Traditional Manufacturing Processes Research Articles

Rapidly-manufactured CD276 CAR-T cells exhibit enhanced persistence and efficacy in pancreatic cancer

BackgroundPancreatic cancer is one of the most lethal malignancies and the lack of treatment options makes it more deadly. Chimeric Antigen Receptor T-cell (CAR-T) immunotherapy has revolutionized cancer treatment and made great breakthroughs in treating hematological malignancies, however its success in treating solid cancers remains limited mainly due to the lack of tumor-specific antigens. On the other hand, the prolonged traditional manufacturing process poses challenges, taking 2 to 6 weeks and impacting patient outcomes. CD276 has recently emerged as a potential therapeutic target for anti-solid cancer therapy. Here, we investigated the efficacy of CD276 CAR-T and rapidly-manufactured CAR-T against pancreatic cancer.MethodsIn the present study, CD276 CAR-T was prepared by CAR structure carrying 376.96 scFv sequence, CD8 hinge and transmembrane domain, 4-1BB and CD3ζ intracellular domains. Additionally, CD276 rapidly-manufactured CAR-T (named CD276 Dash CAR-T) was innovatively developed by shortening the duration of ex vitro culture to reduce CAR-T manufacturing time. We evaluated the anti-tumor efficacy of CD276 CAR-T and further compared the functional assessment of Dash CAR-T and conventional CAR-T in vitro and in vivo by detecting the immunophenotypes, killing ability, expansion capacity and tumor-eradicating effect of CAR-T.ResultsWe found that CD276 was strongly expressed in multiple solid cancer cell lines and that CD276 CAR-T could efficiently kill these solid cancer cells. Moreover, Dash CAR-T was successfully manufactured within 48–72 h and the functional validation was carried out subsequently. In vitro, CD276 Dash CAR-T possessed a less-differentiated phenotype and robust proliferative ability compared to conventional CAR-T. In vivo xenograft mouse model, CD276 Dash CAR-T showed enhanced anti-pancreatic cancer efficacy and T cell expansion. Besides, except for the high-dose group, the body weight of mice was maintained stable, and the state of mice was normal.ConclusionsIn this study, we proved CD276 CAR-T exhibited powerful activity against pancreatic cancer cells in vitro and in vivo. More importantly, we demonstrated the manufacturing feasibility, acceptable safety and superior anti-tumor efficacy of CD276 Dash CAR-T generated with reduced time. The results of the above studies indicated that CD276 Dash CAR-T immunotherapy might be a novel and promising strategy for pancreatic cancer treatment.

The choice of sustainable coproduction technology in a supply chain

Coproduction is recognised as a sustainable technique that promotes optimal resource use by extracting value from leftover materials that would otherwise be wasted in traditional manufacturing processes. However, the sustainability of coproduction technology in supply chains remains uncertain, subject to fluctuations in suppliers' raw material prices. In this paper, we model a decentralised supply chain consisting of a raw material supplier and a coproduction manufacturer, and investigate how their interactions affect the economic and environmental performance of coproduction. We find that manufacturers should consider adopting coproduction technology when the size of the green consumer segment is either relatively small or significantly large. Specifically, if applicable, the manufacturer will endogenously set the coproduct quality at a moderate level, maximising material utilisation. This result offers novel insights into the choice of coproduction technology within a supply chain, particularly considering that a significant motivation for manufacturers to embrace coproduction is to capture value from green consumption. Additionally, when the size of the green consumer segment is sufficiently large, the supplier can benefit from coproduction by raising the wholesale price for raw materials, creating a win-win outcome for both the supplier and the manufacturer. However, we also find that coproduction technology is not always beneficial to the environment. The manufacturer may produce large quantities of coproducts due to high demand from green consumers, leading to increased total material consumption and waste generation.

Adopting quality management practices in the industry 4.0 era: an investigation into the challenges

In this transformative phase of Industry 4.0, the integration of advanced digital technologies into traditional manufacturing processes presents a paradigm shift in quality management. This seminal study ventures into the forefront of this transition, uncovering the intricate challenges impeding the adoption of Quality Management Practices (QMP) amidst digital innovation. Leveraging a comprehensive survey with 172 quality management professionals, alongside the methodological rigour of Exploratory Factor Analysis (EFA) and the Analytical Hierarchy Process (AHP), our research delineates fifteen pivotal barriers to the harmonious integration of digital technologies with quality management systems. Predominantly, ‘Organisational Behaviour’ and ‘Information Technology and Governance’ surface as critical dimensions, outlining the complex landscape stakeholders must navigate. Central to our findings are leadership, cybersecurity, data protection, and organisational structure, underscored as the primary challenges that demand strategic focus. This investigation offers a pioneering framework for global stakeholders, illuminating a path forward in the quest for Quality 4.0. It marks a significant contribution to the literature by proposing a roadmap for organisations striving for excellence and innovation in the Industry 4.0 era, advocating for a seamless fusion of digital transformation and quality management.

Overcoming the semantic gap in the customer-to-manufacturer (C2M) platform: A soft prompts-based approach with pretrained language models

Customer-to-Manufacturer (C2M) is a strategy in smart manufacturing where customers collaborate with manufacturers for customized product development on an online platform. The platform enables the shift from the traditional manufacturing process, which is driven by research and marketing, toward a customer-centric product development process. However, a challenge arises as customers lack technical knowledge to communicate their product specifications effectively, creating a semantic gap. This paper proposes a soft prompt-based network structure that utilizes pretrained language models to bridge the semantic gap on the C2M platform. To address limited customer needs data and imbalanced classes, a large corpus of product review texts is used to establish a mapping between reviews and product specifications. A smaller set of customer needs text is then employed to adapt this mapping to the target customer needs-product specifications relationship, thereby closing the semantic gap. The experimental results demonstrate the effectiveness of the proposed model adaptation operation and the prompting structure. Additionally, the experiments highlight the robustness of the proposed method against variations in training data size, thereby mitigating the challenges posed by imbalanced classes. The proposed method could potentially bring innovation to product customization and C2M platform development. By bridging the semantic gap, companies can better integrate customers in the co-design process and effectively translate customer needs into actionable product specifications.

Domain‐specific translation tool from structured text to C source code with code readability enhancement in programmable logic controllers

AbstractThe Industrial Internet has emerged as a key technology in the field of industrial automation, revolutionizing traditional manufacturing processes and enabling advanced control systems by integrating machines, sensors, and software systems through network connectivity, allowing for real‐time data exchange, analysis, and decision‐making in industrial environments. Programmable Logic Controllers (PLCs) play a critical role in industrial automation systems, which are specialized digital computers designed to control various manufacturing processes and machinery. As a promising language, Structured Text (ST) is of paramount importance for industrial Internet, and it is essential to translate ST into C, which is widely used in various industries for implementing control systems. However, due to differences in syntax, data types, and programming paradigms between the two languages, the translation process is facing several challenges. In this paper, we present a domain‐specific translation tool that automates the process of converting ST code to C code. This tool incorporates advanced AI techniques, particularly leveraging the capabilities of NL‐PL LLMs, to facilitate accurate and efficient translation while generating comprehensive documentation to assist developers. Finally, the evaluation and case studies conducted validate the effectiveness of the tool, demonstrating its practical applicability and benefits in real‐world industrial settings.

PROCESS DEVELOPMENT IN MECHANICAL ENGINEERING: INNOVATIONS, CHALLENGES, AND OPPORTUNITIES

Process development in mechanical engineering encompasses a broad spectrum of innovations, challenges, and opportunities that drive advancements in various industries. This review delves into the multifaceted landscape of process development within mechanical engineering, highlighting key themes and trends. Innovations in process development are propelled by the continuous quest for efficiency, sustainability, and enhanced performance. Advances in additive manufacturing, automation, and digitalization have revolutionized traditional manufacturing processes, enabling the creation of complex geometries with unprecedented precision and speed. Additive manufacturing techniques such as 3D printing offer versatility in material selection and design freedom, facilitating rapid prototyping and customization while minimizing material wastage. Automation technologies, including robotics and AI-driven systems, optimize production workflows, augmenting productivity and reducing human error. Moreover, digital twins and simulation tools empower engineers to simulate and optimize processes virtually, accelerating product development cycles and minimizing costly experimentation. However, alongside these innovations, mechanical engineers face a myriad of challenges. The integration of new technologies often requires substantial investment in infrastructure and workforce training. Quality control and assurance remain critical concerns, particularly in additive manufacturing, where ensuring part integrity and repeatability is paramount. Furthermore, the sustainability implications of emerging processes must be carefully evaluated to mitigate environmental impact and resource depletion. Despite these challenges, process development in mechanical engineering presents abundant opportunities for growth and advancement. The rise of Industry 4.0 initiatives fosters collaboration between academia, industry, and government, driving research and development efforts towards sustainable and interconnected manufacturing ecosystems. The advent of advanced materials, including composites and biomaterials, unlocks new possibilities for lightweight structures, enhanced performance, and tailored functionalities. Additionally, the pursuit of circular economy principles promotes resource efficiency and waste reduction throughout the product lifecycle. In conclusion, process development in mechanical engineering is characterized by a dynamic interplay of innovation, challenges, and opportunities. By embracing emerging technologies, addressing key challenges, and leveraging collaborative partnerships, mechanical engineers can drive transformative change across industries, paving the way for a more efficient, sustainable, and interconnected future.
 Keywords: Process, Development, Mechanical, Engineering, Innovation, Review.

SUSTAINABLE FOOTWEAR DESIGN: BALANCING COMFORT, FUNCTIONALITY AND ENVIRONMENTAL IMPACT

Sustainability is becoming increasingly important in the footwear industry, with consumers demanding products that are not only comfortable and functional but also environmentally friendly. This paper explores the challenges and opportunities of sustainable footwear design, focusing on the balance between comfort, functionality, and environmental impact. The first part of the paper examines the current state of the footwear industry, highlighting the environmental issues associated with traditional footwear manufacturing processes and materials. It then discusses the growing interest in sustainable footwear design and the need for innovative solutions to reduce the industry's environmental footprint. Next, the paper explores various aspects of sustainable footwear design, including material selection, manufacturing processes, and product life cycle. It discusses the importance of using eco-friendly materials such as recycled plastics, organic cotton, and sustainable leather alternatives, as well as the benefits of incorporating sustainable practices into the design process. The paper also considers the challenges of balancing sustainability with comfort and functionality. It discusses the importance of designing footwear that meets the needs of consumers while also minimizing environmental impact, highlighting the role of innovative design and technology in achieving this balance. Keyword: sustainable footwear design, comfort, functionality, environmental impact, eco-friendly materials, innovation

Innovative syntheses of immobilized CuxO semiconductors grown on 3D prints and their photoelectrochemical activity for sulfamethoxazole degradation

Traditional copper oxide manufacturing processes require high energy consumption, high synthesis temperatures, and long process times. This study proposes an innovative additive manufacturing process to support immobilized copper oxide, offering greater design flexibility and customization. CuxO semiconductors were synthesized on 3D-printed substrates via the anodization process and evaluated for their effectiveness in degrading sulfamethoxazole (SMX). XRD analysis of the samples revealed the presence of both CuO and Cu2O crystalline phases, this mixture of oxides helps to expand the absorption range of visible light. The immobilized CuxO semiconductors exhibited band gaps ranging between 1.6 and 1.8 eV. Negative current densities and Mott-Schottky analysis confirmed the nature of the p-type semiconductor. Semiconductors grown by 3D printing demonstrated remarkable degradation capacity for the antibiotic sulfamethoxazole (SMX), achieving 60% degradation after 360 minutes under visible light. Kinetic degradation tends to be a first-order and zero-order model. TOC analysis further revealed the formation of reaction intermediates during SMX degradation, ultimately leading to the mineralization of the contaminant. Based on these results, we report, for the first time CuxO semiconductors grown on large 3D-printed substrates as promising photocatalysts for the degradation of emerging water pollutants. Based on these results, we report, for the first time, that CuxO semiconductors grown on large 3D-printed substrates are promising photocatalysts for the degradation of emerging water contaminants. Furthermore, it should be emphasized that the proposed method is faster and does not require subsequent thermal treatments for its functionalization, making it attractive for various industrial applications.

INNOVATIVE MATERIAL PROCESSING TECHNIQUES IN PRECISION MANUFACTURING: A REVIEW

Precision manufacturing plays a pivotal role in various industries, demanding high accuracy, efficiency, and quality in the production process. The continual pursuit of innovation in material processing techniques is essential to meet evolving demands and challenges. This review explores the latest advancements and innovations in material processing methods within precision manufacturing. The review encompasses a comprehensive analysis of various innovative material processing techniques, including additive manufacturing, subtractive manufacturing, and hybrid approaches. Additive manufacturing, often referred to as 3D printing, has gained significant attention for its capability to produce complex geometries with high precision. The exploration of novel materials, such as metal alloys, polymers, and composites, expands the applicability of additive manufacturing in diverse industrial sectors. Subtractive manufacturing techniques, such as milling, turning, and grinding, are also undergoing transformative advancements to enhance precision and efficiency. Emerging technologies like abrasive waterjet machining, electrical discharge machining (EDM), and laser machining offer improved accuracy and surface finish while enabling the processing of a wide range of materials, including hard-to-machine alloys and composites. Hybrid manufacturing approaches, combining additive and subtractive techniques, are revolutionizing precision manufacturing by leveraging the strengths of both methods. These hybrid systems enable the production of intricate components with high precision, reduced lead times, and minimized material waste, addressing the challenges of traditional manufacturing processes. Furthermore, the review highlights advancements in process monitoring and control technologies, such as in-process sensing, real-time feedback systems, and adaptive control algorithms, facilitating enhanced quality assurance and productivity in precision manufacturing. The integration of advanced computational tools, simulation techniques, and artificial intelligence further augments the optimization and customization capabilities of material processing techniques, driving efficiency and innovation in precision manufacturing. Overall, this review provides valuable insights into the latest developments and trends in innovative material processing techniques, offering a roadmap for future research directions and applications in precision manufacturing industries.
 Keywords: Material, Processing, Techniques, Precision, Manufacturing, Review.

Additive manufacturing of Invar 36 alloy

Invar 36 alloy, renowned for its ultra-low coefficient of thermal expansion (CTE), is a functional Fe–Ni alloy that finds wide applications in aerospace and precision instruments. Additive manufacturing (AM), as a rapid digital manufacturing process, can efficiently and flexibly fabricate Invar 36 alloy parts with complex geometric and exceptional properties. Considering the advantages of AM and the increasing interest and demand for Invar 36 alloy parts fabrication by AM in recent years, it is imperative to provide a comprehensive summary of the current research status and technological advancements pertaining to AM Invar 36 alloy. Firstly, an overview of the AM processes currently employed for fabricating Invar 36 alloy is provided, including laser powder bed fusion, selective laser sintering, directed energy deposition, cold spray additive manufacturing, wire arc additive manufacturing, and binder jetting. Additionally, the microstructure, mechanical properties, and CTE of Invar 36 alloy manufactured by AM are summarized. Even eliminating the post heat treatment, the as-printed Invar 36 alloy can achieve excellent low CTE and mechanical properties, comparable to or exceeding traditional manufacturing processes. Moreover, the advantages and research progress of AM Invar 36 alloy composites are introduced. Enhancing mechanical properties while reducing CTE is a common challenge for both AM Invar 36 alloy and Invar composites. Finally, the technical gaps, research trends, and potential applications of AM Invar 36 alloy are summarized and prospected.

Acoustic properties of natural fiber reinforced composite micro-perforated panel designed using 3D printing

The present study investigated the acoustic performance of biodegradable MPP absorbers made of natural fiber-reinforced composites (NFRC) using 3D printing. The novelty of this current research lies in the recent development of a methodology that aids industry professionals in optimizing the production of MPP (Micro Perforated Panel) at a competitive cost. This is achieved by addressing and eliminating issues commonly faced in traditional manufacturing processes, such as manual preparation and pressing. The FDM technique was used to fabricate test samples utilizing the PLA/corkwood composite. Using an impedance tube device with two microphones, the acoustic absorption coefficients of MPPs with different perforation diameters, thicknesses, and perforation rates were measured. Maa's analytical model was used to predict the acoustic absorption performance. Moreover, considering the average sound absorption and total cost of fabricating the samples, RSM-CCD was employed to optimize these samples. In the end, the parallel arrangement of MPP double layer and the combination of MPP with kenaf porous material were tested to improve the sound absorption performance. The results showed that the average sound absorption coefficient of the NFRC-MPP sound absorber is 25% more than that of conventional MPP sound absorbers.

Fabrication and characterization of Nickel-coated 3D printed electrodes for enhanced oxygen evolution reaction in acidic media at various temperatures

Additive manufacturing (AM), often referred to as 3D printing, is a new technology that allows objects to be created by adding layer by layer, as opposed to traditional manufacturing processes. Therefore, the rapid and cost-effective AM method can facilitate research and development efforts in the field of electrochemistry. In this study, oxygen evolution reaction (OER) electrodes are fabricated by a 3D printing technique utilizing carbon-based (PP filament) and graphene-based PLA filaments (BM filament). Electrodes are then coated with Ni by electrochemical deposition method at different temperatures. Electrochemical analysis of Ni coated PP and BM electrodes is made in acidic environments (0.5 M H2SO4) using different characterization techniques. The results indicate that PP/Ni-50 and BM/Ni-50 electrodes have the highest catalytic activity for OER in acidic media. PP/Ni-50 and BM/Ni-50 electrodes exhibited a superior double layer (Cdl) value than other Ni coated 3D printed electrode samples, and their active surface areas are calculated as 0.201 cm2 and 0.286 cm2, respectively. A larger active surface area leads to an increase in the number of active sites, causing the OER process to be more effective. Consequently, increasing the active surface area of electrode samples is crucial for improving the efficiency and effectiveness of the Oxygen Evolution Reaction (OER) process, especially in the context of renewable energy and sustainable technology applications.

Quality Evaluation of Refrigerated Salted Butter Made with Goat and Cow Milk

Butter is a dairy product that is susceptible to oxidation, which causes a rancid taste and a short shelf life. The quality of the butter depends on the quality of milk. The aim of the study is to determine the quality of butter made from goat and cow reared by small-scale farmers in Yogyakarta with the traditional manufacturing process. The milk of Saanen-Peranakan Ettawa (Sapera) goats and Fresian Holstein were taken from farmers in Sleman district, Yogyakarta, Indonesia. Butters were sampled after 0, 15, 30 days storage. This study used the Nested Design method , namely the nested quality of butter in the type of milk. The result showed that butter made from cow milk produced a higher fat content compared to goat milk butter (P<0.05), namely 85.29 ± 0.04% and 80.10 ± 0.27%. The acid value increased while pH value was decreased during storage (P<0.05). There was no increase in peroxide value in cow butter but there was an increase in goat butter on day 0 to day 15 (P<0.05). It can be concluded that the goat and cow milk reared by small-scale farmers in Yogyakarta have good quality so it produced good quality butter which is still good for consumption until 30 days of storage in the refrigerator.

Anisotropy of microstructure, mechanical properties and thermal expansion in Invar 36 alloy fabricated via laser powder bed fusion

Invar 36 is a renowned iron-nickel alloy with an ultra-low coefficient of thermal expansion (CTE), which is widely used in aerospace and precision instruments. Laser powder bed fusion (LPBF) as a prevalent metal additive manufacturing technique could break through the limitations of traditional processes, such as low material utilization and difficulties in forming complex structures. In this work, Invar 36 alloy specimens were fabricated via LPBF process in 0° (H0 specimen), 45° (D45 specimen), and 90° (V90 specimen) build orientations. The microstructure, tensile properties, thermal expansion, and magnetic properties of the three orientations specimens were comprehensively investigated, and the anisotropy of microstructure, yield strength and CTE were analyzed. The V90 specimen exhibited the highest elongation (62.70%), while the D45 specimen owned the highest yield strength (496 MPa). The anisotropic mechanical properties can be attributed to variations in dislocation density, grain size, and intrinsic yield strength. The CTE of LPBF-fabricated Invar 36 alloy specimens were all lower than that of traditional manufacturing process at all temperature ranges. Since CTE is more related to magnetic properties, not sensitive to microstructure, the anisotropy of CTE is not significant in three build orientations. This study has significant implications to produce Invar 36 alloy devices with exceptional properties and 3D dimensional stability via the LPBF process.

EcoPrintAnalyzer: Assessing Sustainability in Material Extrusion Additive Manufacturing for Informed Decision-Making

Sustainability is fundamental in the field of additive manufacturing (AM) for improving eco-consciousness and driving evolution toward environmentally responsible production methods. Compared to traditional manufacturing processes, AM technologies can be more resource-efficient and offer innovative solutions for creating eco-friendly processes and products. Nevertheless, there is significant potential for improvement in additive manufacturing sustainability. The key factors driving this improvement include design optimization and increased awareness. Designers and engineers can create designs that optimize material efficiency and reduce support structures. Raising awareness and educating stakeholders about the environmental benefits of AM can promote responsible choices throughout the industrial process. The development of a tool to assess the environmental impact of AM processes could be a significant contribution to advancing sustainability in the AM field. The EcoPrintAnalyzer, introduced as a complementary plugin for UltiMaker Cura, offers data on the equivalent carbon dioxide footprint and energy consumption in material extrusion additive manufacturing. This tool facilitates informed decision-making regarding materials, designs, and settings, enabling users to optimize their AM processes for reduced waste and enhanced energy efficiency. Beyond aiding decision-making, the EcoPrintAnalyzer fosters environmental consciousness and encourages the adoption of sustainable practices within the AM ecosystem. The efficacy of the tool is demonstrated through the 3DBenchy model case study, showcasing its intuitive interface and seamless integration within the AM process workflow for immediate and comparative environmental impact assessments across different process configurations.

Acoustic properties of natural fiber reinforced composite micro-perforated panel (NFRC-MPP) made from cork fiber and polylactic acid (PLA) using 3D printing

The present study investigated the acoustic performance of biodegradable MPP absorbers made of natural fiber-reinforced composites (NFRC) using 3D printing. The novelty of this current research lies in the recent development of a methodology that aids industry professionals in optimizing the production of MPP (Micro-Perforated Panel) at a competitive cost. This is achieved by addressing and eliminating various issues commonly faced in traditional manufacturing processes, such as manual preparation and pressing. The FDM technique was used to fabricate test samples utilizing the PLA/corkwood composite. Using an impedance tube device with two microphones, the acoustic absorption coefficients of MPPs with different perforation diameters, thicknesses, and perforation rates were measured. Maa's analytical model was used to predict the acoustic absorption performance. Moreover, considering the average sound absorption and total cost of fabricating the samples, RSM-CCD was employed to optimize these samples. In the end, the parallel arrangement of MPP double layer and the combination of MPP with kenaf porous material were tested in order to improve the sound absorption performance. The results showed that the average sound absorption coefficient of the NFRC-MPP sound absorber is 25 % more than that of conventional MPP sound absorbers. The sample with a perforation diameter of 0.70 mm, a panel thickness of 0.90 mm, and an 8 mm distance between the perforations was selected as the optimal sound absorber. The measurement and model data for NFRC-MPP panels do not correspond well. The parallel arrangement of two layers of MPP and the addition of an optimized kenaf layer behind the MPP significantly improved the sound absorption performance in the intended frequency range. The findings of this study, coupled with data available in the literature for other types of biocomposite Micro-Perforated Panel (MPP), strongly indicate that Cork fiber-based MPP exhibits substantial promise for application, either independently or in conjunction with Kenaf materials, as a material for acoustic conditioning. Implementing smart manufacturing techniques for acoustic panels not only enhances engineering noise control efforts but also amplifies the overall effectiveness of Hearing Conservation Programs.

Numerical prediction of hatch spacing effect on porosity appearance in parts manufactured by laser powder bed fusion

Laser powder bed fusion, as a brand-new technology, has significant advantages over the traditional manufacturing process, including design flexibility and short production times. The resulting workpiece characteristics are dramatically impacted by the process parameters variation. In the current study, a 3D thermal model was developed by means of the Ansys Additive software to predict the relationship between the hatch spacing, the porosity occurrence, and the thermal history of the Ti-6Al-4V powder layers using a series of numerical simulations. The numerical results reveal that the hatch distance has a significant impact both on porosity appearance and on thermal history. When the hatch spacing increases, the porosity will also increase which negatively affects the part’s properties. The predicted findings are compared with experimental investigations from literature. Reasonable accordance of the suggested finite element model with the experimental investigations was obtained.

Finite Element Analysis and Experimental Study of Manufacturing Thin-Walled Five-Branched AISI 304 Stainless Steel Tubes with Different Diameters Using a Hydroforming Process.

This study aims to investigate the feasibility of hydroforming (HF) technology coupled with response surface optimization for producing high-quality five-branched AISI 304 stainless steel tubes with different diameters, addressing the shortcomings of traditional manufacturing processes. Conventional techniques often result in issues with multiple consumables, low precision, and subpar performance. The research focuses on finding optimal forming parameters for a more effective process. Initial attempts at a five-branched tube proved unfeasible. Instead, a multi-step forming approach was adopted, starting with the formation of the upper branch tube followed by the two reducing lower branch tubes, a strategy termed "first three, then five". This method, enhanced by a subsequent solid solution treatment, yielded promising results: the combined height of the upper and lower branches was 141.1 mm, with a maximum thinning rate of 26.67%, reduced to 25.33% after trimming. These outcomes met the product usage requirements. Additionally, the study involved designing and developing dies for manufacturing five-branched tubes with different diameters using servo HF equipment. The effectiveness of the multi-step forming process and parameter combinations was confirmed through experimental validation, aligning closely with the FE simulation results. The maximum thinning rate observed in the experiments was 27.60%, indicating that FE simulation and response surface methodology can effectively guide the production of high-quality parts with superior performance.

Optimizing Energy Efficiency of a Twin-Screw Granulation Process in Real-Time Using a Long Short-Term Memory (LSTM) Network.

Traditional pharmaceutical manufacturing processes for solid oral dosage forms can be inefficient and have been known to produce a large amount of undesired product. With the progressing trend of achieving carbon neutrality, there is an impetus to increase the energy efficiency of these manufacturing processes while maintaining the critical quality attributes of the product. One of the important steps in downstream pharmaceutical manufacturing is wet granulation, and within that, twin screw granulation (TSG) is a popular continuous manufacturing technique. In this study, the energy efficiency of the TSG process was maximized by combining a long-term memory (LSTM) model with an optimization algorithm. The LSTM model was trained on time-series process data obtained from the TSG experimental runs. The optimization process, with the objective of maximizing energy efficiency, was performed using a stochastic optimization algorithm, and constraints were enforced on the process parameter design space. Experimental runs at the optimal process parameters were conducted on the TSG equipment with updates occurring at predefined intervals depending on the optimization scenarios. The purpose of these experimental runs was to validate the capability of increasing the overall process energy efficiency when operating at the optimized process parameters. A maximum increase of 27% was obtained between two tested optimization scenarios while maintaining the yield of the granules at the end of the twin-screw granulation process.

Selective immunoglobulin aggregates removal in antivenoms by a simple chromatographic step based on a monolithic stationary phase

Antivenom therapy is a critical intervention for treating the more than 5.000.000 envenomation accidents that occur each year around the world. These immunotherapeutic drugs are mostly produced following techniques developed more than fifty years ago with minor changes. Aggregate content has been described as one of the main causes of early adverse effects after intravenous administration of antivenoms. In this work we propose the introduction of a final polishing step to traditional antivenom manufacturing processes aimed at lowering the aggregate content in the final product. The refinement step proposed in this work is based on the selective capture of immunoglobulin aggregates by a cation exchange monolithic stationary phase. We show that this media can effectively remove aggregates in the final product under isotonic ion-strength and mildly acidic conditions following a negative chromatography strategy, thus making it a useful technique for producing higher quality products.