufficient strength in the extruded strands at the macrostructural level. As a result, the component can collapse, a phenomenon known as 'slumping'. Thermal energy also influences microstructural changes, such as crystallisation kinetics, which affect properties such as the strength and stiffness of the final product. The duration and dynamics of thermal energy are influenced by manufacturing parameters and the possible use of additional peripheral equipment, which affects component quality. In this study, the influence of thermal energy on structural processes through simulations of polyamide 6 with 40% carbon fibres (PA6 wt.%40 CF) is investigated. The results show that by adjusting the process parameters and using modification units, the thermal profile of the material can be accurately controlled, which allows the microstructural processes to be precisely controlled. This leads to the targeted modification of the macroscopic material properties. The focus of this work is on the combination of numerical simulations of the LS-MEX process with semi-empirical methods for the analysis of crystallisation processes. The application of the Nakamura model, which is used throughout similar investigations, allows a detailed description and prediction of the crystallisation kinetics during the manufacturing process. The study shows that the absolute degree of crystallisation can be determined with simplified assumptions using a combination of thermal simulations and semi-empirical approaches. It was found that the absolute degree of crystallisation increases from the outer interface of the strand to the print bed across the cross-section. This can be attributed to the specific thermal boundary conditions and the resulting temperature profiles at different points.

Trend of pharmaceuticals 3D printing in the Middle East and North Africa (MENA) region: An overview, regulatory perspective and future outlook

The traditional method of producing medicine using the “one-size fits all” model is becoming a major issue for pharmaceutical manufacturers due to its inability to produce customizable medicines for individuals’ needs. Three-dimensional (3D) printing is a new disruptive technology that offers many benefits to the pharmaceutical industry by revolutionizing the way pharmaceuticals are developed and manufactured. 3D printing technology enables the on-demand production of personalized medicine with tailored dosage, shape and release characteristics. Despite the lack of clear regulatory guidance, there is substantial interest in adopting 3D printing technology in the large-scale manufacturing of medicine. This review aims to evaluate the research efforts of 3D printing technology in the Middle East and North Africa (MENA) region, with a particular emphasis on pharmaceutical research and development. Our analysis indicates an upsurge in the overall research activity of 3D printing technology but there is limited progress in pharmaceuticals research and development. While the MENA region still lags, there is evidence of the regional interest in expanding the 3D printing technology applications in different sectors including pharmaceuticals. 3D printing holds great promise for pharmaceutical development within the MENA region and its advancement will require a strong collaboration between academic researchers and industry partners in parallel with drafting detailed guidelines from regulatory authorities.

A sensor-driven operations and maintenance planning approach for large-scale leased manufacturing systems

The rise of mass customisation drives manufacturers to adopt leasing agreements for their machinery rather than outright their ownership. This industrial trend results in large-scale leased manufacturing systems, where the asset conditions and maintenance requirements for a fleet of machines and/or production lines from several manufacturers are continuously monitored and managed by a lessor. In this paper, we propose an operations and maintenance planning model that explicitly models (i) dynamic real-time failure rate predictions for machines based on sensor-driven degradation data, (ii) optimal routes for maintenance teams across a number of geographically-distributed manufacturing sites, and (iii) operational outcomes. The model can handle complex maintenance and operational outcome interdependencies between multiple machines, and incorporate demand for different products, heterogeneous machine capacities and capabilities, factory topology, and the resulting production flow capacities of products. To demonstrate the model’s practicality, it is applied to three experimental case studies with various numbers of machines, operating schedules, product types, and flow capacities. The results show that the proposed model significantly outperforms the traditional reliability-based maintenance model in key metrics such as the number of unexpected failures, the cost of preventive maintenance actions, machine downtime, the percentage of unsatisfied demand, and total cost.

Advancements in Polymer-Assisted Layer-by-Layer Fabrication of Wearable Sensors for Health Monitoring.

Recent advancements in polymer-assisted layer-by-layer (LbL) fabrication have revolutionized the development of wearable sensors for health monitoring. LbL self-assembly has emerged as a powerful and versatile technique for creating conformal, flexible, and multi-functional films on various substrates, making it particularly suitable for fabricating wearable sensors. The incorporation of polymers, both natural and synthetic, has played a crucial role in enhancing the performance, stability, and biocompatibility of these sensors. This review provides a comprehensive overview of the principles of LbL self-assembly, the role of polymers in sensor fabrication, and the various types of LbL-fabricated wearable sensors for physical, chemical, and biological sensing. The applications of these sensors in continuous health monitoring, disease diagnosis, and management are discussed in detail, highlighting their potential to revolutionize personalized healthcare. Despite significant progress, challenges related to long-term stability, biocompatibility, data acquisition, and large-scale manufacturing are still to be addressed, providing insights into future research directions. With continued advancements in polymer-assisted LbL fabrication and related fields, wearable sensors are poised to improve the quality of life for individuals worldwide.

A Low-Cost Defect Segmentation System Based on IoT for Large-Scale Photovoltaic Manufacturing

A Low-Cost Defect Segmentation System Based on IoT for Large-Scale Photovoltaic Manufacturing

Biosynthesis and characterizations of silver nanoparticles by using green banana peel extract: Evaluation of their antibacterial and electrical performances

Biosynthesized silver nanoparticles (Ag NPs) hold tremendous promise in nano-bioscience, with applications spanning engineering, science, and industry. This study delves into their fabrication process, crystallographic characteristics, and nanostructures. Employing green banana peel extract (GBPE), Ag NPs were synthesized. Various analytical techniques, such as UV–Vis absorption spectrophotometry (UV), X-ray diffraction (XRD), Gas chromatography-mass spectrometry (GC-MS), Field emission scanning electron microscopy (FESEM), Fourier-transform infrared spectroscopy (FTIR), and Transmission electron microscopy (TEM) elucidate their attributes. UV–visible analysis reveals a 413 nm absorption band due to surface plasmon resonance. The Ag NPs exhibit a face-centered cubic structure with an average crystallite size of 45.87 nm. Lattice parameters and dislocation density are also determined. When tested against harmful bacteria, such as E. coli and S. epidermidis, advanced microscopy reveals a median size of particles of 55.12 nm and demonstrates their antibacterial characteristics. These environmentally benign Ag NPs also improve the efficiency of bio-electrochemical cells (BECs), opening the door to large-scale manufacturing at a reasonable cost and broadening the range of possible uses.

Highly stable power control for chip-based continuous-variable quantum key distribution system.

Quantum key distribution allows secret key generation with information theoretical security. It can be realized with photonic integrated circuits to benefit the tiny footprints and the large-scale manufacturing capacity. Continuous-variable quantum key distribution is suitable for chip-based integration due to its compatibility with mature optical communication devices. However, the quantum signal power control compatible with the mature photonic integration process faces difficulties on stability, which limits the system performance and causes the overestimation of a secret key rate that opens practical security loopholes. Here, a highly stable chip-based quantum signal power control scheme based on a biased Mach-Zehnder interferometer structure is proposed, theoretically analyzed, and experimentally implemented with standard silicon photonic techniques. Simulations and experimental results show that the proposed scheme significantly improves the system stability, where the standard deviation of the secret key rate is suppressed by an order of magnitude compared with the system using traditional designs, showing a promising and practicable way to realize a highly stable continuous-variable quantum key distribution system on chip.

IOT based water flow meter using ThingSpeak

The Large scale manufacturing companies are fully automated. Soft Drink Industries and Chemical industries have to constantly measure and quantify the liquids that they are handling during this automation process, and the most common sensor used to measure the flow of a liquid is a Flow Sensor. By using a flow sensor with a microcontroller like NodeMCU, we can calculate the flow rate, and check the volume of liquid that has passed through a pipe, and control it as required. Apart from manufacturing industries, flow sensors can also be found in the agriculture sector, food processing, water management, mining industry, water recycling, coffee machines etc. Further, a water flow sensor will be a good addition to projects like Automatic water dispenser and smart irrigation systems where we need to monitor and control the flow of liquids. In this project, we are going to build a water flow meter using NodeMCU. We will interface the water flow sensor with NodeMCU and LCDI2C, and program it to display the volume of water, which has passed through the valve. For this particular project, we are going to use the YF-S201 water flow sensor, which uses a hall effect to sense the flow rate of the liquid. The measured values are also communicated to the ThingSpeak cloud. The parameters can be monitored remotely form any part of the world. When the volume exceeds the threshold value, Thingspeak will activate the Thingspeak react to send a message to the responsible person with help of the IFTTT applet.

Design and scale up of a mixing process for a novel automotive coating

The study reported here was performed as part of a larger project aiming to develop a high performance automotive coating and the associated manufacturing process to enable large scale manufacture of the new product. We report from the process development aspect of the project which aimed at establishing the comparative blending performance of two types of impeller- one currently in use and an alternative- at different scales. Mixing time measurements compared on the basis of volumetric power input were comparable for the sawtooth impeller and pitched blade turbine over the turbulent and transitional regimes at formulation (T= 0.13 m, ∼2 l) and pilot scales (T= 0.30 m, ∼ 20 l). At the largest scale of ∼ 160 l, it took a lot longer to blend when using the sawtooth impeller. Measured mixing time results were in agreement with predicted values using the well-established correlation for both impellers in T= 0.30 m and also for the PBT at large scale, For the sawtooth impeller the correlation underpredicted at large scale unless a higher value for the constant in the mixing time correlation (about twice) was used. This deviation in the performance at large scale has highlighted the complexity of design and scale up using a sawtooth impeller.

Development of novel lipoplex formulation methodologies to improve large-scale transient transfection for lentiviral vector manufacture

Large-scale transient transfection has advanced significantly over the last 20 years, enabling the effective production of a diverse range of biopharmaceutical products, including viral vectors. However, a number of challenges specifically related to transfection reagent stability and transfection complex preparation times, remain. New developments and improved transfection technologies are required to ensure that transient gene expression-based bioprocesses can meet the growing demand for viral vectors. In this paper we demonstrate the growth of cationic lipid-based liposomes, an essential step in many cationic lipid-based transfection processes, can be controlled through adoption of low pH (pH 6.40 – pH 6.75) and in low salt concentration (0.2X PBS) formulations, facilitating improved control over the nanoparticle growth kinetics and enhancing particle stability. Such complexes retain the ability to facilitate efficient transfection for prolonged periods compared to standard preparation methodologies. These findings have significant industrial applications for the large-scale manufacture of lentiviral vectors for two principal reasons. First, the alternative preparation strategy enables longer liposome incubation times to be used, facilitating effective control in a GMP setting. Second, the improvement in particle stability facilitates the setting of wider process operating ranges, which will significantly improve process robustness and maximise batch-to-batch control and product consistency.

Best management practice adoption amongst potato producers in Ontario: a study of drivers and barriers

Best management practices (BMPs) are practical, affordable alternatives to conventional production systems. They contribute to improving the agricultural production system’s ability to address social, economic, and ecological challenges. BMPs enhance the viability and sustainability of agriculture when successfully applied, but in systems where intensive industrial agriculture predominates, their use is limited. Working with potato producers (large, medium, and small scale) in South-Western and Central Ontario, Canada this project applied a Systems Thinking approach to understand motivating drivers and structural, institutional, and organizational barriers impacting the adoption of BMPs for potato cultivation. This study used a mixed-methods approach for two years to collect quantitative and qualitative data using a farm-level survey, focus groups, workshops, and participant observation. Data was collected regarding demographics, management approaches, social networking, and perceived challenges with BMPs uptake. Our data analysis revealed that family and future generations, ecosystem, soil and human health, community and social relationships, and efficiency and profitability were motivating drivers (based on beliefs and values) influencing management decisions. However, structural, institutional, and organizational barriers (including market access, regulation, production efficiencies and competition), mediate producers’ abilities to act according to these motivations. Small-scale, medium-scale and large-scale producers are impacted by these barriers differently. In understanding the decision-making factors which drive BMP uptake in Ontario’s potato sector, policy and program design can leverage drivers and reduce barriers.

A Three-in-One Hybrid Strategy for High-Performance Semiconducting Polymers Processed from Anisole.

The development of semiconducting polymers with good processability in green solvents and competitive electrical performance is essential for realizing sustainable large-scale manufacturing and commercialization of organic electronics. A major obstacle is the processability-performance dichotomy that is dictated by the lack of ideal building blocks with balanced polarity, solubility, electronic structures, and molecular conformation. Herein, through the integration of donor, quinoid and acceptor units, an unprecedented building block, namely TQBT, is introduced for constructing a serial of conjugated polymers. The TQBT, distinct in non-symmetric structure and high dipole moment, imparts enhanced solubility in anisole-a green solvent-to the polymer TQBT-T. Furthermore, PTQBT-T possess a highly rigid and planar backbone owing to the nearly coplanar geometry and quinoidal nature of TQBT, resulting in strong aggregation in solution and localized aggregates in film. Remarkably, PTQBT-T films spuncast from anisole exhibit a hole mobility of 2.30 cm2 V-1 s-1, which is record high for green solvent-processable semiconducting polymers via spin-coating, together with commendable operational and storage stability. The hybrid building block emerges as a pioneering electroactive unit, shedding light on future design strategies in high-performance semiconducting polymers compatible with green processing and marking a significant stride towards ecofriendly organic electronics.

Automated Reinforcement during Large-Scale Additive Manufacturing: Structural Assessment of a Dual Approach

Automated and seamless integration of reinforcement is one of the main unresolved challenges in large-scale additive construction. This study leverages a dual-reinforcement solution consisting of high-dosage steel fiber (up to 2.5% by volume) and short vertical reinforcements as a complementary reinforcement technique for 3D-printed elements. The mechanical performance of the printing material was characterized by measuring the compressive, flexural, and uniaxial tensile strengths of mold-cast specimens. Furthermore, the flexural performance of the plain and fiber-reinforced 3D-printed beams was evaluated in the three main loading directions (X, Y, and Z-directions in-plane). In addition, short vertical threaded reinforcements were inserted into the fiber-reinforced 3D-printed beams tested in the Z-direction. The experimental results revealed the superior flexural performance of the fiber-reinforced beams loaded in the longitudinal directions (X and Y). Moreover, the threaded reinforcement significantly increases the flexural strength and ductility of beams loaded along the interface, compared to the control. Overall, the proposed dual-reinforcement approach, which exhibited notably less porosity compared to the mold-cast counterpart, holds great potential as a reinforcement solution for 3D-printed structures without the need for manual operations.

Towards the fabrication of fully printed flexible P(VDF-TrFE)-based piezoelectric sensors

The emergent Internet of Things (IoT) market has increased the need of sensors, actuators and nanogenerators, demanding cost-effective and large-scale manufacturing methods to fabricate these devices. Printed electronics (PE), which consists of the application printing and coating technologies in the deposition of functional materials, is one of the ways to process low-cost lightweight, semi-transparent, and flexible devices, usually employing polymers as functional materials. In this work we present the fabrication of poly(vinylidene fluoride-co-trifluoroethylene) (P(VDF-TrFE)) copolymer-based printed piezoelectric devices applying different semi-transparent flexible conductive substrates as bottom electrodes. The screen-printing process was chosen as a large-scale cost-effective fabrication method at low-temperature processing. Printing and the laser scribing parameters were established, and the effectively use of silver and PEDOT:PSS as top electrodes was demonstrated. The final devices were electrically poled and characterized by Electrochemical Impedance Spectroscopy (EIS) and correlations among the device’ performance regarding the different bottom and top electrodes were set up, leading to processing recommendations. Employing a cycle olefin polymer coated with silver nanowires (AgNW) as substrate, P(VDF-TrFE) as active material and silver as top electrode, a 223 µF/m2 capacitance was obtained when compressing at 2.37 KPa, demonstrating the devices charge storage capacity by the application of a mechanical stress. All the employed processing conditions can be easily integrated in a R2R pilot line, allowing high throughput, low-cost and large-area manufacturing. Additionally, the use of the polymer substrates enables the fabrication of flexible and lightweight devices.

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.

All-solution-processed ultraflexible wearable sensor enabled with universal trilayer structure for organic optoelectronic devices.

All-solution-processed organic optoelectronic devices can enable the large-scale manufacture of ultrathin wearable electronics with integrated diverse functions. However, the complex multilayer-stacking device structure of organic optoelectronics poses challenges for scalable production. Here, we establish all-solution processes to fabricate a wearable, self-powered photoplethysmogram (PPG) sensor. We achieve comparable performance and improved stability compared to complex reference devices with evaporated electrodes by using a trilayer device structure applicable to organic photovoltaics, photodetectors, and light-emitting diodes. The PPG sensor array based on all-solution-processed organic light-emitting diodes and photodetectors can be fabricated on a large-area ultrathin substrate to achieve long storage stability. We integrate it with a large-area, all-solution-processed organic solar module to realize a self-powered health monitoring system. We fabricate high-throughput wearable electronic devices with complex functions on large-area ultrathin substrates based on organic optoelectronics. Our findings can advance the high-throughput manufacture of ultrathin electronic devices integrating complex functions.