Industrial Technology Research Articles

IMPACT OF BLOCKCHAIN TECHNOLOGY IN THE E-COMMERCE SECTOR

Blockchain technology is considered as a significant development after the invention of the internet. Blockchain technology records the transactions on database which are encrypted and distributed over many computer networks like a digital ledger of online transactions. This technology can be utilized in the e-commerce industry to develop a decentralized online buying and selling platform. E-commerce industry presently facing many unique challenges like security measures of the e-commerce system, transparency, and trust, efficiency, etc. These challenges can be answered by the implementation of blockchain technology in the e-commerce industry. This paper discussed opportunities for using blockchain technology in the e-commerce industry. Blockchain applications and opportunities are discussed for various aspects of e-commerce like Payment, Security, Supply chain, Work automation with Smart contract, Ethical practices for transparency in e-commerce transactions. The paper seeks to explore the possible uses of blockchain technology within the e-commerce sector.

The Role of Financial Technology in Enhancing the Efficiency of Legal Services

With the rapid development of financial technology (FinTech), its application in the legal service sector is gradually becoming a key force in driving industry innovation. This paper uses both qualitative and quantitative research methods to explore the interaction and synergistic effects of financial technology, regulatory technology (RegTech), and intellectual property protection (IP Protection) in the legal service industry. The study analyzes the current status of financial technology in contract law, compliance checks, and dispute resolution, and evaluates its actual effect on improving the efficiency of legal services. The study found that financial technology has optimized the contract execution process through technologies such as smart contracts and blockchain, improved the level of automation in compliance work, and provided new ways for dispute resolution. Although facing challenges such as technology integration, data security, and legal regulation, these challenges can be effectively controlled through effective risk management and strategic response. The study proposes a series of strategic recommendations, including technological innovation, policy support, education, and training, to promote the collaborative development of financial technology, regulatory technology, and intellectual property protection in the legal service industry. (Beck, R., Bugnion, F., & Pohl, M., 2018) The conclusion of this paper emphasizes the positive role of financial technology in enhancing the efficiency of legal services and points out strategies to cope with challenges, providing valuable insights and suggestions for legal service providers, technology developers, and policy makers to promote the modernization and digital transformation of the legal service industry.

The industrial technological spillover effect and differentiation characteristics of industrial chains in the ecological efficiency of the yellow river basin

The Yellow River Basin (YRB) stands as a critical ecological barrier and a significant economic hub, bridging the western and eastern regions of China. To investigate the synergy of ecoefficiency within the industrial chain of the YRB, this paper introduces a novel research approach. By establishing an industrial technology similarity matrix, spatial econometric models can be employed to analyze spillover effects, which provides a new tool for related research and overcomes some drawbacks of previous studies. The study reveals that industrial ecoefficiency exhibits distinct interaction characteristics across different spatial dimensions. Specifically, the interaction effect within the province is notably superior to that observed within the YRB, as well as in the broader region encompassing the adjacent provinces of the YRB. The upstream and downstream provinces demonstrate a robust level of interaction within their local scopes. However, the middle reaches of provinces exhibit a weak link that undermines the spillover capacity of industrial ecoefficiency across the entire YRB. This finding suggests that hierarchical policy measures should be devised according to the characteristics of spillover effects across various spatial dimensions.

USEFULNESS OF VIBRATION ANALYSIS TECHNIQUES AND SENSORS TO IMPROVE THE MONITORING OF INDUSTRIAL EQUIPMENT

The food industry is constantly seeking advanced technologies to improve the efficiency and reliability of machinery, which is critical to improving product quality and manufacturing efficiency. This paper explores the applications of integrating vibration analysis techniques and sensors to improve machine monitoring in the food industry. Vibration analysis is a well-established technique for mechanical fault detection, providing valuable insight into the condition of rotating equipment. By incorporating advanced sensors that can capture a wide range of vibration signals the aim of this research is to improve the accuracy and sensitivity of device health monitoring. The review reviews existing literature on vibration analysis, sensor technology, and applications in the food industry. It explores how traditional vibration analysis methods can be incorporated into advanced sensor technologies such as accelerometers and other sensors. The integration of these technologies will provide a comprehensive understanding of machine behavior, leading to faster abnormal detection and predictive maintenance.

The Application of Artificial Intelligence Technology in Mechanical Manufacturing and Automation

In order to achieve intelligent production and quality control, improve production efficiency and accuracy, the author proposes an application method of artificial intelligence technology in mechanical manufacturing and automation. The author aims to explore the specific application of artificial intelligence technology in the mechanical manufacturing industry and summarize the main advantages of automation technology. By analyzing these advantages, the aim is to provide targeted recommendations for future technological development. Meanwhile, the author aims to provide theoretical support for promoting the application of modern artificial intelligence technology and automation technology in the field of mechanical manufacturing. In the manufacturing process, intelligent production and quality control can be achieved, improving production efficiency and accuracy; In the field of automation, artificial intelligence technology can achieve intelligent control systems and autonomous decision-making, improving the flexibility and adaptability of production lines. Overall, the application of artificial intelligence technology has brought revolutionary changes to mechanical manufacturing, promoting the upgrading and development of the industry.

Automated Classification of Egg Freshness Using Acoustic Signals and Convolutional Neural Networks

Abstract The acoustic response of eggs has not been fully optimized for quality detection purposes. This research investigates the utilization of acoustic response as input features for classifying fresh and rotten eggs using Convolutional Neural Networks (CNN). Acoustic measurements were conducted using an experimental setup involving a striking rod, microphone, and microcontroller to capture acoustic responses from eggs struck vertically and horizontally. Features such as energy, entropy, zero crossing rate, spectral centroid, and Mel Frequency Cepstral Coefficients (MFCC) were extracted from the recorded acoustic signals. The study utilized a sample set of 200 intact chicken eggs without cracks, equally split between fresh and rotten eggs. Principal Component Analysis (PCA) revealed significant differences in acoustic responses between fresh and rotten eggs, with clear separation observed in horizontal measurements. Three primary classification models—Convolutional Neural Network (CNN), Deep Neural Network (DNN), and Support Vector Machines (SVM)—were evaluated for this classification task. In vertical tapping, CNN and DNN demonstrated stable performance with approximately 85% accuracy, while SVM slightly trailed with around 80% accuracy. However, in horizontal tapping, all three models achieved perfect classification with accuracy, precision, recall, and F1-score reaching 100%. This study demonstrates the effective use of acoustic response as input for Deep Learning models to distinguish between fresh and rotten eggs. The findings highlight the potential application of this technology in the food industry to ensure product quality before consumption, with significant implications for developing reliable automated solutions. Future research could expand validation using larger datasets and optimize sensor usage and data processing techniques to enhance detection consistency and reliability.

Numerical assessment of thermal bridging effects in 3D-printed foam concrete walls

Abstract Integrating smart technology and advanced materials in the construction industry has revolutionized traditional building practices, enhancing efficiency, sustainability, and overall performance. Researchers and professionals in the construction sector have shown significant interest in three-dimensional concrete printing (3DCP) for automating structural engineering tasks. Despite its potential as a sustainable solution to modern construction issues, there is a lack of research on the thermal insulation performance of three-dimensional printed concrete (3DPC) building envelopes, and the potential for integrating foam concrete (FC) to enhance energy efficiency has not yet been studied. This paper presents a numerical analysis examining how different infill geometries affect the thermal performance of 3D-printed foam concrete (3DPFC) lattice envelopes. Six lattice structures were designed with identical thickness, height, length, and comparable insulation areas. The effects of the contact (intersection) area of webs with the interior face shell, webs, and infill rows on the thermal performance of granularly insulated envelopes were studied. The effectiveness of insulation was also established. The findings indicate that the thermal transmittance of 3DPC envelopes correlates directly with the contact area of the webs and the interior surface, with U-values ranging from 0.151 W m2·K to 0.652 W/m2·K. Notably, the absence of direct connections between exterior and interior surfaces enhances insulation efficiency, with double-row structures achieving up to 94% insulation efficiency. However, when there is a direct connection between the two surfaces, the thermal performance of these envelopes is mainly affected by the contact (intersection) area of the webs with the interior face rather than the number of webs. By integrating foam concrete and double-row walls, this study demonstrates an innovative approach to reducing thermal bridging and improving energy performance in 3D-printed construction. The results offer novel insight into optimizing the thermal behavior of 3DPC systems for sustainable building practices.

Influence of constant and alternating electric fields on the deformation and destruction of a liquid droplet

Examining the impact of electromagnetic field, which provides thrust in contemporary rocket engines, is turning into a significant issue. Its resolution is required to guarantee the safety of space flight by enhancing engine performance and lowering fuel consumption. Spacecraft propulsion is achieved by low-thrust rocket engines. The principle of operation for ion colloid engines is the electrostatic acceleration of charged droplets. A static electric field accelerates charged liquid droplets created by electrospraying them in a low-thrust colloid engine. A promising technology in many industries is the active control of droplet motion and deformation with electric field. An electromagnetic field impact on droplet deformation and destruction in a viscous liquid is examined. The effect of electromagnetic field on individual droplets and emulsions is examined in terms of their physical mechanisms. Constant and alternating electric field effects on liquid droplet are represented numerically. The effects of droplet electric capillary number and viscosity ratio on droplet unsteady deformations is explored. The parameters that correspond to the droplet destruction are found. The results obtained have potential applications in enhancing the efficiency of current industrial electric dehydrators and in advancing the development of new electromagnetic field-based demulsification technologies.

Sonar to Quartz Clock: Technology and Physics in War, Academy, and Industry by Shaul Katzir (review)

Sonar to Quartz Clock: Technology and Physics in War, Academy, and Industry by Shaul Katzir (review)

PROSES PRODUKSI INJECTION PHYLON

ABSTRACT The shoe industry in Indonesia has great potential to compete in the global market, producing high-quality products that are in demand by international consumers. In 2018, the industry produced 1.41 billion pairs of shoes, accounting for 4.6% of the world's shoe needs, making Indonesia the fourth largest shoe producer in the world. However, challenges remain, including the Termination of Employment Relationships which raises concerns among the public and investors. The government seeks to provide positive information about investment and labor absorption. One of the innovations in this industry is the use of a phylon injection machine, which is able to produce the bottom of the shoe with high precision and efficiency. This production process involves advanced technology and the use of special materials such as phylon, which has advantages in elasticity, durability, and comfort. This research method includes observation, literature study, field practice, and data analysis. The results of the study show that the use of a phylon injection machine can improve the production efficiency and quality of shoe products. The conclusion of this study is that innovation and technology in the Indonesian shoe industry can strengthen global competitiveness and make a positive contribution to the economy.

Industrial information integration in deep space exploration and exploitation: Architecture and technology

Recently, China and the United States have achieved remarkable success in aerospace science and technology over the years. Space has become another field of competition in the technological advancement of various countries. Through space missions, space tourism, moon and Mars exploration, China and the United States can demonstrate the sophistication of their technologies to the public and audiences around the world. Despite the competitiveness between the big countries, space missions and deep space exploration and exploitation have provided a lot of deep and orbital space information that is beneficial not only for the next space mission but also for enhancing technological development for other domestic uses. Therefore, space industrial information integration (III), or Space III, connecting IoT to form the Internet of Planets, is critically important for deep space explorations. However, few articles have reviewed the existing technologies of space. We are one of the few groups to perform an extensive review, research the space explorations and divide the space information integration systematically based on the information architecture and technologies in the space industries. In this paper, we propose that III can be divided into three different architectures: data, technology, and application, whereas space technology can be divided into six areas. This review is important not only in formulating research in technological integration but also in determining the proposed architecture to facilitate a further extension of applications to large-scale and complex problems in the space industries in the future.

Towards Frugal Industrial AI: a framework for the development of scalable and robust machine learning models in the shop floor

AbstractArtificial intelligence (AI) among other digital technologies promise to deliver the next level of process efficiency of manufacturing systems. Although these solutions such as machine learning (ML) based condition monitoring and quality inspection are becoming popular, these work under very limited conditions. Solutions do not scale-up in the real environment, where there is a mix of manufacturing equipment, where the quality and quantity of data available changes from machine to machine, or where the process changes, changing the distribution of data (i.e. concept drift). This is particularly challenging in highly reconfigurable and flexible environments. Having to develop machine learning models from scratch every single time is not cost-effective, time-consuming, requires expert knowledge that is typically not available in the manufacturing environment as well as can be challenging when data is not available in high volumes. Model robustness, reusability, adaptability and life cycle management are the keys to scale-up this technology in the manufacturing industry. In this work, a conceptual framework to enable simple and robust ML model development for the shop floor is introduced. Referred here as Frugal Industrial AI, the approach takes advantage of existing models and their context to build more robust ones in a data-efficient manner. Using a semantic knowledge base of how to construct these models for different manufacturing applications and semi-automating the development or reuse of solutions through semantic similarity, it is demonstrated how models can be developed in a more streamlined way. In addition, it is demonstrated how capturing process context information is important for the effective reuse of existing models through continual learning. This is key to building more robust ML solutions that can deal with real changing manufacturing environments, avoiding retraining from scratch as well as enabling the non-expert to use AI effectively on the shop floor.

Managing the Adoption of Geospatial Information and Technologies in Multiple Industries

In the era of the 4th industrial revolution, geospatial information has become essential for improving processes and enhancing task performance across the value chain, benefiting sectors such as agriculture, transportation, and logistics. Despite the widespread adoption of geospatial technology, understanding how to manage its adoption is crucial as technology continually evolves. This study aims to elucidate key aspects of managing the adoption of geospatial information and technology through a case study approach. The research involves interviews with Chief Executive Officers (CEOs) and directors from three different industries in Malaysia—agriculture, logistics, and transport—that utilise geospatial technologies. Thematic analysis of the interviews revealed four main themes: managing expectations of adoption, addressing factors of nonadoption, overseeing interactions in the adoption process, and ensuring the immersion of the technology. These findings provide valuable insights into the challenges and strategies for adopting new technologies, particularly those that transform traditional operations into technology-driven practices. The study’s evidence underscores the importance of effective management in fostering the growth and economic expansion driven by geospatial technology.

An Industrial Micro Parts Recognition Technology Based on Improved Yolov8

Abstract Aiming at the recognition and classification problem of micro assembly parts in industrial production, the Yolov8 object detection algorithm was used as the base model to improve the C2f class in the backbone. And apply the improved object detection algorithm to the recognition field of detecting assembly parts. By collecting images of gears, nails, and screws from various angles on Roboflow, a training set and a validation set containing three types of gears, nails, and screws are formed. At the same time, in order to improve the robustness of the Yolov8 object detection algorithm, data processing methods such as adding noise and image rotation were adopted for the samples in the data. Due to the use of Yolov8 as the base model, a TXT text file containing label prediction box position information was formed after labelling the dataset on Roboflow. Based on Python (3.10.12) and cloud platform, improved Yolov8 object detection algorithm was trained and network validation was carried out. Use TXT files as input for the model to obtain and learn features of gears, nails, and screws. After 200 epochs, the mAP for detecting gears, nails, and screws increased by about 3% compared to the base model.

RETRACTION: Thermoresponsive PEG-Coated Nanotubes as Chiral Selectors of Amino Acids and Peptides.

N. Kameta, J. Dong, H. Yui, "Thermoresponsive PEG-Coated Nanotubes as Chiral Selectors of Amino Acids and Peptides," Small 14, no. 15 (2018): 1800030, https://doi.org/10.1002/smll.201800030. The above article, published online on 13 March 2018 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, Naohiro Kameta, Jiuchao Dong and Hiroharu Yui; the journal Editor-in-Chief, Neville Compton; and Wiley-VCH GmbH, Weinheim. The retraction has been agreed upon following an investigation into concerns raised by National Institute of Advanced Industrial Science and Technology (AIST), and also requested by authors due to image fabrication and falsification in electron microscopy images. In Figures 2a, 2b, 2c and S1b (Supporting Information), where the first author fabricated incorrect TEM images using data shown in Figures 2d and S1a (Supporting Information); all affecting the interpretation of the data and research results presented.

RETRACTION: Shrinkable Nanotubes for Duplex Formation of Short Nucleotides.

N. Kameta, H. Akiyama, "Shrinkable Nanotubes for Duplex Formation of Short Nucleotides," Small 14, no. 34 (2018): 1801967, https://doi.org/10.1002/smll.201801967. The above article, published online on 18 July 2018 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, Naohiro Kameta and Haruhisa Akiyama; the journal Editor-in-Chief, Neville Compton; and Wiley-VCH GmbH, Weinheim. The retraction has been agreed upon following an investigation into concerns raised by National Institute of Advanced Industrial Science and Technology (AIST), and also requested by all authors due to image falsification in electron microscopy images. The TEM images of Figures 2a and 2c, and SEM images of Figures S1a and S1b (Supporting Information), where the first author falsificated incorrect scale bars; all affecting the interpretation of the data and research results presented.

RETRACTION: Supramolecular Nanotube Reactors for Production of Imine Polymers with Controlled Conformation, Size, and Chirality.

N. Kameta, W. Ding, "Supramolecular Nanotube Reactors for Production of Imine Polymers with Controlled Conformation, Size, and Chirality," Small 15, no. 19 (2019): 1900682, https://doi.org/10.1002/smll.201900682. The above article, published online on 28 March 2019 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors, Naohiro Kameta and Wuxiao Ding; the journal Editor-in-Chief, Neville Compton; and Wiley-VCH GmbH, Weinheim. The retraction has been agreed upon following an investigation into concerns raised by National Institute of Advanced Industrial Science and Technology (AIST), and also requested by all authors due to image falsification in electron microscopy images. The SEM and TEM images of Figure 6a, 6b-1, 6b-2, 6c-1 upper left, 6c-1 upper right, 6c-1 lower, 6c-2, 6d, 6e, and 6f, where the first author falsificated incorrect scale bars; all affecting the interpretation of the data and research results presented.

Dependence of green energy markets on big data and other fourth industrial revolution technologies

This paper analyzes the dependence and connectedness among fourth-industrial revolution technology markets (including big data and artificial intelligence, blockchain, and financial technology) and global and regional (US, Europe, and Asia) green energy markets. In particular, we consider the dynamic dependence among these markets in terms of both returns and volatility across different market conditions and investment horizons using the cross-spectral coherence and Quantile-VAR connectedness approach. Three main results emerge from our analysis. First, the return dependence is relatively stronger than volatility dependence and is stronger across most time scales among the technology markets and the European and Asian regional green energy indexes. Second, the return and volatility connectedness is stronger during extreme than normal market conditions. Unless under bullish market times, volatility connectedness appears smaller than return connectedness, implying that market volatility risks spread less forcefully among these markets than return risks under normal and bearish market periods. Third, geopolitical risks, business environment, economic policy, fixed-income, and oil and gold markets’ uncertainties are significant predictors of the degree of return and volatility connectedness. Overall, our findings offer crucial insights for short- and long-term investors interested in portfolios with modern technology and green assets. They also emphasize the roles of market and macroeconomic factors in shock propagation and their implications for low-carbon transition.

Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. Type of peer review: Single Anonymous Conference submission management system: Morressier Number of submissions received: 75 Number of submissions sent for review:53 Number of submissions accepted: 45 Acceptance Rate (Submissions Accepted / Submissions Received × 100): 60 Average number of reviews per paper: 3.00 Total number of reviewers involved: 53 Number of final published papers:35 Number of declined papers:10 Contact person for queries: Name: Gow-Yi Tzou Email: gtzou@uow.edu.au Affiliation: University of Wollongong, Australia President, Taiwan Fasteners Industry Technology Development Association

Internet enterprise management, network structure and network capabilities: Basis for internet industry technology innovation framework

Internet enterprise management, network structure and network capabilities: Basis for internet industry technology innovation framework