Intelligent Manufacturing Technology Research Articles

Narrow Weld Joint Recognition Method Based on Laser Profile Sensor

Intelligent manufacturing technology has recently experienced rapid development, where robot welding systems are an essential component. A laser profile sensor is commonly utilized in intelligent robot welding systems. However, when the laser stripe is projected onto a narrow weld joint, the deformation of the laser stripe is not sufficiently apparent, and the traditional weld joint recognition methods based on the laser profile sensors cannot detect the narrow weld joint position. Meanwhile, the strong arc and spatter noise during welding and the expansion of weld joint width caused by welding thermal expansion are likely to interfere with weld joint recognition. In addition, many common weld seam recognition methods can only recognize certain weld joints and have limited flexibility and robustness for other types of weld joints. This study proposes a wide range of weld joint recognition algorithms based on the laser profile sensor to overcome these challenges. The gray value histogram analysis method, the adaptive threshold method, the internal propulsion center and boundary extraction (IPCBE) method, the coordinate analysis method, and the stripe end center detection method proposed in this study are used primarily in the algorithm. The algorithm solves the problem of identifying narrow weld joints and allows for the identification of larger conventional weld joints. Furthermore, the algorithm has good a anti-spatter and anti-arc interference ability and a fast speed, allowing it to meet the demand for real-time welding identification.

Intelligent manufacturing eco-system: A post COVID-19 recovery and growth opportunity for manufacturing industry in Sub-Saharan countries

The lagging behind intelligent technologies and the COVID-19 pandemic together have impacted the emerging economy particularly the manufacturing sector in sub-Saharan countries. This paper systematically discusses intelligent manufacturing technologies with an aim to map out their importance and industrial applicability and to show their significance to contain COVID-19 pandemic. Intelligent Manufacturing Systems (IMS) is then adapted as a post COVID-19 recovery and growth opportunity to ensemble to production processes of manufacturing industry in the sub-Saharan countries. Proposition of a Triple Helix Collaboration Eco-system that delineate a recursive contribution of Government(s), academia, and industry accompanies the IMS adoption. The intention is to shape the existing industrial challenges through networking in the area of intelligence technologies. While proposing the Eco-system, a post COVID-19 recovery and growth opportunity and intra-Africa scientific collaborations are taken into account.

Intelligent mechanical manufacturing technology based on intelligent manufacturing technology

With the development of intelligent manufacturing technology, the application of intelligent machinery manufacturing technology has been widely promoted. Intelligent machinery manufacturing technology is a technology that integrates advanced manufacturing technology and intelligent control technology. It can realize the intelligent control of the entire manufacturing process, improve the manufacturing efficiency and product quality, and reduce the manufacturing cost. Based on intelligent manufacturing technology, intelligent machinery manufacturing technology has been developed rapidly and has been widely applied in various fields such as automotive, aviation and so on. It can achieve the goals of automation, intelligence, high efficiency, and personalization, and promote the development of various industries towards intelligent manufacturing. However, there are still challenges in the development and application of intelligent machinery manufacturing technology, such as the high cost of equipment, the difficulty in controlling the manufacturing process, and the lack of skilled workers. Future research should focus on solving these challenges and promoting the further development and application of intelligent machinery manufacturing technology.

An Efficient Approach to Sharing Edge Knowledge in 5G-Enabled Industrial Internet of Things

Thanks to the booming development of artificial intelligence, 5G technology, and intelligent manufacturing technology, numerous intelligent edge devices contained in the industrial Internet of Things (IIoT) are endowed with the ability to mine knowledge from perceived massive data. Knowledge-driven IIoT plays an unprecedented role in application fields such as cyber-physical systems and Industry 4.0. However, knowledge is generally scattered across the distributed edge devices of IIoT. Therefore, in order to further achieve the edge intelligence in IIoT, it is very important to explore an efficient edge knowledge sharing method. In this article, we establish a decentralized knowledge sharing platform in IIoT. First, for public knowledge, a dynamics model that can quantitatively describe its sharing process is established by using the system dynamics theory. Furthermore, a control method for maximizing public knowledge sharing under constraints based on the optimal control theory is presented. Second, for private knowledge, a trusted transaction control method based on blockchain technology is proposed. By developing both smart contract and lightweight consensus mechanism, the efficient peer-to-peer sharing of private knowledge is realized, and the integrity of knowledge and the privacy of participants are protected. The results of extensive experiments show that the proposed method can eliminate the obstacles of knowledge sharing among edge devices in IIoT, and further promote the development of edge intelligence empowered 5G-enabled IIoT applications.

Artificial Intelligence Empowered Laser: Research Progress of Intelligent Laser Manufacturing Equipment and Technology

Artificial Intelligence Empowered Laser: Research Progress of Intelligent Laser Manufacturing Equipment and Technology

Causes of concrete cracks in the construction of roads and bridges facing intelligent manufacturing technology

Causes of concrete cracks in the construction of roads and bridges facing intelligent manufacturing technology

Research on the integrated management and mapping method of BOM multi-view for complex products.

The bill of materials (BOM) runs through all stages of the life cycle of manufacturing products, which is the core of manufacturing enterprises. With increasing complexity of modern manufacturing engineering and widespread using of intelligent manufacturing technology, the BOM data keeps rising and transformation process is increasingly frequent and complicated. In order to improve efficiency of BOM management and ensure the diversity, accuracy and consistency of BOM in the product development, the BOM multi-view integrated management and mapping method for complex products were researched. First, a complex product BOM integrated management framework and the evolution model based on multiple views were established which described the BOM integrated management mechanism and transformation relationship among different BOMs. Subsequently, process of BOM transformation was analyzed, and a BOM transformation model was proposed. Moreover, a rule-based BOM multi-view mapping algorithm was proposed. With the rule definition and mathematical modelling for key components, the complex mapping principle was elaborated. Finally, the BOM multi-view transformation cases and the prototype system were illustrated and discussed, which verified the feasibility and versatility of model and method.

Build an Integrated Scene Teaching System for Additive Manufacturing Based on the Integration of Production and Education

Additive manufacturing, also known as 3D printing, is known as one of the subversive intelligent manufacturing technologies that can lead industrial transformation. It has significant advantages in personalized customization and preparation of complex structural components, and is having an important impact on traditional manufacturing process, factory production and processing mode and the entire manufacturing industry chain. At present, the talent gap of additive manufacturing and related specialties in China exceeds 10 million, of which the manufacturing industry has the largest demand for additive manufacturing application talents. It is estimated that the talent gap will be 8 million by 2025. The construction of scenario based teaching system of additive manufacturing integrated courses based on the integration of production and education. At present, it is urgent for universities and vocational education to fully integrate the “research” and “technology” of universities and vocational education institutions with the “production” of enterprises to build a scenario of production and education integration education that suits students. By creating real and vivid scenes for students, Help students get familiar with the background and business operation process of the integrated operation of additive manufacturing, strengthen students’ ability to integrate theoretical knowledge, and apply what they have learned in combination with practice.

Preface

The 4th International Symposium on Robotics and Intelligent Manufacturing Technology (ISRIMT 2022) was successfully held on September 23-25, 2022 in Changzhou, China (virtual conference). ISRIMT 2022 provided a platform for scientific research achievements and cutting-edge technologies sharing, and for all the participants to understand the academic development trends in related fields, promoting cooperation in the industrialization of academic achievements.We had the honor of having invited Prof. Dequn Li from Huazhong University of Science and Technology, China to serve as our Honorary Chairman. The conference covered keynote speeches, oral presentations, and online Q&A discussion, attracting 90 individuals. Firstly, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers selected were presented by their authors by turns.During the conference, twelve distinguished professors were invited to address their keynote speeches. Among them, Prof. Yu Tian from Tsinghua University, China addressed a thought-provoking speech Bio-inspired Adhesion: From Interfacial Mechanism to Robotic Applications. In this presentation, he introduced the research progress of his group in the field of bio-inspired adhesion, focusing on the design strategy from the understanding of interfacial mechanics to the applications of grasping robotics. And then, Prof. Giuseppe Carbone from University of Calabria, Italy made a speech on the Examples of Innovative Robot Designs with Embodied Intelligence. Illustrative examples were outlined to show the feasibility and practical usefulness of this approach as referring to recent designs such as parallel/hybrid manipulators, humanoid robots, cable-driven robots for conventional or non-conventional applications including healthcare, agriculture, cultural heritage/space exploration. Last but not the least, Prof. Dunbing Tang from Nanjing University of Aeronautics and Astronautics, China delivered a presentation on Multi-agent Reinforcement Learning for Online Scheduling in Smart Factories. This paper presented new cyber-physical integration in smart factories for online scheduling of low-volume-highmix orders. Their dramatic speeches had triggered heated discussion in the conference. And every participant praised this conference for disseminating useful and insightful knowledge.The proceedings of ISRIMT 2022 are a compilation of the accepted papers and represent an interesting outcome of the conference. These papers feature but are not limited to the following topics: Artificial Intelligence, Cloud Manufacturing, Distributed Robot Systems, Intelligent Optimization Method, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.We would like to express our sincere gratitude to all the keynote speakers, peer reviewers, and all the participants who supported ISRIMT 2022. Particularly, our special thanks go to the Journal of Physics: Conference Series, for all the efforts of its colleague in publishing this paper volume. We firmly believe that ISRIMT 2022 have contributed to not only scientific and engineering progress but also other new products and processes.The Committee of ISRIMT 2022List of Committee member, Honorary Chairman are available in this Pdf.

Preface

The 3rd International Conference on Advanced Materials and Intelligent Manufacturing (ICAMIM 2022) was successfully held in Guangzhou, China from August 5-7, 2022. ICAMIM 2022 provided a high-level technical exchange platforms for experts, scholars, and entrepreneurs worldwide to communicate face-to-face with each other, strengthening the exchange of advanced materials and intelligent manufacturing technologies in various countries around the world.We were greatly honored to have both Prof. Kaiming Wu from Wuhan University of Science and Technology, China and Prof. Liejun Li from South China University of Technology, China to serve as our Conference Chairmen. 120 individuals attended the conference. The conference agenda was composed of keynote speeches and oral presentations. Firstly, keynote speakers were each allocated 30-45 minutes to hold their speeches. Then in the oral presentations, the excellent papers we had selected were presented by their authors by turns.At the beginning of the conference, nine sophisticated keynote speakers were invited to deliver their speeches. Among them, Prof. Mingxin Huang from The University of Hong Kong, China made a report on the Hydrogen Embrittlement of 1500 and 2000 MPa Press-Hardened Steel. This presentation compared the hydrogen embrittlement of two PHS grades with ultimate tensile strength of 1500 and 2000 MPa respectively. And it was found that hydrogen embrittlement depends strongly on the deformation strain rate. In addition, Prof. Tongguang Zhai from University of Kentucky, USA showed us his research: Physical Models for Quantification of Fatigue Crack Initiation Life in Engineering Alloys Based on Microstructure. He introduced the relationships between fatigue crack initiation and 3-D microstructure discovered recently in high performance Al alloys and established two physical models to quantify the stochastic behaviors of fatigue crack initiation. Last but not least, Researcher. Yu Chen from Institute of Intelligent Manufacturing, GDAS delivered a speech on the Industrial Internet Technologies and Manufacturing Digital Transformation. This speech introduced the concepts, intension and features of Industrial Internet, expounded the close relationship between Intelligent Manufacturing and Industrial Internet, and illustrated the typical Industrial Internet application scenarios in the Intelligent Factory and Manufacturing Digital Transformation. The brilliant speeches of each keynote speaker had triggered heated discussion in the conference. Moreover, their speeches won the praise of every participant for disseminating useful and insightful knowledge.The proceedings of ICAMIM 2022 cover various topics, which include Non-ferrous Metal Materials, Ceramic Metallurgy, Biomimicry Mechanisms, Engineering Optimization, Digital Manufacturing, etc. All the papers have been checked through rigorous review and processes to meet the requirements of publication.On behalf of the conference organizing committee, we’d like to show our congratulation and sincere gratitude to all the keynote speakers, peer reviewers, and all the participants. In addition, our special thanks go to the Journal of Physics: Conference Series, for all efforts of the colleagues in publishing this paper volume. The help and contribution of each individual and institution was instrumental in the success of the conference.Committee of ICAMIM 2022List of Committee member is available in this Pdf.

Application of Digital Twins and Metaverse in the Field of Fluid Machinery Pumps and Fans: A Review

Digital twins technology (DTT) is an application framework with breakthrough rules. With the deep integration of the virtual information world and physical space, it becomes the basis for realizing intelligent machining production lines, which is of great significance to intelligent processing in industrial manufacturing. This review aims to study the application of DTT and the Metaverse in fluid machinery in the past 5 years by summarizing the application status of pumps and fans in fluid machinery from the perspective of DTT and the Metaverse through the collection, classification, and summary of relevant literature in the past 5 years. The research found that in addition to relatively mature applications in intelligent manufacturing, DTT and Metaverse technologies play a critical role in the development of new pump products and technologies and are widely used in numerical simulation and fault detection in fluid machinery for various pumps and other fields. Among fan-type fluid machinery, twin fans can comprehensively use technologies, such as perception, calculation, modeling, and deep learning, to provide efficient smart solutions for fan operation detection, power generation visualization, production monitoring, and operation monitoring. Still, there are some limitations. For example, real-time and accuracy cannot fully meet the requirements in the mechanical environment with high-precision requirements. However, there are also some solutions that have achieved good results. For instance, it is possible to achieve significant noise reduction and better aerodynamic performance of the axial fan by improving the sawtooth parameters of the fan and rearranging the sawtooth area. However, there are few application cases of the Metaverse in fluid machinery. The cases are limited to operating real equipment from a virtual environment and require the combination of virtual reality and DTT. The application effect still needs further verification.

Application of Mechanical Intelligent Manufacturing Technology in Factory Production

Application of Mechanical Intelligent Manufacturing Technology in Factory Production

Research and Implementation of "Personalized Orientation" Talent Training Program Based on Geely Automobile

With the application of new intelligent manufacturing technology to transform the specialty, build a personalized talent training mode deeply integrated into innovation education. Build a curriculum system highly integrated with the professional ability development needs of core posts related to the pillar industries such as the vehicle factory and power base of Zhejiang Geely Holding Group Co., Ltd., focusing on the improvement of innovation ability and the application of new technologies, and establish a trinity practical teaching system of "training, research and development, innovation". Strengthen the construction of high-quality teaching resources, improve the application level of digital teaching resources, and improve the level of the "double teachers and double abilities" teacher team. Deepen the integration of production and education, greatly improve the quantity and quality of scientific research and enterprise technological transformation, and significantly expand the depth and breadth of school enterprise cooperation.

Intelligent Manufacturing Technology in the Steel Industry of China: A Review.

Intelligent manufacturing, defined as the integration of manufacturing with modern information technologies such as 5G, digitalization, networking, and intelligence, has grown in popularity as a means of boosting the productivity, intelligence, and flexibility of traditional manufacturing processes. The steel industry is a necessary support for modern life and economic development, and the Chinese steel industry's capacity has expanded to roughly half of global production. However, the Chinese steel industry is now confronted with high labor costs, massive carbon emissions, a low level of intelligence, low production efficiency, and unstable quality control. Therefore, China's steel industry has launched several large-scale intelligent manufacturing initiatives to improve production efficiency, product quality, manual labor intensity, and employee working conditions. Unfortunately, there is no comprehensive overview of intelligent manufacturing in China's steel industry. We began this research by summarizing the construction goals and overall framework for intelligent manufacturing of the steel industry in China. Following that, we offered a brief review of intelligent manufacturing for China's steel industry, as well as descriptions of two typical intelligent manufacturing models. Finally, some major technologies employed for intelligent production in China's steel industry were introduced. This research not only helps to comprehend the development model, essential technologies, and construction techniques of intelligent manufacturing in China's steel industry, but it also provides vital inspiration for the manufacturing industry's digital and intelligence updates and quality improvement.

Preface

The 2022 5th International Conference on Mechanical, Electrical and Material Application (MEMA 2022) was successfully held on June 17-19, 2022. Due to the COVID-19 pandemic around the world, and with the strict travelling rules in China, it is still difficult to take international travel for our attendees abroad. Therefore, MEMA 2022 was held both in physical (Chengdu, China) and online (Zoom).The conference focused on the latest research field of “Mechanical, Electrical and Material applications”, promoted the development and integration of related disciplines, grasped the international frontier trends in this field, exchanged the latest research results, and provided an international platform for domestic and foreign institutions of higher learning, scientific research institutes, experts, professors, scholars, engineers, etc. to share professional experience, expand professional networks, exchange new ideas face-to-face and display research results, to explore the key challenges and research directions facing the development of this field. Focused on the latest research results of experts and scholars in the key areas of mechanical electrical technology and material equipment around the world, and carried out high-level, three-dimensional and international academic exchanges and cooperation. Through exchanges from different disciplines and fields, we will forge innovative ideas, stimulate innovative sparks, and accumulate strength to promote the development of related fields and industries and grasp a new wave of scientific and technological and industrial change. Experts and scholars in related fields are welcome to actively submit articles to participate in the conference.During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches.There were over 150 experts and scholars in the area of mechanical, electrical and material application representing different famous universities and institutes around the globe to attend this hybrid conference. During the conference, we were pleased to invite four distinguished experts to present their insightful speeches. The first keynote speaker, Prof. Kai Yang, Huazhong University of Science and Technology, China. And then we had Prof. Valentina E. Balas, Aurel Vlaicu University of Arad, Romania. Her research interests are in Intelligent Systems, Fuzzy Control, Soft Computing, Smart Sensors, Information Fusion, Modeling and Simulation. Prof. Prof. Junxi Bi, Inner Mongolia University of technology. His main directions include reliability design, manufacturing, optimization and control of complex electromechanical equipment; Fault diagnosis and performance prediction of large equipment; Digital machining and intelligent manufacturing technology. Our finale keynote speaker, Assoc. Prof. Guomin Luo, Beijing Jiaotong University. She has been engaged in the research of power system transient signal analysis and processing for a long time. Their insightful speeches had triggered heated discussion. Every participant praised this conference for disseminating useful and insightful knowledge.List of Committee member is available in this Pdf.

Research on the Integration of Intelligent Technology and Mechatronics in Mechanical Manufacturing

With the arrival of the era of technological revolution, the speed of scientific and technological development has been gradually accelerated, which has effectively promoted the integration of electromechanical equipment as soon as possible and further strengthened the production level. In short, at present, we are in the era of industrial informatization, and electromechanical integration technology has also developed, which has effectively promoted the perfect combination of machinery and electronics. Over time, it has developed into electromechanical integration technology, which can intelligently control various mechanical equipment. For mechatronics technology, the intelligent manufacturing technology can interact closely with the system during the specific use, build an all-round and multi-level intelligent manufacturing, and effectively promote the development of industrial production in the direction of humanization and scientization.

A novel graph neural networks approach for 3D product model retrieval

ABSTRACT With the quick development of intelligent manufacturing technology, increasing of 3D product models data resource raises the need for product models retrieval method that can fully exploit model information, whereas the existing methods only concern geometric information with little or no manufacturing information. Model-Based Definition (MBD) 3D engineering has gained wide popularity in recent times which enables smart manufacturing by attaching product manufacturing information. Its tip orientation to the effective reuse of MBD for reducing development time and creating an efficient digital thread. In this paper, we proposed the MBD-based attribute adjacency graph neural networks (MAAGNN) with attention mechanism. Firstly, the MBD-based attribute adjacency graph (MAAG) is established to fully express the product semantic information, which includes geometric and non-geometric information of the MBD model. Then graph neural network (GNN) is employed to embed the MAAG into continuous vector spaces, and attention mechanism is introduced to adaptively recognize more important features information, which can solve the ambiguity problem caused by blend features such as chamfer. Finally, the model is trained to achieve fast and accurate retrieval of the MBD models. Experiments demonstrate its potential advantages to meet the requirements of engineering applications.

Laser-Induced Graphene Stretchable Strain Sensor with Vertical and Parallel Patterns.

In intelligent manufacturing and robotic technology, various sensors must be integrated with equipment. In addition to traditional sensors, stretchable sensors are particularly attractive for applications in robotics and wearable devices. In this study, a piezoresistive stretchable strain sensor based on laser-induced graphene (LIG) was proposed and developed. A three-dimensional, porous LIG structure fabricated from polyimide (PI) film using laser scanning was used as the sensing layer of the strain sensor. Two LIG pattern structures (parallel and vertical) were fabricated and integrated within the LIG strain sensors. Scanning electron microscopy, an X-ray energy dispersive spectrometer, and Raman scattering spectroscopy were used to examine the microstructure of the LIG sensing layer. The performance and strain sensing properties of the parallel and vertical stretchable LIG strain sensors were investigated in tensile tests. The relative resistance changes and the gauge factors of the parallel and vertical LIG strain sensors were quantified. The parallel strain sensor achieved a high gauge factor of 15.79 in the applied strain range of 10% to 20%. It also had high sensitivity, excellent repeatability, good durability, and fast response times during the tensile experiments. The developed LIG strain sensor can be used for the real-time monitoring of human motions such like finger bending, wrist bending, and throat swallowing.

The Recent Progress of Lithography Machine and the State-of-art Facilities

With the rapid development of industrial intelligent manufacturing and electronic information technology, the importance of integrated circuits has grown fast. Photolithography, as the core technology of integrated circuit industry, has become a key research target for researchers all over the world. In this paper, we provide a brief introduction to photolithography as well as an outlook on the future development direction. Firstly, the key metric of lithography system, which is resolution, and how it relates to lithographic performance is analyzed. Secondly, some exposure methods developed on UV and DUV light sources are discussed, which are commonly used in the industry nowadays. Subsequently, this paper presents the structure and performance of some representative lithography equipment. Then, some summarizations are completed about the most recent advances in EUV lithography and high NA lithography. Finally, we examine the limitations of current lithography and forecast the future of lithography. The goal of this paper is to provide a guide on lithography equipment, particularly the most advanced products available nowadays. Additionally, some potential challenges that photolithography may face in its future development are highlighted, and some perspectives on how photolithography will evolve over the next decade are provided. These results shed light on guiding the future development direction of lithography machine as well as ways to push Moore’s law even further.

Emerging Intelligent Manufacturing of Metal Halide Perovskites

AbstractThe incorporation of high‐precision intelligent manufacturing technologies into patterned metal halide perovskite production has attracted scientific and commercial interest because of advantages in terms of designable and controllable processes, multiscale and multimaterial construction strategies, and improved energy‐conversion performance. Here, the current developments in intelligent manufacturing technologies are reviewed for patterned and tailored perovskite structures. Six high‐precision approaches, namely, nanoimprint lithography, space‐confined growth, ink‐based direct printing, laser‐induced nucleation, modification using a laser, and high‐energy etching, are investigated and summarized. The focus of the review is on the basic principles of intelligent manufacturing methods, process optimization, and controllable perovskite microstructures. Additionally, the performance improvements of patterned and tailored perovskites and their devices, including photodetectors, solar cells, lasers, information storage and encryption devices, anticounterfeiting devices, and full‐color display applications, are discussed. The potential future applications of shaped perovskites fabricated via intelligent manufacturing technologies are promising.