Industrial Manufacturing Applications Research Articles

High-Precision Chromatic Confocal Technologies: A Review

Chromatic confocal technology is widely used for precise, steady, and efficient displacement measurement in many industrial fields. It employs the confocal and dispersion principles to encode axial positions with the wavelengths of the reflected broad spectrum. The typical chromatic confocal sensor includes a light source, a dispersion objective, conjugate pinholes, and a spectral detection device. This study offers an overview of the current research on chromatic confocal technology. Because of its good performance in displacement detection, chromatic confocal technology has been widely used in contour measurement, biomedical imaging, and thickness measurements, as part of global and professional research. Due to its structural flexibility, it is also easily integrated into industrial equipment for in-machine and online profile measurements. It holds significant potential for future applications in industrial manufacturing and scientific research. However, there are also some challenges to be explored in terms of the broadband light source, dispersive optics design, and the balance between speed and accuracy in signal processing.

Optimized design of macro‐microreactor for scale‐up of liquid–liquid chemical processes

AbstractThe scale‐up of microreactor‐based flow chemical process represents a grand challenge in chemical engineering. The small characteristic size (<1000 μm) of a typical microreactor leads to not only microscale effect (process intensification) but also low throughput. Here, we report macro‐microreactor to achieve scale‐up of liquid–liquid chemical operation with process intensification. By incorporating the designed internals based on computational fluid dynamics, the characteristic size of the macro‐microreactor is expanded into 3000–4000 μm. The optimized design of macro‐microreactor with helical‐shaped internal exhibits both similar or even stronger microscale effect and high throughput in contrast to the typical microreactor. For the liquid–liquid chemical process, seven times higher mass transfer coefficient and about half reduction of the pressure drop are realized. These macro‐microreactors would find further applications in industrial chemical manufacturing.

A Meta-Analysis Review: Nanoparticles as a Gateway to Optimized Boiling Surfaces.

Pool boiling is essential in many industrial manufacturing applications. In addition, it can become critical in the journey towards improving energy generation efficiency and accomplishing the goal of net-zero carbon emissions by 2050 via new or traditional power generation applications. The effectiveness of boiling is governed by the bubble cycle. The chemistry and topographical features of the surface being heated have been found to highly impact the boiling performance, such as in the case of pool boiling enhancement when employing hydrophilic and hydrophobic surfaces via nano/micro heater surface modification. Nevertheless, it is questionable how feasible it is to create these surfaces for large-scale applications due to their manufacturing and maintenance cost and complexity. The current work assesses whether the use of nanoparticles in traditional coolants could potentially unlock the mass production of optimised heating surface modification through a metadata literature review analysis. It was discovered that self-assembled layers created as a result of the deposition of nanoparticles in coolants undergoing pool boiling seem to behave most similarly to manufactured hydrophilic surfaces. The creation of enhanced patterned-heat transfer surfaces is shown to be possible via the use of a combination of different nanoparticle suspensions in coolants.

Enhancing Efficiency and Energy Optimization: Data-Driven Solutions in Process Industrial Manufacturing

This paper reviews the current state of research in data analytics and machine learning techniques, focusing on their applications in process industrial manufacturing, particularly in control and optimization. Key areas for future research include selection and transfer learning for process monitoring, addressing time-varying characteristics, and enhancing data-driven optimal control with domain-specific knowledge. Additionally, the paper explores reinforcement learning techniques and robust optimization, including distributional robust optimization, for high-level decision-making. Emphasizing the importance of historical knowledge of plants and processes, this paper aims to identify knowledge gaps and pave the way for future research in data-driven strategies for process industries, with a particular emphasis on energy efficiency and optimization.

Tribological properties of pickering emulsion constructed with ZnO nanoparticles modified by magnetic surfactants

To fulfill the requirements of long-term stable lubrication and corrosion protection, conventional industrial emulsion lubricants often involve complex formulations with multiple components, posing challenges in terms of preparation, recycling, and potential environmental impact. In order to address the problems, a Pickering emulsion with a simple composition and excellent anti-corrosion properties is prepared by incorporating magnetic surfactant ((C18H37)2N+(CH3)2[CeCl4]-) modified ZnO nanoparticles as a multifunctional additive into colza oil and water. The results demonstrate that Pickering emulsions exhibit excellent stability. Moreover, their magnetic responsiveness makes them promising candidates for intelligent lubricants. Furthermore, effective recycling and sustainability are achieved through reversible emulsification and demulsification. Tribological test results reveal that the addition of modified ZnO enhances the emulsions’ anti-friction and anti-wear properties due to nanoparticle rolling and repairing effects, generation of tribofilms, and deposition of ZnO nanoparticles. We anticipate that the Pickering emulsion could find widespread applications in various sectors, including metalworking and industrial manufacturing, owing to its uncomplicated composition, environmentally friendly nature, excellent anti-corrosion capabilities, and superior lubricating properties.

Comparison of Flavonoid Content, Antioxidant Potential, Acetylcholinesterase Inhibition Activity and Volatile Components Based on HS-SPME-GC-MS of Different Parts from Matteuccia struthiopteris (L.) Todaro.

Matteuccia struthiopteris is one of the most globally consumed edible ferns and widely used in folk medicine. Reports mainly focus on young fronds and the rhizome which are common edible medicinal parts. However, there are few detailed reports on other parts. Therefore, the volatile components of different parts based on HS-SPME-GC-MS were identified, and total flavonoid contents, antioxidant activities and acetylcholinesterase inhibitory activities were compared in order to reveal the difference of volatile components and potential medicinal value of different parts. The results showed that total flavonoid contents, antioxidant activities and volatile components of different parts were obviously different. The crozier exhibited the strongest antioxidant activities, but only underground parts exhibited a dose-dependent inhibition potential against AChE. Common volatile compounds were furfural and 2-furancarboxaldehyde, 5-methyl-. In addition, it was found that some volatile components from adventitious root, trophophyll, sporophyll and petiole were important ingredients in food, cosmetics, industrial manufacturing and pharmaceutical applications.

Challenges and opportunities of automated data pipelines for environmental sustainability applications in industrial manufacturing

Energy efficiency analyses and life cycle assessments are two examples of data-driven applications focused on environmental sustainability in the industrial manufacturing context. Both use methodologies based on aggregating operational data, extracted from multiple data sources along a value chain. However, the possibility to source, utilize, and share data is often obstructed by heterogeneous or non-transparent data operations across organizations, as well as poor availability of digital interfaces for data collection. In practice, the underlying application processes lack fidelity and granularity, as a trade-of to simplify the modeling and data collection tasks. Therefore, new opportunities arise for automated workflows on data collection (data pipelines) as a relevant component of every digital transformation strategy. This study reflects on the challenges experienced by two industrial actors collecting operational data for an energy efficiency analysis and a Life-cycle Assessment (LCA), each with a different manufacturing context and architectural approach. Finally, it presents the opportunities for new technologies at affordable costs that potentially ease the development and operation of data pipelines to solve such challenges.

Recent research on the physicochemical properties and biological activities of quinones and their practical applications: a comprehensive review.

Quinones represent a class of crude organic compounds ubiquitously distributed in nature. Their distinctive quinone-type structure confers upon them unique properties and applications. Quinones demonstrate significant biological activities, including antioxidant, antimicrobial, and antitumor properties. Additionally, they demonstrate noteworthy physicochemical characteristics, including excellent dyeing properties and stability. Given their diverse qualities, quinones hold significant promise for applications in industrial manufacturing, healthcare, and food production, thus garnering considerable attention in recent years. While there is a growing body of research on quinones, the existing literature falls short of providing a comprehensive review encompassing recent advancements in this field along with established knowledge. This paper offers a comprehensive review of research progress for quinones, encompassing structural classification, source synthesis, extraction methods, properties, functions, and specific applications. It serves as a reference and theoretical foundation for the further development and utilization of quinones.

UPGRADING AND SURFACE COATING OF EGYPTIAN WHITE SAND WITH POLYMERS AND SILANES

Egypt is endowed with huge reserves of filler minerals, such as silica sand which form approximately 95% of the Earth's crust. The silica sand industry is used in many fields, such as pharmaceutical practices, chemicals, glass, ceramics, electronics, and photovoltaic industries. The aim of this study is to remove impurities from silica sand and apply surface modification processes to enhance its value for various industrial manufacturing applications. Various processing techniques, including classification, attrition scrubbing, magnetic separation, ultra-fine grinding and surface modification, were conducted throughout the study. The results indicated that attrition scrubbing to the classified size fraction of -0.6 + 0.1 mm was capable of reducing the iron concentration from 0.068% to 0.045%. Utilizing the Box-Behnken design, the optimal conditions for magnetic separation were identified, resulting in a decrease in iron content down to 0.012%. Simultaneously, the silica content increased from 99.05% to 99.76%. The results of ultrafine grinding using an attritor mill revealed that a grinding time of 2 hours is sufficient to reach a size suitable for the coating process. Surface modification of the produced ultrafine sand was conducted using polymers and silanes. The treated sand was characterized using SEM, zeta potential, adsorption density, and FTIR measurements. Notably, hydrophobicity increased, accompanied by an increase in particle size. Simultaneously, the surface becomes flatter, indicating the formation of a thin layer. Consequently, the coated sand proved to be a satisfactory material that met the criteria to be used as a filler in coating and paints.

Digital twin: Application and prospect

Digital twin (DT) is considered one of the most promising enabling technologies for achieving intelligent manufacturing and Industry 4.0. The key characteristic of DT is the seamless integration between the cyber and physical spaces. The significance of DT is increasingly recognized by the academic and industrial communities. To understand the development and application of DT in industry, this paper provides an in-depth review of the research status of key components of DT, the current state of DT development, and its major applications in aerospace, industrial manufacturing and smart cities. This paper also outlines some potential directions for future work and discusses current challenges. First, the integration of machine learning algorithms with digital twins can enable more complex data analysis, decision-making, and predictive capabilities. Second, the application of blockchain technology in digital twin ecosystems can increase the potential for secure and transparent data sharing and collaboration. Finally, the expansion of the scope of digital twins can achieve environmental sustainability.

Digital-twin deep dynamic camera position optimisation for the V-STARS photogrammetry system based on 3D reconstruction

ABSTRACT Photogrammetry systems are widely used in industrial manufacturing applications as an assistance measurement tool. Not only does it provide high-precision feedback for assembly process inspection and product quality assessment, but also it can improve the flexibility and robustness of manufacturing systems and production lines. However, with growing global competition and demands, companies are forced to enhance production efficiency, shorten production lifecycle and increase product variety by incorporating reconfigurable factory design that can meet challenging timeline and requirements. Although dynamic facility layout is widely investigated, the position selection for the photogrammetry system in dynamic manufacturing environment is usually overlooked. In this paper, dynamic layout of the V-STARS photogrammetry system is investigated and optimised in a digital-twin environment using deep reinforcement learning. The learning objectives are derived from the field of view (FoV) evaluation from point clouds 3D reconstruction, and collision detection from the digital twin simulated in Visual Components. The application feasibility of the proposed dynamic layout optimisation of the V-STARS photogrammetry system is verified with a real world industrial application.

High-accuracy transverse translation velocimeter enabled by OAM-assisted dual-point transverse Doppler effect

Laser Doppler velocimetry has developed as a powerful enabling technology within a myriad of realistic scenarios. While existing toolkits that exploit optical vortex allow access to longitudinal linear velocimetry and/or transverse rotational velocimetry of a motion object, achieving high-accuracy transverse translation velocimetry is still an open challenge. Here, we overcome this restriction by breaking the prevailing single-point metrological paradigm, instead employing dual-point transverse Doppler effect of customized orbital-angular-momentum (OAM) light fields as our pathway. We show that the dual-point transverse Doppler shifts can be generated and detected in a single velocimetry geometry for the first time, thereby enabling the determination of arbitrary transverse translation velocity. In particular, we demonstrate that the limited frequency resolution causes the velocimetry deviation and increasing the sampling duration can thus effectively improve velocimetry accuracy. As a consequence, a high-accuracy transverse translation velocimeter with a relative error below 0.08% has been well-established. Our validated findings not only provide a profound insight into the interaction of OAM with macroscopic motion object but also may find potential applications in clinical medicine, astronomical observation, and industrial manufacturing.

Long-infrared dual-wavelength linear-polarization-multiplexed confocal metalens based on an all-silicon dielectric.

The metalens has vast applications in biomedicine and industrial manufacturing due to their ultrathin structure and vital ability to manipulate the properties of light waves for long-infrared systems. However, it is difficult for metalens to achieve the confocal function with high focusing efficiency, wide wavelength bandwidth, and low structural complexity. Here, we propose and experimentally demonstrate an all-silicon dielectric metalens composed of arrays of minimalist meta-atoms with a single rectangular nanopillar arranged on a periodic square lattice substrate, which realizes the confocal function of the orthogonal-linear-polarized light with wavelengths of 10.6 µm and 9.3 µm, with focusing efficiencies of 64.94% and 60.03%, respectively. Also, it reveals nearly the diffraction-limited focusing performance. In addition, the metalens can realize precise long-infrared thermal imaging. Moreover, the proposed metalens is compatible with the standard complementary metal oxide semiconductor processes, which can effectively reduce the manufacturing cost and provide a feasible solution for developing planar integrated multifunctional micro-nanophotonic devices in the long-infrared field.

Sequence Analysis and Biochemical Characteristics of Two Non-specific Lipid Transfer Proteins from Tartary Buckwheat Seeds.

Plant non-specific lipid transfer proteins (nsLTPs) play an important role in plant resistance to various stresses, and show potential applications in agriculture, industrial manufacturing, and medicine. In addition, as more and more nsLTPs are identified as allergens, nsLTPs have attracted interest due to their allergenicity. Two nsLTPs from Tartary buckwheat have been isolated and identified. There is a need to study their biochemical characteristics and allergenicity. The study aims to investigate the biochemical characteristics of two nsLTPs from Tartary buckwheat seeds and evaluate their potential allergenicity. Two nsLTPs derived from Tartary buckwheat, namely FtLTP1a and FtLTP1b, were produced by gene cloning, expression, and purification. Sequence analysis and biochemical characteristics of the proteins, including lipid binding ability, α-amylase inhibition activity, antifungal activity, and allergenic activity, were investigated. High-purity recombinant FtLTP1a and FtLTP1b were obtained. FtLTP1a and FtLTP1b exhibited similar lipid binding and antifungal properties. Only FtLTP1b showed weak inhibitory activity against α-amylase. FtLTP1b could specifically bind IgE in the serum allergic to buckwheat and cross-react with pollen (w6). FtLTP1b is a novel allergenic member of the lipid-transfer protein 1 family found in Tartary buckwheat.

An ultra-high sensitivity methane gas sensor based on Vernier effect in two parallel optical fiber Sagnac loops

Methane gas sensing has attracted great interest for its applications in agriculture production, industrial manufacturing, medical diagnosis, and environmental monitoring. In this paper, we proposed an ultra-high sensitivity methane gas sensor based on Vernier effect in two parallel optical fiber Sagnac loops. The reference arm contained a polarization maintaining photonic crystal fiber (PM-PCF), while sensing arm consists of a methane gas sensitive film coated PM-PCF. Vernier effect (VE) was generated and as a result the sensitivity was improved by multiple times. The finite element method (FEM) was used to assess the methane gas sensor’s sensing capabilities. According to the numerical simulation, the average sensitivity based on two parallel Sagnac loops in the methane gas concentration of 0-3.5% was 197.775 nm/%, which was 5.5 times in contrast to a single Sagnac loop. To our best knowledge, we presented the methane gas sensor based on VE in two parallel optical fiber Sagnac loops for the first time. The designed optical fiber methane gas sensor possessed the merits of ultra-high sensitivity, providing helpful guidelines for the fabrication of high-performance methane gas sensors.

A Bioinspired Smart Adhesion Actuator with Fast‐Driving and Self‐Sensing Capability

AbstractSmart adhesion actuators have played an increasingly important role in industrial manufacturing, medical equipment, and other applications of daily life. Inspired by the octopus sucker, a smart bionic adhesion actuator is designed that uses hydrogel‐based materials with a photothermal effect to simulate the contraction and relaxation of octopus sucker muscles, enabling it to rapidly grasp and release objects weighing more than 24 times its own weight, while having good cyclic stability. The magnitude of the grasping force can be monitored in real time through an additional sensing structure, which is similar to the nerves of octopus sucker. By sensing and adjusting the state of adsorption, controllable adsorption can be achieved using this self‐sensing function, thereby greatly improving energy efficiency. It provides a new direction for the design of smart bionic adhesion actuators with hydrogels.

Color printing based on 3MF: Color diffusion from the surface to the interior of voxel model

AbstractFull‐color 3D printing technology has become more and more popular for industrial manufacturing applications. The voxelization of color 3D models and the expression of appearance colors become more and more important. To illustrate the complex appearance and internal characteristics of 3D models, we present a voxelization algorithm of the color 3D models for color 3D printing in this paper. Specifically, we use the 3D model of 3D Manufacturing Format (3MF) with color appearance features for surface voxelization first. Then, we propose an improved scan line filling algorithm to realize the voxelization of the interior of the model and obtain the color voxel model. Finally, to improve the high quality of color printing, we propose a surface color inward diffusion algorithm, which can make the surface color of the voxel model diffuse inward and further express the surface color of the voxel model. The experimental results show our proposed method can obtain an effective color voxel model and accurately express the color of the voxel model surface, which can enhance the color effect of the color model and realize the control of voxels.

Industrial Manufacturing Applications of Zinc Oxide Nanomaterials: A Comprehensive Study

Nanomaterials (NMs) that are created with zinc oxide are very valuable for a wide variety of applications. There is a present interest in ZnO nanoparticles in a wide range of industries. This interest may be attributed to the fact that ZnO NPs have many important features. It will be necessary for ZnO NPs to possess certain qualities in order for them to rapidly find uses in industry and for these applications to have an effect on the expansion of the economy. A large surface area, a large bandgap, photocatalytic property, biosensing, bioimaging, and other qualities are included in this list. In this article, the extraordinary characteristics of ZnO NPs, as well as their novel applications in industrial settings and the challenges that come along with their utilization, will be discussed.

A Real-time Video Measurement System for Quality Control Applications

Quality control is extremely important for manufacturing compatible parts to supply products that meet production requirements. It provides to track and control the stages of the process and minimizes waste by supporting high levels of productivity. Most of the manufacturers prefer a video measurement system (VMS), which offers non-contact high accurate measurement devices, for evaluating machined parts and products. However, due to the advanced technology and low competition the cost of the non-contact measurement devices is high. Besides some facilities and some research laboratories couldn’t reach these high-cost devices. Today, with the help of evolving technology and open-source image processing libraries, it is possible to offer cost-effective and accurate non-contact measurement systems. This study aims to put forward a VMS to measure parts/products in two dimensions with swift and accurate results. The proposed system has an error below 1% and the linear regression coefficient (r2) was found over 0.95. It works in real-time and minimum frequency was found 10 Hz for repetitive measurements, real-time measurement applications. The proposed cost-effective device can be adapted into various quality control applications in industrial manufacturing

Ultrasound Sensing Using Packaged Microsphere Cavity in the Underwater Environment.

The technologies of ultrasound detection have a wide range of applications in marine science and industrial manufacturing. With the variation of the environment, the requirements of anti-interference, miniaturization, and ultra-sensitivity are put forward. Optical microcavities are often carefully designed for a variety of ultra-sensitive detections. Using the packaged microsphere cavity, we fabricated an ultrasound sensor that can work in an underwater environment. During practical detection, the optical resonance mode of the cavity can work with real-time response accordingly. The designed structure can work in various complex environments and has advantages in the fields of precision measurement and nano-particle detection.