Intelligent Manufacturing Technology Research Articles

A wireless reconfigurable modular manipulator and its control system

As the core of Industry 4.0, the intelligent manufacturing technology requires robotic arms to be networked, customized and flexible. Traditional industrial robots have a large number of electrical cables. The end effectors cannot be easily replaced. In this paper, a reconfigurable modular arm with quick replacement of tools and its neural adaptive control system are developed. It consists of an anthropomorphic 7 degree-of-freedom (DOF) manipulator, a reconfigurable connection mechanism (RCM) and a wireless controller. Based on the modular design ideas, each joint is integrated with a motor, a harmonic reducer, two encoders and a servo controller to achieve high torque capacity but keep light weight. Shape Memory Alloy (SMA) wires and steel spheres are used in the RCM to provide mechanical and electrical connections between the arm and the end effector for rapid replacement. The central controller communicates with each servo controller through wireless communication links. Furthermore, the neural adaptive control method compensating position and force tracking errors caused by the model uncertainty and time delay is addressed. Finally, the prototype is fabricated and experiments are carried out. The developed arm has high position accuracy, force control accuracy, and reliable reconfigurable capability.

Application Analysis of Infrared thermal imaging Technology in Intelligent Manufacturing Field

With the continuous development of science and technology, traditional manufacturing technology has also been developed. It has gradually developed in the direction of intelligent manufacturing technology through continuous integration with the advantages of machinery, energy, materials and other technologies. Intelligent manufacturing technology has been widely used by virtue of its own advantages such as high quality, high efficiency and energy saving. At present, in order to better improve the efficiency of intelligent manufacturing technology, relevant personnel have begun to apply infrared thermal imaging technology to the manufacturing field.

Complex Behavior of Droplet Transfer and Spreading in Cold Metal Transfer

In intelligent manufacturing, an intelligent control method of welding process is an important process of intelligent welding manufacturing technology (IWMT). Metal transfer is a key factor to control the welding process. Metal transfer and droplet spreading are of vital importance for welding formation. A new theoretical model of cold metal transfer (CMT) in short-circuit transfer mode is proposed in this paper. In this model, the CMT welding process is regarded as a continuous process of arc heating, mass transfer, short-circuit, and spreading, and the relations between these processes are analyzed. The calculation equations used by the model can analyze the welding formation clearly and simplify the complex welding process into continuous physical behavior. The predicted welding width shows good agreement with the measurement results. The mechanism of increased welding width is also comprehensively analyzed. Results have a certain guiding effect on aluminum alloy welding process control.

Research on Intelligent Manufacturing Technology of Automobile Industry

Research on Intelligent Manufacturing Technology of Automobile Industry

A knowledge base model of integral impeller milling process based on Teamcenter platform

As an important foundation of integral impeller milling manufacturing, integral impeller milling process knowledge plays a significant role in design and production. With the rapid development of aerospace industry and intelligent manufacturing technology, it is very urgent to construct knowledge base of milling process for typical integral impeller structure. Based on the analysis of typical milling process knowledge of integral impeller, the study proposes a model of knowledge base of milling process of integral impeller based on Teamcenter platform, which can effectively realize the sharing and reuse of knowledge of integral impeller milling process.

WITHDRAWN: Game analysis of dual network embedded enterprise technology innovation: Intelligent manufacturing pilot perspective

Abstract The innovation activities of intelligent manufacturing pilot enterprises are becoming more and more reticulated. Cluster innovation network and knowledge innovation network are embedded in the technology innovation of intelligent manufacturing pilot enterprises. This paper constructs innovation evolution mechanism. It uses game and simulation to verify and analyze. The research results show that: When the physical domain of the network is embedded, the willingness to share resources among enterprises with similar strength is greatly influenced by time. The relationship maintenance curve of both parties evolves slowly in a decreasing trend. When the spatial domain of the network is embedded, the strategic choice of universities and research institutes is not sensitive to the change of collaborative innovation level of intelligent manufacturing pilot. The duration of cooperation is in direct proportion to the level of collaborative innovation. This study provides a reference for China's intelligent manufacturing technology innovation decision making.

Preface

Welcome to 2020 International Conference on Advanced materials and Intelligent Manufacturing & Advanced Steel for Automotive Seminar (ICAMIM 2020). The conference was successfully held during August 21-23, 2020 in Guilin, China. The aim of this conference is to share the latest research progress especially on steel in the structural part of modern car and to strengthen the exchange of advanced materials and intelligent manufacturing technologies in various countries around the world. This conference provided a high-level technical exchange platform to jointly promote continuous innovation in the field of advanced materials and intelligent manufacturing for worldwide experts, scholars, science and technology workers, entrepreneurs and other relevant personnel engaging in advanced materials and intelligent manufacturing research.The meeting focused on the latest research fields of “Advanced materials” and “Intelligent Manufacturing & Advanced Steel for Automotive”. It consists of two parts: oral presentations and speeches of keynote speakers. More than 70 participants attended the meeting, they were from China, Singapore, Malaysia, Italy, Iran and more. We are greatly honored to have invited Prof. Liejun Li, from South China University of Technology, and Researcher. Taobo Cheng, from Guangdong Institute of Intelligent Manufacturing to serve as our Conference Chairs.List of Committee member is available in this pdf.

Research Status and Development Trend of Advanced Manufacturing Technology for fuze

This paper analyzes a series of problems which need to be solved for a long time in China’s fuze manufacturing industry, such as high resource consumption, poor economic benefit, low technology content, mostly in the low end of the industrial value chain, and points out that advanced manufacturing technology can promote the transformation and development of China’s fuze manufacturing industry. Based on the brief introduction of the concept, development history and key technologies of advanced manufacturing technology, this paper focuses on the application background, theoretical research and engineering progress of micro nano structure precision machining technology, intelligent additive manufacturing technology, intelligent manufacturing system and industrial internet. It is proposed that China should take “made in China 2025” as the traction, vigorously develop advanced manufacturing technology, and promote the sustainable, green and healthy development of China’s manufacturing industry.

Intelligent Manufacturing Systems in COVID-19 Pandemic and Beyond: Framework and Impact Assessment

Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks. The intelligent manufacturing (IM) systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms. The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network, which mitigates the severity of industrial chain disruption. In this study, we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks. Considering the constraints of the IM resources, we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic.

Address business crisis caused by COVID‐19 with collaborative intelligent manufacturing technologies

While COVID-19 has affected the daily life of almost everyone around the world, it has also caused major disturbances to the global economy and to the operations of many businesses in the manufacturing industry. Reginal lockdowns resulted in supply chain breakages. Workforce shortages caused difficult shop floor operations. This study tries to discuss how collaborative intelligent manufacturing technologies can help to address these challenges through (i) optimal design of resilient collaborative supplier networks; (ii) collaborative planning of manufacturing operations among geographically distributed manufacturing plants; (iii) functional redundancy and dynamic reconfiguration of different shop floors; (iv) dynamic intelligent rescheduling of workforces for factory/shop floor operations; (v) remote testing and maintenance of manufacturing equipment with the support of digital twins technologies. These approaches are expected to be an effective hedge against the impact of COVID-19 or other natural disasters.

Research on Cloud Manufacturing Overlay Network Technology Based on Web of Things

In recent years, the combination of the Web of things and various manufacturing technologies has become a hot issue in academia. The emergence of intelligent manufacturing technology based on the Web of things has been repeatedly proposed by various industrial enterprises and researchers. On this basis, a new manufacturing mode of cloud manufacturing technology is proposed. It can be seen that the Web of things technology combined with cloud manufacturing is the key technology to realize intelligent manufacturing thinking in today’s society. This paper summarizes the overall architecture of the Web of things coverage network through a brief analysis of cloud manufacturing technology, and finally comes to a conclusion.

Research on Garment Mass Customization Architecture for Intelligent Manufacturing Cloud

The deep integration of Internet, intelligent manufacturing and big data technology has promoted the development of products to be networked, digital, intelligent and personalized. The rapid iteration and differential segmentation of consumer demand has spawned new personalized consumer demand, transforming the traditional manufacturing model into a service-oriented manufacturing model. This paper analyses the large-scale customized operation mode of domestic and foreign clothing custom brands. In view of the transformation of traditional clothing industry, this paper proposes a solution to establish a large-scale custom clothing architecture under the vision of intelligent manufacturing cloud platform technology. This paper uses data mining and cloud computing and other methods to build an “Internet + manufacturing” innovation model with rapid collaboration under the umbrella of big data, and propose an architecture for mass customization of clothing, providing effective solutions and strategy recommendations for the transformation and upgrading of the traditional apparel industry.

Research and Application of Key Technology of Data-Driven Intelligent Manufacturing of Electronic Components

With the development of electronic equipment towards multi-function, high performance and miniaturization, the assembly density and complexity of electronic components become higher and higher. For the manufacturing characteristics of electronic components in many varieties, small batch and mixed production line, this paper uses intelligent manufacturing technology based on industrial big data, puts forward implementation architecture of electronic components digital workshop, explores the “perception - analysis - decisions” closed-loop mechanism of all data of manufacturing process of electronic component, sets up network security platform for industrial control system which ensures workshop operate transparently and safely. The necessity and feasibility of landing of data-driven intelligent workshop are verified by an application example of digital workshop of radar core microwave components, which effectively improves the production efficiency and workshop management level.

Intelligent Control of Flexible Joint Manipulator Based on Dynamic Pattern Recognition

With the rapid development of intelligent manufacturing and Internet technology, the industrial system has entered a new stage of development. As an indispensable carrier for intelligent manufacturing and industrial development, robots are expanding their applications. Among them, the flexible mechanical arm has the advantages of light weight, low energy consumption and low inertia compared with the bulky rigid mechanical arm, and has been increasingly valued. The flexible manipulator is a very complex dynamic system whose dynamic equations are characterized by nonlinearity, strong coupling and time-varying. Therefore, this paper uses the most common and effective method to establish the dynamic model of the flexible manipulator using the Lagrange equation. Due to the uncertain system parameters, lack of control of the trajectory and the influence of load changes and external disturbances, the flexible manipulator has great uncertainty in its control process, and the traditional control methods have not very good control effect. Based on this, this paper proposes a combination of dynamic pattern recognition theory and flexible joint manipulator intelligent control method for the two-link flexible manipulator, and uses the new GA-RBF neural network closed-loop adaptive control method to achieve high precision. Trajectory tracking ensures stability in a shorter time. The simulation results show that the intelligent joint control method based on dynamic pattern recognition has better trajectory tracking and autonomous fast recognition dynamic mode.

DfRem-Driven Closed-Loop Supply Chain Decision-Making: A Systematic Framework for Modeling Research

With the prevalence of a circular economy, extended producer responsibility, and the maturity of intelligent manufacturing technology, Design for Remanufacture (DfRem) has become a new driving force for the profitability of the modern supply chain. DfRem activities occur at the stage of new product design but have a significant impact on subsequent remanufacturing operations. Based on the closed-loop supply chain operation systems with DfRem, we systematically explored the impact of DfRem on supply chain operation decisions through a case study and modeling analysis and built up a modeling research framework of DfRem-driven closed-loop supply chain (CLSC) operation decision-making. Our research identified DfRem-driven model design elements and discussed the modeling of DfRem-driven investment decision problems, involving different approaches to obtain DfRem investment (i.e., DfRem-driven horizontal or vertical supply chain cooperation) and the ownership of DfRem-level decision-making rights. Moreover, the DfRem-driven two-stage and multi-period modeling processes are elaborated in detail. The aim of this paper is to provide other scholars with a more comprehensive understanding of DfRem research issues, and to establish an integrated DfRem-driven research framework for subsequent scholars to better conduct modeling research on DfRem.

Priority of scientific and technological development "The transition to advanced digital, intelligent manufacturing technologies, robotic systems, new materials and methods of design, the creation of systems for processing large amounts of data, machine learning and artificial intelligence". Opening speech of the chairman of the priority council of RAS academician I.A. Kalyaev

Opening speech of the chairman of the priority council of RAS academician I.A. Kalyaev

A Systematic Disturbance Analysis Method for Resilience Evaluation: A Case Study in Material Handling Systems

With the development of intelligent manufacturing technology, the material handling system (MHS) faces larger resilience challenges that threaten the sustainability of the system. To evaluate system resilience, the disturbance that the system may experience and the system response need to be identified in advance. This paper proposes a systematic and innovative approach to performing resilience-related disturbance analysis, i.e., disturbance mode and effects analysis (DMEA). Using this method, the possible disturbance modes, their occurrence probabilities, and the quantitative effects on system performance can be collected in a bottom-up process, and the information can be applied to further resilience quantification. Moreover, a quantitative system resilience evaluation framework for the MHS based on DMEA and the Monte Carlo method is presented. Production is defined as the key performance index of the system and is monitored to reflect the resilience behavior of the system after the disturbance occurs. The resilience of a tire tread handing system is quantified in our case study, and the results show the effectiveness of our DMEA-based resilience evaluation method. We also find that a reasonable system configuration and maintenance strategy can effectively improve system resilience, and a trade-off can be made between resilience and cost.

Research on the Countermeasures for Training Technical Skills Talents in Intelligent Manufacturing Environment

Historical experience proves that the equipment manufacturing industry is a country's core competitiveness, and building an internationally competitive manufacturing industry is the only way for China to upgrade its national strength, safeguard national security, and build a world power. Since the implementation of the Made in China 2025 strategy in 2015, the national manufacturing industry is undergoing intensive transformation and upgrading, and the corresponding technical skills training has become a hot issue in the field of vocational education. In this paper, the objectives and connotations of Industry 4.0 and intelligent manufacturing are elaborated. At the same time, the ability model of technical skills talents under the intelligent manufacturing mode is constructed. The countermeasures for the cultivation of intelligent manufacturing technology skills are studied.

The impact of intelligent manufacturing elements on product design towards reducing production waste

With ever-increasing market competition and advances in technology, more and more countries are prioritizing for advanced and intelligent manufacturing technology as a top priority for improving product design and reducing production waste towards promoting economic growth. Consequently, this study empirically tests the set of intelligent manufacturing elements (IMEs) that affect product design towards minimizing production waste at mineral water factories in the Kurdistan region of Iraq. The results of this study were based on the data obtained from the mixed methods represented in a questionnaire survey and semi-structured interviews in the framework of the case study. The questionnaire survey already has been tested. The sample of the study was 269 respondents selected based on a stratified sampling technique. The criteria for choosing the respondents to be part of the study were based on the status of full-time employee of the organization. The findings showed that among the IMEs addressed in this study, each intelligent device and intelligent process had had a strong impact on improving product design, and hence the efficient use of manufacturing resources towards reducing manufacturing waste in the industrial organizations.

Bi-objective Flexible Job Shop Scheduling with Operation Overlapping Costs

Abstract Industry 4.0 brings a more flexible machine scheduling mode via intelligent manufacturing technologies. When each job consists of more than one operation, it may break the traditional constraint that the processing time segments of consecutive operations for a same job cannot overlap. This works studies a flexible job shop scheduling problem where consecutive operations of any job is allowed to be overlapped during processing, while the overlapping induces an extra processing cost. We establish a bi-objective mathematical model for the considered problem, aiming at the minimum makespan and the processing cost induced by the overlapping. We apply the Epsilon-constraint method to solve the model and produce the Pareto front. A brief framework of future research is provided as well.