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This study used friction stir spot welding (FSSW) to weld 1.1‐ and 2.1‐mm AA6061‐T6 sheets at 560, 710, 900, and 1120 rpm at a fixed dwell duration of 5 s. It was determined how much heat was supplied into the FSSW, and the cycle temperature that occurred throughout the FSSW technique was carefully documented. Both the sheet metals and the formed FSSW weldments were subjected to micro and macrostructure analysis, as well as a lap shear test and a hardness test. A scanning electron microscope (SEM) was also used to study the cracked surfaces. A broad variety of rotation rates, ranging from 560 to 1120 rpm, were used to construct error‐free spot joints, as shown by the macroanalysis. The microstructural results may show acceptable mechanical characteristics of FSSW joints, which pertain to the grain refinement of the joints' stir zone (SZ). It was discovered that the optimal welding condition for establishing spot welds with varying thicknesses of thin sheets was 710 rpm. This was achieved with a SZ lap shear resistance of 5020 ± 20 N and hardness of 99 ± 2 HV(100). The temperature fluctuation and Von Mises stress distribution, in the AA6061‐T6 FSSW sheets, were analysed by using ABAQUS/CAE 2021 software. The simulated peak temperature is rather similar to the recorded one. On the other hand, by raising the rotation speed, the peak temperature at the welded joints rose. The friction stir welding (FSW) procedures have an impact on the residual stresses; on the other hand, the welding parameters are influenced by the welding temperature and mixing. [ABSTRACT FROM AUTHOR]

[Objective] Manufacturing accuracy of the steel bridge pier, which is an important part of the suspended mono-rail transit system, determines the erection and installation of track beams, thereby affecting the train smooth running. Therefore, it is necessary to conduct research on it. [Method] Based on the Tourism Special Line Phase I Project, a supporting facility for Wuhan Optics Valley Ecological Corridor Tourism, the process research is conducted in response to the T-shaped structural characteristics of steel bridge piers for suspended monorail transit and combining the design requirements for the manufacturing accuracy of steel bridge piers. The difficulties in the manufacturing process of monorail steel bridge piers are analyzed, and the manufacturing schemes for the steel cap beams are compared and selected. Moreover, the manufacturing process and accuracy control methods of suspended monorail steel bridge piers are systematically expounded. [Result & Conclusion] Through the actual manufacturing of steel bridge piers and the on-site erection and installation of track beams, the distance between the lug plates of the steel cap beams (0-2 mm) and the distance from the cantilever center to the column central line (2-2 mm) can be effectively controlled. After the overall assembly and formation of the steel bridge piers, the distance error between the line connecting the positioning point of the left cap beam pin axis to the center point at the steel column bottom, and the line connecting the positioning point of the right cap beam pin axis to the center point at the steel column bottom is ≤3 mm, and the elevation error between the center of the lug plate and the center of the column is 2 mm, meeting the requirements for the overall assembly and production of steel bridge piers, and realizing the control over the manufacturing accuracy of steel bridge piers. [ABSTRACT FROM AUTHOR]

Copyright of Low-Carbon Materials & Green Construction is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this study, the hybrid simulation approach was adapted using the System Dynamics methodology to characterize continuous and discrete variables in the lightweight brick manufacturing process. Vensim® software was used to evaluate the effects of delays in production flows at specific time intervals, and the continuous impact of variability in the stages of the process was established. The results demonstrate that carrying out a continuous evaluation of the input flow of raw material does not impact the accumulation of material. However, when assessing the monitoring of delay times in a discrete approach, there is a direct impact on batch formation and production capacity fulfilment, resulting in an 8.54 % increase. In conclusion, it is crucial to not only characterize the variables but also to assess their impact using an overarching indicator, such as production capacity, rather than focusing solely on subsequent stages. This comprehensive approach enables strategic decision-making to identify areas of opportunity within the process. [ABSTRACT FROM AUTHOR]

This research describes an online solution for the collection and processing of production data, which are gathered from manufacturing and assembly processes at automotive companies. The solution describes the process for live monitoring of the production health and then evaluation through reports, with the option to generate reports for up to six months. Since the data are located in multiple sources, it is challenging to monitor them live or generate reports on demand. The solution described in this research outlines applications that simplify users' tasks and provide immediate insights into the processes and health of production lines. Research will be divided into three applications which are delivered in one package, which is called Cycle Time Deviation (CTD): (i) workshop application for live monitoring; (ii) for evaluating data older than 24 h, the shift report application; and (iii) for comparing and monitoring the impact of process changes on the analysis, the before and after application—the Plant Improvement Tracker (PIT)—will be presented. The aim of the research is to describe the proposed solution that was implemented in a multinational automotive corporation and to outline the benefits gained from the implementation. [ABSTRACT FROM AUTHOR]

To successfully meet the various requirements of modern storage systems, NAND flash memory should be highly optimized by precisely tuning a huge number of internal operating parameters. Although 3D NAND flash memory succeeds in increasing the capacity of storage systems, its complex architecture and unique error behavior make such optimization a more difficult and time-consuming process during NAND manufacturing. In this paper, we introduce HAIPO, a novel methodology for post-fabrication optimization of NAND flash memory, which is an essential step in the manufacturing process of modern 3D NAND flash memory to simultaneously meet various requirements on reliability, performance, yield, etc. HAIPO is based on simple machine-learning approaches that consist of (i) a lightweight deep-learning (DL) model to generate initial device parameters and (ii) an evolutionary algorithm (EA) to explore device parameters automatically. To more effectively explore device parameters, we introduce three key guidelines for each generation in the EA: (1) domain-specific rules, (2) recent optimization results, and (3) online Bayesian simulation, respectively, to enable quick optimization for a huge number of device parameters within the limited product turnaround time (TAT). In addition, we integrate two optimization modules with HAIPO to improve optimization efficiency even in environments with severe process variation. We demonstrate the feasibility and effectiveness of HAIPO using real 320 3D TLC/QLC NAND flash chips, showing significant performance and reliability improvements by up to 8.8% and 12% on average, respectively, within a quite limited optimization TAT. [ABSTRACT FROM AUTHOR]

Due to a significant reduction in the availability and standard of natural resources, numerous firms are claiming to implement environmentally sustainable practices. This research constructs and validates green variables within the knowledge management (KM) process, drawing on resource‐based views (RBV) and organizational learning theory. It aims to explain how manufacturing firms minimize innovation risk. The author followed a combined methodology of Smart partial least squares structural equation modeling (PLS‐SEM) and fuzzy set qualitative comparative analysis (fsQCA). Primary response data were collected from industry experts and literature studies to develop items for the knowledge aptitude model to decrease innovation risk (KMIR). The mixed variables of the KM and green process were validated through the fsQCA technique. The outcome of PLS‐SEM showed a positive connection between certain green variables to minimize innovation risk. fsQCA examines the combined approach of green implementation and KM practice; the finding indicated significant connections between green variables and the KM process to KMIR. This study can be measured as innovative in the KMIR field, as it has validated and developed its constructs based on primary data. It can help scholars and industry experts acquire a head start in the KMIR field, and this mechanism will assist with the investigation of the green variables and knowledge domain, providing an outline for future studies. [ABSTRACT FROM AUTHOR]

The most durable and acceptable tooth-colored crown material should have good physical, and mechanical properties, chemical resistance, biocompatibility, and aesthetic behavior. The most common materials for artificial crowns are metals, polymers, and ceramics. Ceramics have better mechanical properties than polymers and better aesthetic properties than metals. Still, because of the ceramic excessive brittleness, it is not advisable to manufacture dental crowns by conventional manufacturing methods such as formative and subtractive due to some drawbacks in the previous types of manufacturing such as material wastage, and high complexity that conventional manufacturing methods can’t achieve. So additive manufacturing methods attract the interest of researchers in dental ceramics. The most common additive manufacturing method is vat photopolymerization in which ceramic slurry is accurately prepared and then introduced into a 3d printing machine under the control of the vat photopolymerization process performance parameters then the printed part is introduced into the heat treatment process then we characterize the manufactured part to conform its performance with the required properties of the product. Then cost analysis is done to estimate the cost of manufactured dental crowns. Overall, the design of dental crowns for manufacturing is helpful for dental manufacturers. [ABSTRACT FROM AUTHOR]

［Objective］ Manufacturing accuracy of the steel bridge pier, which is an important part of the suspended monorail transit system, determines the erection and installation of track beams, thereby affecting the train smooth running. Therefore, it is necessary to conduct research on it. ［Method］ Based on the Tourism Special Line Phase I Project, a supporting facility for Wuhan Optics Valley Ecological Corridor Tourism, the process research is conducted in response to the T-shaped structural characteristics of steel bridge piers for suspended monorail transit and combining the design requirements for the manufacturing accuracy of steel bridge piers. The difficulties in the manufacturing process of monorail steel bridge piers are analyzed, and the manufacturing schemes for the steel cap beams are compared and selected. Moreover, the manufacturing process and accuracy control methods of suspended monorail steel bridge piers are systematically expounded. ［Result & Conclusion］ Through the actual manufacturing of steel bridge piers and the on-site erection and installation of track beams, the distance between the lug plates of the steel cap beams (0-2 mm) and the distance from the cantilever center to the column central line (-2-2 mm) can be effectively controlled. After the overall assembly and formation of the steel bridge piers, the distance error between the line connecting the positioning point of the left cap beam pin axis to the center point at the steel column bottom, and the line connecting the positioning point of the right cap beam pin axis to the center point at the steel column bottom is ≤3 mm, and the elevation error between the center of the lug plate and the center of the column is ≤2 mm, meeting the requirements for the overall assembly and production of steel bridge piers, and realizing the control over the manufacturing accuracy of steel bridge piers.

Abstract Applying 3D concrete printing (3DCP) technology to design and manufacturing can create a diverse configuration of the marine landscape. However, this combination of 3D technology and artificial coral products is still in the initial stage of research and application. Therefore, this study introduces a novel design shape model, bridging theory and experimental models. Two innovative design models have been presented, and one has been manufactured and assembled based on the optimal assembling process. The paper aims to propose a design shape model for artificial coral reefs that employs innovative 3D concrete printing technology to create rough surfaces with openings and cavities similar to those found in natural rocks. The proposed design shape for artificial coral reefs, successfully trialed in this research, can be used as a reference model. The procedure for essential works, including drawing, printing, assembling, and some techniques, is helpful for understanding and implementing the works presented in the study. The application of 3D concrete printing technology to an artificial reef fulfills an identified need and plays a crucial role in marine ecosystem restoration and protecting endangered habitats, thereby making a significant social impact while promoting sustainable development in construction. This paper fulfills an identified need to apply 3D concrete printing technology to manufacturing artificial coral reefs.

Abstract The most durable and acceptable tooth-colored crown material should have good physical, and mechanical properties, chemical resistance, biocompatibility, and aesthetic behavior. The most common materials for artificial crowns are metals, polymers, and ceramics. Ceramics have better mechanical properties than polymers and better aesthetic properties than metals. Still, because of the ceramic excessive brittleness, it is not advisable to manufacture dental crowns by conventional manufacturing methods such as formative and subtractive due to some drawbacks in the previous types of manufacturing such as material wastage, and high complexity that conventional manufacturing methods can’t achieve. So additive manufacturing methods attract the interest of researchers in dental ceramics. The most common additive manufacturing method is vat photopolymerization in which ceramic slurry is accurately prepared and then introduced into a 3d printing machine under the control of the vat photopolymerization process performance parameters then the printed part is introduced into the heat treatment process then we characterize the manufactured part to conform its performance with the required properties of the product. Then cost analysis is done to estimate the cost of manufactured dental crowns. Overall, the design of dental crowns for manufacturing is helpful for dental manufacturers. Graphical abstract

Introduction. Dissolving polymeric microneedles are attractive drug delivery system especially for vaccine delivery. Still there are a lot of obstacles in developing scalable manufacturing process of them.Aim. To develop a scalable manufacturing process for producing polymeric dissolving microneedles, which can enable keeping protein activity during manufacturing process.Materials and methods. Microneedles were produced from aqua solution of 20 % w.v. pullulan and 3 % w.v. polyvinyl alcohol by casting in hollow negative polyethylene terephthalate mold. Human serum albumin was chosen as a model protein for this investigation.Results and discussion. There were chosen the mode of mold filling and microneedle drying process, which can guarantee keeping of protein activity during manufacturing process.Conclusion. The designed technology can be easily scaled up and used for producing vaccine drug delivery systems, because it doesn’t contain any restraining processes.

The evolution of structural changes and the textural features during the ripening process of four varieties of Spanish sheep cheese were studied using Magnetic Resonance Imaging (MRI). Specifically, longitudinal (T1) and transverse (T2) relaxation times and apparent diffusion coefficient maps were analyzed. Also, proton density was used to improve the description of the structure of the cheeses. The MRI results displayed important information about cheese matrix structure, associated with different manufacturing processes (industrial vs. traditional), ripening times (RTs, from 2 to 180 days), and geographical origins. A significant interaction between RT and cheese variety related to the variations in physicochemical and textural parameters was found. Linear regression models were developed per the abundant literature. Logarithmic regression models showed the highest R2 when monitoring the dependency on T1 and T2 parameters of water content, water activity, RT, and some texture parameters. Therefore, these results support that MRI is a useful technology to monitor the ripening process, predict textural behavior and physicochemical variables, and characterize the structure of different varieties of sheep cheese. [ABSTRACT FROM AUTHOR]

Background/Objectives: Biological products are emerging as therapeutic management options for intervertebral disc (IVD) degenerative affections and lower back pain. Autologous and allogeneic cell therapy protocols have been clinically implemented for IVD repair. Therein, several manufacturing process design considerations were shown to significantly influence clinical outcomes. The primary objective of this study was to preclinically qualify (chondrogenic potential, safety, resistance to hypoxic and inflammatory stimuli) cryopreserved primary progenitor cells (clinical grade FE002-Disc cells) as a potential cell source in IVD repair/regeneration. The secondary objective of this study was to assess the cell source's delivery potential as cell spheroids (optimization of culture conditions, potential storage solutions). Methods/Results: Safety (soft agar transformation, β-galactosidase, telomerase activity) and functionality-related assays (hypoxic and inflammatory challenge) confirmed that the investigated cellular active substance was highly sustainable in defined cell banking workflows, despite possessing a finite in vitro lifespan. Functionality-related assays confirmed that the retained manufacturing process yielded strong collagen II and glycosaminoglycan (GAG) synthesis in the spheroids in 3-week chondrogenic induction. Then, the impacts of various process parameters (induction medium composition, hypoxic incubation, terminal spheroid lyophilization) were studied to gain insights on their criticality. Finally, an optimal set of technical specifications (use of 10 nM dexamethasone for chondrogenic induction, 2% O2 incubation of spheroids) was set forth, based on specific fine tuning of finished product critical functional attributes. Conclusions: Generally, this study qualified the considered FE002-Disc progenitor cell source for further preclinical investigation based on safety, quality, and functionality datasets. The novelty and significance of this study resided in the establishment of defined processes for preparing fresh, off-the-freezer, or off-the-shelf IVD spheroids using a preclinically qualified allogeneic human cell source. Overall, this study underscored the importance of using robust product components and optimal manufacturing process variants for maximization of finished cell-based formulation quality attributes. [ABSTRACT FROM AUTHOR]

Carbon accounting is critical to manufacturing and achieving a low-carbon transition and lean carbon management. A comprehensive understanding of carbon emissions in manufacturing is essential to calculate a product's carbon footprint accurately. Based on the life cycle assessment (LCA) method, this study divides the whole process of mechanical products from parts to finished products into three stages: parts (P), assembly (A), and testing (T). By decomposing each stage's carbon emission sources and combining each stage's characteristics, a series of corresponding carbon emission accounting models is established. Finally, the three-stage carbon emission model of the manufacturing process of a three-piece ball valve is established, and the validity and feasibility of the proposed model are verified. The results show that raw material consumption, energy consumption, and transportation are the primary sources of carbon emissions in the manufacturing process of three-piece ball valves, accounting for 35.6%, 38.8%, and 17.6%, respectively. The corresponding carbon emissions were 17.854 kgCO2e, 19.405 kgCO2e, and 8.8 kgCO2e, respectively. Through these results, we can provide some theoretical and data support for the low-carbon transformation of manufacturing enterprises as well as some research ideas for realizing low-carbon production through process planning and shop scheduling. [ABSTRACT FROM AUTHOR]

Summary: Boiling, centrifuging and various drying techniques (vacuum freeze‐drying (VFD), vacuum drying (VD), hot‐air drying (HAD) and microwave drying (MWD)) were assessed for their impact on bioactive compounds in Antarctic krill meal. A comparison between the raw and boiling groups revealed a significant degradation and isomerisation of astaxanthin, accompanied by a 1.25‐fold and 1.32‐fold increase in saturated (SFAs) and monounsaturated fatty acids (MUFAs), respectively. Drying was the primary factor responsible for the reduction in phospholipids, α‐tocopherol and polyunsaturated fatty acid (PUFAs), in combination with the increase in thiobarbituric acid‐reactive substances. For different drying methods, it was found that HAD induced severe lipid oxidation. In contrast, the VFD, VD and MWD improved lipid quality, reducing thiobarbituric acid‐reactive substances (TBARS) by 13–22% and increasing phospholipids by 1.08–1.11 times compared to HAD. VD preserved higher levels of bioactive compounds. PLS‐DA analysis identified 13‐cis‐astaxanthin, α‐tocopherol and eleven fatty acids as key indicators for Antarctic krill meal. [ABSTRACT FROM AUTHOR]

The industrial and technological sectors are pushing the boundaries to develop a new class of high-pressure vessels for hydrogen storage that aim to improve durability and and endure harsh operating conditions. This review serves as a strategic foundation for the integration of hydrogen tanks into transport applications while also proposing innovative approaches to designing high-performance composite tanks. The goal is to offer optimized, safe, and cost-effective solutions for the next generation of high-pressure vessels, contributing significantly to energy security through technological advancements. Additionally, the review deepens our understanding of the relationship between microscopic failure mechanisms and the initial failure of reinforced composites. The investigation will focus on the behavior and damaging processes of composite overwrapped pressure vessels (COPVs). Moreover, the review summarizes relevant simulation models in conjunction with experimental work to predict the burst pressure and to continuously monitor the degree of structural weakening and fatigue lifetime of COPVs. Simultaneously, understanding the adverse effects of in-service applications is vital for maintaining structural health during the operational life cycle. [ABSTRACT FROM AUTHOR]

The control of the injection speed in hydraulic injection molding machines is critical to product quality and production efficiency. This paper analyzes servomotor-driven constant pump hydraulic systems in injection molding machines to achieve optimal tracking control of the injection speed. We propose an efficient reinforcement learning (RL)-based approach to achieve fast tracking control of the injection speed within predefined time constraints. First, we construct a precise Markov decision process model that defines the state space, action space, and reward function. Then, we establish a tracking strategy using the Deep Deterministic Policy Gradient RL method, which allows the controller to learn optimal policies by interacting with the environment. Careful attention is also paid to the network architecture and the definition of states/actions to ensure the effectiveness of the proposed method. Extensive numerical results validate the proposed approach and demonstrate accurate and efficient tracking of the injection velocity. The controller's ability to learn and adapt in real time provides a significant advantage over the traditional Proportion Integration Differentiation controller. The proposed method provides a practical solution to the challenge of maintaining accurate control of the injection speed in the manufacturing process. [ABSTRACT FROM AUTHOR]

Nowadays advanced sensing technology enables high-resolution in-process data collection in various systems, known as profile data. These data facilitate in-process monitoring and anomaly detection, which have been extensively studied in recent years. This paper conducts a comprehensive survey on the recent literature for profile modeling and monitoring, including linear profiles, nonlinear profiles, spatial profiles, multi-stage profiles, profile network data, and partially observable profiles, covering techniques such as functional data analysis, tensor analysis, deep learning, etc. By summarizing the developments and challenges associated with the reviewed papers, this paper aims to provide researchers and practitioners with a valuable resource for understanding the latest research advances. [ABSTRACT FROM AUTHOR]

By combining the formability of injection-molded polymers with a wide range of metal options, metal injection molding (MIM) allows for manufacturing metallic components with small dimensions and complex geometries. However, steels produced through this process often exhibit higher porosity compared to conventional methods. This article aims to fill this gap by developing a thermochemical oxynitrocarburizing treatment cycle applied to the austenitic stainless steel Catamold 316L. The developed treatment analyzes the diffusion kinetics, mechanical properties, and metallurgical behavior. The oxynitrocarburizing treatment was carried out at a temperature of 570 °C for varying durations of 30, 60, and 120 min. The findings showed that surface microhardness significantly increased, and corrosion resistance improved due to the ceramic behavior of the Epsolon composite and the formation of magnetite, compared to the sintered material. The study reveals a substantial rise in residual compressive stresses of up to − 2790 MPa on the sample surface. The residual stress values and the elevated surface microhardness are highly beneficial for improving the tribological properties of Catamold 316L steel produced by the MIM process. The study suggests that using ionic oxynitrocarburizing in salt baths presents an alternative to plasma processes for treating Catamold 316L steel, providing improved diffusion of nitrogen and carbon. [ABSTRACT FROM AUTHOR]

The Hayes-Wheelwright Product-Process Matrix (PPM) has historically been a pivotal tool in manufacturing, guiding firms to strategically align product volume and variety with the most optimal production process. Delving into its developmental journey, this research thoroughly examines the PPM's evolution through the industrial eras. From the outset of Industry 2.0, marked by the adoption of Flexible Manufacturing Systems prioritizing mass customization, to the inception of Industry 4.0, characterized by a seamless integration of digital and physical systems with a pronounced focus on tailored products, the matrix has consistently adapted. The main findings of this work underline the imperative to reconceptualize the PPM within the context of Industry 5.0. Building on this foundation, a new model is here proposed to represent the PPM matrix in the Industry 5.0 environment that incorporates creative and technological innovation and the concept of sustainability. This entails a fusion of cutting-edge technological developments, urgent sustainability considerations, and the unyielding deep human insights. The proposed matrix (PPM 5.0) maps each product to the most suitable production process and guides companies in selecting processes that align with sustainable objectives. Furthermore, it provides a flexible foundation designed to readily adapt to evolving market demands, technological advancements, and emerging trends in manufacturing, offering substantial benefits to practitioners and business owners in their strategic design decisions and technology investments. To achieve these insights, a qualitative methodology is employed, grounded in an exhaustive review of the extant literature, thereby ensuring a holistic and informed perspective on the future trajectory of industrial practices. [ABSTRACT FROM AUTHOR]

The expansion of the manufacturing processes network requires algorithms that can enable better planning and optimization of the manufacturing processes. Therefore, in the recent years the developments within the machine-learning (ML) and artificial intelligence (AI) have led to a new terminology, the so-called Industry 4.0. The fastest growth of Industry 4.0 has been encountered in the manufacturing, supply chain, services and products. The machine learning is prone to enable the development of smart supply-chains and manufacturing processes. The present research concerns the suitability and efficiency of the machine learning algorithm for the enhanced supply chain in manufacturing processes. The results show that the machine learning algorithm enables and enhances the efficiency of the manufacturing processes by clustering the machine-tools and increasing the number of manufactured components at the same tool location.

This study investigates the properties of various adhesives and assesses the effects of the coating and drying conditions of aluminum surface treatment agents on adhesion strength and chemical resistance. The adhesion between aluminum and the polymer film is improved through the application of a surface treatment agent to the aluminum surface. This study examines the initial adhesive strength of a manufactured pouch film with respect to the drying temperature and time and evaluates its adhesive strength in the presence of moisture. The results indicate that the residual moisture on the aluminum surface weakens the adhesive strength and significantly affects electrolyte resistance. A noticeable reduction in strength was observed after water spraying, when the drying temperature and time were relatively low during the initial strength measurement. Among the adhesives used for aluminum and CPP lamination, olefin adhesives exhibit less susceptibility to electrolyte effects and have higher adhesive strengths compared to urethane and ester adhesives. Leveraging these characteristics, flexible pouch cells were manufactured and their stability was evaluated. The results confirm that the flexible cells demonstrate excellent stability, exhibiting potential for application in wearable devices. [ABSTRACT FROM AUTHOR]

Industrial automation in the manufacturing environment has revolutionized production and manufacturing in many industries, generating significant improvements in efficiency, quality, and process effectiveness. However, it has also posed challenges related to feedback in manufacturing environment monitoring systems, and increasing the effectiveness, productivity, and quality in industrial production. Feedback systems in the manufacturing environment are fundamental to industrial automation, which is why an application has been developed for the detection of elements in a printed circuit board manufacturing cell. The solution presented in this article proposes implementing a continuous feedback system with the ability to provide real-time information to identify the location of elements in a manufacturing cell and potentially detect anomalies, with the goal of improving the manufacturing process appropriately. [ABSTRACT FROM AUTHOR]

As a subserie of the dental ceramic material family, glass–ceramics are favored for their excellent aesthetic properties. The feasibility of current commercially available dental glass–ceramics applications has been proven, while the assurance and development of more functional properties for them are still being explored. Effective utilization of various modification mechanisms by adjusting the chemical composition and microstructure is essential to improve the mechanical properties, aesthetic properties, and other properties such as biocompatibility of dental restorative materials. Among them, the mechanical properties of restorations should take into account the mechanical properties of glass ceramics and the final restoration (restoration and tooth set) in the mechanical behavior. This paper provides an overview of the chemical composition design, classification of microstructure, property requirements, and strengthening methods applied to dental glass–ceramics, including ion exchange, chain effects, heat treatment modulation, and strengthening mechanisms. In addition, research on traditional hot pressing, subtractive manufacturing, and newly developed additive manufacturing in glass–ceramics are systematically presented. Finally, the tendency of dental glass–ceramics was forecasted by analyzing the relationship between glass–ceramic composition, process, and mechanical properties. [ABSTRACT FROM AUTHOR]

This paper presents a new layered plaster-based material for building purposes. First, a new manufacturing machine was designed to make the elaboration process easier. This manufacturing machine and the way it works are described. In this study, perlite and recycled glass wool (RGW) were added to traditional plaster with the aim of improving the performance of this material. Two series (with and without perlite) and three different layer configurations were developed and assessed. Recycled glass wool layered materials were subjected to both physical and mechanical characterisation to determine their suitability for precast elaboration. The addition of perlite resulted in a significant improvement in flexural strength. Moreover, the addition of RGW also gave rise to extra flexural strength when added. The two-layered samples performed better than the one-layered samples. Mechanical properties increased up to 75% when both the perlite and RGW layers were added. Potential Global Warming Potential (GWP 100) savings were also analysed, reporting up to 49% savings. A complementary cost analysis was performed, aimed at establishing potential savings in production costs; thus, 13–57% potential cost savings were reported. After that, a comparative analysis within the literature was conducted to contextualise the results obtained in this study. [ABSTRACT FROM AUTHOR]

A classical emulsion formulation based on petrolatum and mineral oil as the internal phase with emulsifier wax as a typical topical emulsion cream was investigated for the effect of process parameters on drug product quality and performance attributes. The Initial Design of Experiment (DoE) suggested that an oil phase above 15%, coupled with less than 10% emulsifying wax, resulted in less stable emulsions. Different processing parameters such as homogenization speed, duration, cooling rate, and final temperature showed minimal influence on properties and failed to improve stability. The final DoE suggested that the optimal emulsion stability was achieved by introducing a holding period midway through the cooling stage after solvent addition. Within the studied holding temperature range (25–35 °C), a higher holding temperature correlated with increased emulsion stability. However, the application of shear during the holding period, using a paddle mixer, adversely affected stability by disrupting the emulsion microstructure. IVRT studies revealed that the release of lidocaine was higher in the most stable emulsion produced at a holding temperature of 35 °C compared to the least stable emulsion produced at a holding temperature of 25 °C. This suggests that a holding temperature of 35 °C improves both the stability and active release performance. It appears that a slightly higher holding temperature, 35 °C, allows a more flexible and stable emulsifying agent film around the droplets facilitating stabilization of the emulsion. This study offers valuable insights into the relationship between process parameters at various stages of manufacture, microstructure, and various quality attributes of emulsion cream systems. The knowledge gained will facilitate improved design and optimization of robust manufacturing processes, ensuring the production of the formulations with the desired critical quality attributes. [ABSTRACT FROM AUTHOR]

Modern electric motors developed for the automotive industry have an ever higher power density with a relatively compact size. Among the various existing solutions to improve torque and power density, a reduction in the dimensions of the end-windings has been explored, aiming to decrease volume, weight, and losses. However, more compact end-windings often lead to complex shapes of the conductors, especially when preformed hairpin windings are considered. The rectangular cross-section of hairpin conductors makes them prone to deviating out of the bending plane during the forming process. This phenomenon, known as torsional–flexural instability, is influenced by the specific aspect ratio of the cross-section dimensions and the bending direction. This study focuses on understanding this instability phenomenon, aiming to identify a potential threshold of the cross-section aspect ratio. The instability makes it difficult to predict the final geometry, potentially compromising the compliance with the geometric tolerances. A finite element model is developed to analyse a single planar bend in a hairpin conductor. Various cross-section dimensions with different aspect ratios are simulated identifying those that experience instability. Moreover, an experimental campaign is conducted to confirm the occurrence of instability by testing the same single planar bending. The experimental data obtained are used to validate the finite element model for the tested dimensions. The aim is to provide designers with a useful tool to select hairpin geometries that are more suitable for the folding process, contributing to successful assembly and improving the overall design process of preformed hairpin conductors. [ABSTRACT FROM AUTHOR]

Copyright of Automobile Technology & Material is the property of Automobile Technology & Material Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Tieguanyin (TGY) is renowned for its distinctive “Yin Rhyme” flavor. To elucidate the underlying formation mechanism, we conducted sensory evaluations, electronic tongue analysis, and widely-targeted metabolomics. Our sensory evaluations and electronic tongue results indicated that TGY exhibits a thick and mellow taste profile, contributing to the “Yin Rhyme” flavor. Metabolomics analysis of tea products revealed that TGY shows significantly higher concentrations of umami substances (L-glutamate, L-theanine) and bitter substances (valine, catechins) compared to Jinguanyin (JGY). Additionally, metabolomic analysis during different oolong tea processing stages revealed significant differences in 21 substances, including L-glutamate, L-theanine, valine, and catechins, between fresh leaves of both varieties. These substances exhibited distinct fluctuation patterns during processing, indicating that the cultivar plays a crucial role in developing the “Yin Rhyme” flavor, which was enhanced throughout processing. This study provides a theoretical foundation for understanding the formation of the unique “Yin Rhyme” flavor of TGY.

Industrial design change task refers to the task resulting from industrial design schemes changing processes due to manufacturing needs in complex product development. In order to make full use of the experience generated in design design change, this paper proposes an industrial design change task allocation method based on implementation intention. Based on the action stage model, the connotation of the implementation intention of industrial design tasks is proposed. Based on the state of the design change, the design team and design task model are constructed through the Extenics theory. A quantitative model of implementation intention and an evaluation method for generalization are constructed. The similarity between the design tasks and the support of the design team for the design tasks are quantified and calculated by the complex network. For change design tasks other than design activities, the collaborative filtering algorithm is improved to achieve design team recommendations based on task similarity. In the process of collaborative filtering, the relationship between tasks is considered, and the time loss caused by the propagation of tasks among different teams is evaluated to improve the effectiveness of the task allocation scheme. Take the change in the internal facility manufacturing requirements of the intelligent cabin as an example. Compared to the design process before applying this method, the task load of design teams was reduced by 18.74 %, which proved this method can support industry design change problems.

[Objective] Due to the diverse components, complex internal structures, and significant deformation risks of straddle monorail beam-switching turnout, issues such as improper component installation, welding-induced thermal deformation, and stress concentration may arise during the manufacturing process, leading the products failure in meeting the required design quality. Therefore, it is necessary to conduct a systematic study on the manufacturing process of the straddle monorail beam-switching turnout. [Method] The overview of straddle monorail beam-switching turnout is presented. The structural characteristics and material properties of the straddle monorail beam-switching turnout are analyzed. Targeted research is conducted on manufacturing challenges, process route planning, process design, fixture design, and other aspects. A set of manufacturing processes suitable for the straddle monorail beam-switching turnout is proposed, and the implementation effects of the proposed manufacturing process are verified. [Result & Conclusion] The adopted fixture frame and welding process can control the dimensional accuracy of each component within the design requirements. Coupled with vibration aging treatment, it effectively improves the distribution state of structural stress and reduces the risk of residual deformation after welding, so as to ensure that the linear dimensions of the turnout meet the standards after assembly.

Carbon Fibers (CFs) are usually derived from a polyacrylonitrile precursor during composite fiber production. Due to high-temperature needs, the CF composite manufacturing process is considerably energy-consuming and costly. Hence, energy intensity prediction is required. Energy intensity is predicted by the prevailing research techniques; however, it is not predicted accurately. Thus, a Limit Jordan Deep Recurrent Neural Network (LJDRNN)-centric energy intensity prediction was proposed for accurately predicting the energy intensity. Primarily, the material values and processes are detected. Next, for the determined values, pre-processing is done; in addition, the components are extracted from the input values. Then, by employing the Linear Interpolated Honey Badger Optimization (LIHBO), the optimal components are selected. Next, LJDRNN predicts the energy intensity by deploying the optimal components. The proposed LJDRNN achieved an accuracy of 98.32%, outperforming the JRNN (92.10%), RNN (87%), ANN (78%), and CNN (86%), thus demonstrating its superiority in energy intensity prediction. Grounded on the performance measures, the proposed technique’s performance is weighed against the prevailing research techniques where the proposed system attained enhanced performance when analogized to the prevailing methodologies. This study is of high significance to CF producers, offering a robust tool to predict and manage energy consumption effectively. By enabling more precise energy intensity forecasting, the proposed method supports producers in optimizing their manufacturing processes, reducing energy costs, and aligning with sustainable production goals, ultimately driving greater operational efficiency and competitiveness in the CF industry.

This study compares conventional turning (CT) and ultrasonic vibration-assisted turning (UVAT) in machining hardened AISI 52100 steel (62 HRC) with a PVDcoated TiAlSiN carbide tool. UVAT experiments, utilizing an ultrasonic frequency of 20 kHz and vibration amplitude of 20 µm, varied the cutting speed, feed, and depth of cut. Remarkably, UVAT reduced tool wear, extending tool longevity. Surprisingly, power consumption showed no significant differences between CT and UVAT. Mathematical models based on experimental data highlight the substantial impact of the cutting speed on tool wear, followed closely by the depth of cut. For power consumption, the depth of cut took precedence, with the cutting speed and feed rate playing pronounced roles in UVAT. This emphasizes the potential for further research on machinability, particularly exploring different vibration directions on the tool in feed, tangential, and radial aspects. [ABSTRACT FROM AUTHOR]

Amidst uncertainty, decision-making in manufacturing becomes a central focus due to its complexity. This study explores complex transportation constraints and uses novel ways to guide manufacturers. The Multi-objective Stochastic Linear Fractional Transportation Problem (MOSLFTP) is a crucial tool for managing supply chains, manufacturing operations, energy distribution, emergency routes, healthcare logistics, and other related areas. It adeptly addresses uncertainty, transforming efficiency and effectiveness in several domains. Stochastic programming is the process of converting theoretical probabilities into concrete certainties. The artistic compromise programming technique acts as a proficient mediator, reconciling opposing objectives and enabling equitable decision-making. This novel approach also addresses the Multi-objective Stochastic Linear plus Linear Fractional Transportation Problem (MOSLPLFTP), which involves two interconnected issues. The effectiveness of these principles is clearly shown with the help of the LINGO® 18 optimization solver. This study uses a ranking method to compare the similar methods to solve the current problems. A meticulously designed example acts as a significant achievement, shedding light on our method in a practical setting. It serves as a distinctive instrument, leading manufacturers through the maze of uncertainty and assisting them in determining the most advantageous course of action. This journey involves subtle interactions between complexity and simplicity, uncertainty is overcome by decisiveness, and invention is predominant. [ABSTRACT FROM AUTHOR]

This study aims to analyze the effect of the curing temperature of nano-reinforcements during the manufacturing process on the mechanical properties of composites involving graphene (GNP), carbon nanofibers (CNFs), and a hybrid mixture of these two nanoparticles. In this context, the type of nanoparticles, their content, their type of resin, and their hybridization were considered. The results showed that both nanoparticles increased the viscosity of the resin suspension, with an increase of between 16.3% and 38.2% for GNP nanoparticles and 45.4% and 74% for CNFs depending on the type of resin. Shrinkage was also affected by the addition of nanoparticles, as the highest results were obtained with GNP nanoparticles, with a 91% increase compared with the neat resin, and the lowest results were obtained with CNFs, with a decrease of 77% compared with the neat resin. A curing temperature of 5 °C promoted the best bending and hardness performance for all composites regardless of the type of resin and reinforcement used, with improvements of up to 24.8% for GNP nanoparticles and 13.52% for CNFs compared with the neat resin at 20 °C. Hybridization led to further improvements in bending properties and hardness compared with single-reinforcement composites due to a synergistic effect. However, the effectiveness of hybridization depends on the type of resin. [ABSTRACT FROM AUTHOR]

The objective of this study was to evaluate the microbiological properties of commercially available traditional Korean salted shrimp (Saeu-jeot) and to analyze the effects of saltwater immersion and ultraviolet (UV) irradiation on the reduction of Staphylococcus aureus in Saeu-jeot. A microbiological analysis was conducted across 56 commercially available Saeu-jeot samples from the Korean, Chinese, and Vietnamese markets. The microbiological analysis revealed no presence of Escherichia coli, coliforms, or Vibrio parahaemolyticus in any commercial samples. The total viable count and S. aureus were 3.8 ± 0.4 and 0.6 ± 0.3 log CFU/g, respectively. An investigation of the procedures conducted on Saeu-jeot samples at various production stages by Hazard Analysis Critical Control Point (HACCP)-certified companies demonstrated the substantial relevance of the raw material (tiny shrimp) on S. aureus counts. In order to reduce S. aureus in Saeu-jeot, saltwater immersion and UV irradiation treatments were applied, which reduced the S. aureus counts by 1.4 log CFU/g and 0.3 log CFU/g, respectively, and S. aureus's efficacy was limited to the food's surface. These results suggest that a co-treatment of saltwater immersion and UV irradiation could be effective in reducing S. aureus. The maintenance of hygienic handling and cleanliness are essential in the modern manufacturing processes of Saeu-jeot. [ABSTRACT FROM AUTHOR]

A Novel Technique is proposed in this investigation called Double Stage Friction Stir Spot Extrusion Welding (DSFSSEW). It is carried out in two stages by using a pin-shoulder tool in step 1 and a pin-less tool in step 2 to investigate the joint strength of the AA1050 sheet. The advantage of this new double-stage FSSEW technique compared to the classical FSSW led to the elimination of the keyhole, which is an intrinsic flaw of the Friction Stir Spot Welding (FSSW) process resulting in higher mechanical joint properties. The impact of the plunge depth and tool revolving speed on the characteristics of the bond was investigated. The height of the extruded aluminium was increased by increasing the tool rotation speed and the plunging depth which was the effective variable. The joint strength was increased in step 2. The two sheets are bonding together at a line of the interface by a mechanical interlock formed by a continuous metal flow of aluminium extrusion that is free of flaws. There were two mechanisms of failure in the studied samples: cleavage of the aluminium metal at the tool trace and shearing of the extruded aluminium, respectively. The suggested method is novel and has a great potential for future investigation, this work might pave the way for studies of welding with additional alloys, both similar and dissimilar to those already studied. [ABSTRACT FROM AUTHOR]

Biofoam products have attracted considerable attention lately because there is a growing demand for green/sustainable products. To this end, various biobased foams have either been developed or are currently in development, e.g., bio-based polyurethanes (PUs), polylactic acid (PLA), starch, and polyhydroxyalkanotates (PHAs). Indeed, significant progress has been made; however, challenges still persist, for example, biobased foam products have poor processability, inferior compatibility, thermal and strength properties. In this review, we focus on five biofoam products: namely bio-based PUs, PLA, starch, PHAs, and cellulose biofoam products, along with their properties and performance, as well as their manufacturing processes. Further efforts are still needed to unlock the full potential of these bio-based products and meet the goal of complementing and gradually replacing some of their fossil-based counterparts. Finally, the challenges, as well as arising opportunities of future research directions are discussed. [ABSTRACT FROM AUTHOR]

Cylindrical lithium-ion batteries are widely used in consumer electronics, electric vehicles, and energy storage applications. However, safety risks due to thermal runaway-induced fire and explosions have prompted the need for safety analysis methodologies. Though cylindrical batteries often incorporate safety devices, the safety of the battery also depends on its design and manufacturing processes. This study conducts a design and process failure mode and effect analysis (DFMEA and PFMEA) for the design and manufacturing of cylindrical lithium-ion batteries, with a focus on battery safety. [ABSTRACT FROM AUTHOR]

The reflected power function distribution (RPFD) has increasing importance in practical life due to its application in diversified fields of life. Organisations often face difficulty monitoring operations to identify and remove errors during production. That is why there is a need to introduce control charts that effectively monitor the processes, mainly when the number of errors follows RPFD and the manufacturing process is in control. The current study suggested memory-based control charts as a solution to the problem. The control charts are based on the estimation methods and play a remarkable role in enhancing the machine process reliability. The parameters of RPFD are evaluated through the percentile estimator (PE) and modified maximum likelihood estimator methods (MMLM). Further, we create memory-based control charts, i.e., hybrid exponentially weighted moving average (HEWMA) and extended exponentially weighted moving average (EEWMA), using the PE and MMLM. The findings reflect that HEWMA control charts based on PE provide a better result in estimating the defects. The implications of the study will be helpful for practitioners and policy makers from reliability engineering, management sciences, and statisticians. [ABSTRACT FROM AUTHOR]

Friction is a pivotal factor influencing wrinkle formation in composite material shaping processes, particularly in novel thermoplastic composites like polyetheretherketone (PEEK) and low-melting polyaryletherketone (LM-PAEK) matrices reinforced with unidirectional carbon fibers. The aerospace sector lacks comprehensive data on the behavior of these materials under forming conditions, motivating this study's objective to characterize the interlaminar friction of such high-performance thermoplastic composites across diverse temperatures and forming parameters. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) were employed to analyze the thermomechanical behaviors of PEEK and LM-PAEK. These data guided friction tests covering room-to-forming temperatures. Horizontal pull-out fixed-plies tests were conducted to determine the friction coefficient and shear stress dependency concerning temperature, pressure, and pulling rate. Below the melting point, both materials adhered to Coulomb's law for friction behavior. However, above the melting temperature, PEEK's friction decreased while LM-PAEK's friction increased with rising temperatures. These findings highlight the distinct responses of these materials to temperature variations, pulling rates, and pressures, emphasizing the need for further research on friction characterization around glass transition and melting temperatures to enhance our understanding of this phenomenon. [ABSTRACT FROM AUTHOR]

Improving the quality of the manufacturing process is an important goal of professional technicians. This study systematically explored the key success factors in the product-forming ability and visual optimization of 3D forming in the clay-shaping process through actual manufacturing and implementation. The purpose of this study was to identify the forming technology and technical indicators that can successfully achieve a high degree of completeness and maturity in the manufacturing process, increasing the shaping performance of the end products and enabling the evaluation of optimization. In this study, we evaluated soil shaping, material use, the manufacturing process, and product forming. The key success factors were studied and analyzed via expert interviews. The research and analysis were summarized into 4 dimensions with 48 sub-dimensions. These included: (1) soil material, with 12 sub-dimensions; (2) the design concept, with 12 sub-dimensions; (3) the prototype process, comprising 12 sub-dimensions; and (4) kiln firing, comprising 12 sub-facets. A research team composed of 13 scholars and experts conducted three surveys on the evaluation dimensions of the Delphi technique. They analyzed the mean (M), mode (Mo), and standard deviation (SD) of various dimension options. They used the Kolmogorov–Smirnov one-sample test research and analysis to analyze the appropriateness and consistency of the survey results. The results of this study showed that 15 sub-dimensions met the appropriateness and consistency conditions, based on which 15 key factors were established. The results of this study provide reference indicators for the manufacturing process, forming process, and forming technology optimization quality for follow-up research. [ABSTRACT FROM AUTHOR]

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Abstract As a subserie of the dental ceramic material family, glass–ceramics are favored for their excellent aesthetic properties. The feasibility of current commercially available dental glass–ceramics applications has been proven, while the assurance and development of more functional properties for them are still being explored. Effective utilization of various modification mechanisms by adjusting the chemical composition and microstructure is essential to improve the mechanical properties, aesthetic properties, and other properties such as biocompatibility of dental restorative materials. Among them, the mechanical properties of restorations should take into account the mechanical properties of glass ceramics and the final restoration (restoration and tooth set) in the mechanical behavior. This paper provides an overview of the chemical composition design, classification of microstructure, property requirements, and strengthening methods applied to dental glass–ceramics, including ion exchange, chain effects, heat treatment modulation, and strengthening mechanisms. In addition, research on traditional hot pressing, subtractive manufacturing, and newly developed additive manufacturing in glass–ceramics are systematically presented. Finally, the tendency of dental glass–ceramics was forecasted by analyzing the relationship between glass–ceramic composition, process, and mechanical properties.

In the film manufacturing process, process variables, such as temperature and pressure, are measured and controlled to manage the film properties, such as thickness and optical characteristics. Each film property is regulated by the product specifications, and having all film properties adhere to the specifications is important. In this study, soft sensors were utilized to predict film properties and the importance of the variables that affect the film property variations for each soft sensor was calculated. Different process states were considered in the soft sensor modeling, a different soft sensor was constructed for each state, and soft sensor models with film property prediction accuracies higher than those of the conventional ones were achieved. The importance of the process variables was calculated by adding random variables to identify the truly important variables. The appropriate process variables were confirmed to be detected from the perspective of on-site process engineers. This study contributes to the application of soft sensors in film manufacturing processes.

Most electrical machine design optimization processes do not include constraints imposed during manufacture. Ignoring cutting tolerance when optimizing a machine, for example, can result in a machine who’s performance is susceptible to manufacturing defects. Ideally, design of electrical machines for high-volume production should account for the impact of manufacturing tolerance, material variation and material processing. This ‘robust’ design ensures that models realistically predict achievable performance, thereby mitigating the risk of obsolescence during mass production. This paper introduces a procedure to address the influence of lamination punching in the robust design of electrical machines. A six-phase segmented switch reluctance motor is simulated with a multi-layer finite element model to account for the effects of punching on the magnetic characteristics of the electrical steel laminations. Additionally, to enhance the accuracy of finite element model, a geometry-dependent excitation and control circuit is integrated with the finite element model. The results demonstrate that the optimization model presented increases the likely torque output of a machine built with a normal distribution of manufacturing errors.