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The purpose of this paper is to enhance control accuracy, energy efficiency and productivity of customized industrial robots by the proposed multi-objective trajectory optimization approach. To obtain accurate dynamic matching torques of the robot joints with optimal motion, an improved dynamic model built by a novel parameter identification method has been proposed.

This paper proposes a novel multi-objective optimal approach to minimize the time and energy consumption of robot trajectory. First, the authors develop a reliable dynamic parameters identification method to obtain joint torques for formulating the normalized energy optimization function and dynamic constraints. Then, optimal trajectory variables are solved by converting the objective function into relaxation constraints based on second-order cone programming and Runge–Kutta discrete method to reduce the solving complexity.

Extensive experiments via simulation and in real customized robots are conducted. The results of this paper illustrate that the accuracy of joint torque predicted by the proposed model increases by 28.79% to 79.05% over the simplified models used in existing optimization studies. Meanwhile, under the same solving efficiency, the proposed optimization trajectory consumes a shorter time and less energy compared with the existing optimization ones and the polynomial trajectory.

A novel time-energy consumption optimal trajectory planning method based on dynamic identification is proposed. Most existing optimization methods neglect the effect of dynamic model reliability on energy efficiency optimization. A novel parameter identification approach and a complete dynamic torque model are proposed. Experimental results of dynamic matching torques verify that the control accuracy of optimal robot motion can be significantly improved by the proposed model.

Sensorless passive lead-through programming (LTP) is a promising physical human-robot interaction technology that enables manual trajectory demonstrations based on gravity and friction compensation. The major difficulty lies in static friction compensation during LTP start-up. Instead of static friction compensation, conventional methods only compensate for Coulomb friction after the joint velocity exceeds a threshold. Therefore, conventional start-up external torques must overcome static friction. When the static friction is considerable, it is difficult for conventional LTP to start up and make small movements. This paper aims to decrease the start-up external torque and improve the small movement performance.

This paper reveals a novel usage of a high-gain position-loop in industrial robot applications aimed at sensitively detecting external torque during start-up. Then, the static friction is partly compensated by Coulomb friction to facilitate start-up. In addition, a detailed transition method between the proposed start-up and conventional passive LTP is proposed based on a finite state machine.

Experiments are implemented on the ROKAE XB4 robot to verify the effectiveness of the proposed external torque detection. Compared with the conventional LTP method, the proposed LTP method significantly decreases the start-up external torque and facilitates small movements.

This paper proposes and verifies a novel start-up method of sensorless LTP based on a start-up external torque detection and a transition method between start-up and conventional LTP. This research improves the LTP start-up performance, especially for industrial robots with large static friction.

In the last decade, cloud manufacturing (CMfg) has attracted considerable attention from academia and industry worldwide. It is widely accepted that the design and analysis of cloud manufacturing architecture (CMfg-A) are the basis for developing and applying CMfg systems. However, in existing studies, analysis of the status, development process and internal characteristics of CMfg-A is lacking, hindering an understanding of the research hotspots and development trends of CMfg-A. Meanwhile, effective guidance is lacking on the construction of superior CMfg-As. The purpose of this paper is to review the relevant research on CMfg-A via identification of the main layers, elements, relationships, structure and functions of CMfg-A to provide valuable information to scholars and practitioners for further research on key CMfg-A technologies and the construction of CMfg systems with superior performance.

This study systematically reviews the relevant research on CMfg-A across transformation process to internal characteristics by integrating quantitative and qualitative methods. First, the split and reorganization method is used to recognize the main layers of CMfg-A. Then, the transformation process of six main layers is analysed through retrospective analysis, and the similarities and differences in CMfg-A are obtained. Subsequently, based on systematic theory, the elements, relationships, structure and functions of CMfg-A are inductively studied. A 3D printing architecture design case is conducted to discuss the weakness of the previous architecture and demonstrate how to improve it. Finally, the primary current trends and future opportunities are presented.

By analyzing the transformation process of CMfg-A, this study finds that CMfg-A resources are developing from tangible resources into intangible resources and intelligent resources. CMfg-A technology is developing from traditional cloud computing-based technology towards advanced manufacturing technology, and CMfg-A application scope is gradually expanding from traditional manufacturing industry to emerging manufacturing industry. In addition, by analyzing the elements, relationships, structure and functions of CMfg-A, this study finds that CMfg-A is undergoing a new generation of transformation, with trends of integrated development, intelligent development, innovative development and green development. Case study shows that the analysis of the development trend and internal characteristics of the architecture facilitates the design of a more effective architecture.

This paper predominantly focuses on journal articles and some key conference papers published in English and Chinese. The reason for considering Chinese articles is that CMfg was proposed by the Chinese and a lot of Chinese CMfg-A articles have been published in recent years. CMfg is suitable for the development of China’s manufacturing industry because of China’s intelligent manufacturing environment. It is believed that this research has reached a reliable comprehensiveness that can help scholars and practitioners establish new research directions and evaluate their work in CMfg-A.

Prior studies ignore the identification and analysis of development process and internal characteristics for the current development of CMfg-A, including the main layers identification of different CMfg-As and the transformation process analysis of these main layers, and in-depth analysis of the inner essence of CMfg-A (such as its elements, relationships, structure and functions). This study addresses these limitations and provides a comprehensive literature review.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Cloud manufacturing (CMfg) is a networked manufacturing mode that promotes the agile, service-oriented, green and intelligent development of the manufacturing industry. Although some scholars have reviewed related studies of CMfg from multiple perspectives, these reviews are not fully systematic or well justified and fail to fully reveal the key characteristics in the development process of CMfg. The purpose of this paper is to systematically review the relevant research on CMfg via identification of key characteristics of definition, architecture, supporting technology and application of CMfg to provide critical information in decision support for the innovation and development of CMfg.

This study systematically reviews the relevant research on CMfg across theoretical methods to technical applications by integrating quantitative and qualitative methods. Word cloud method is used to quantitatively analyse the structure and feature of different definitions of CMfg. The principle of System Science is used to explore the basic components and functions of various CMfg architectures and their common and differing characteristics. A multi-level technology framework is developed to explore the development status of CMfg supporting technologies. A multi-stage application classification is proposed to reveal the application status of CMfg.

Through literature review, this study found that CMfg architecture is currently dominated by general architectures and lacks architectures that fit the actual enterprise characteristics; CMfg supporting technology is mature in the traditional cloud computing-based technology, but it is still weak in the development of virtualization and servitization technology, service scheduling technology; CMfg application is still in the initial stage and still lacks a relatively complete system application. By analysing the development status of CMfg, this study also identified potential research directions of CMfg in information management, service composition and evaluation, system application and sustainable development and other aspects.

This paper predominantly focuses on journal articles and some key conference papers published in English and Chinese. Chinese articles account for more than half of the total. The reason is that CMfg was proposed by the Chinese and CMfg is suitable for the development of China's manufacturing industry because of China's intelligent manufacturing environment. It is believed that this research has reached a reliable comprehensiveness that can help scholars and practitioners establish new research directions and evaluate their work in CMfg.

Prior literature reviews ignore the identification and analysis of key feature identification for the current development of CMfg, including common and unique feature identification of different CMfg architectures and functions, multi-layer analysis and interpretation of CMfg technology and different stage analysis of CMfg applications. This study addresses these limitations and provides a comprehensive literature review.

The human and technology have integrated, and distinctive characteristics of different societies have intertwined with technology. Thus, technology constitutes the reflection of the society, where it exists, in economic, social, and political domains. The desires, expectations, and needs of people have affected the change of technology in time. This effect contains different domains in itself. Life has changed since the 1980s under the leadership of means of informatics, and following the 1990s, internet technology have opened the doors of an informatics era whose effect is being highly sensed today. In addition to its importance, it creates significant changes and effects on individuals, society, culture, and other domains. When significant changes in technology and digitalization have combined with the globalization of information and communication, the resulting problems have begun to spread faster.

In this study, which was performed for examining the digital conflicts arising in business infrastructure, literature was reviewed thoroughly. In the first part of the study, the conceptual framework of business infrastructure was examined and tried to be clarified. Moreover, it was intended to convey the commencement of the technologies used, and their following processes. Then, it was urged upon clarifications regarding business processes and digitalization of business processes, and by referring to the implementations of technologies – used in business processes – in the domain of digitalization, structural examinations were conveyed from the literature. Finally, the issues of digital conflicts and cyber security occurring in business infrastructure, which are being expressed as more prominent factors, were clarified.

This chapter reviews the recent developments at the intersection of personalization and AI in marketing and related fields. We provide a formal definition of personalized policy and review the methodological approaches available for personalization. We discuss scalability, generalizability, and counterfactual validity issues and briefly touch upon advanced methods for online/interactive/dynamic settings. We then summarize the three evaluation approaches for static policies – the Direct method, the Inverse Propensity Score (IPS) estimator, and the Doubly Robust (DR) method. Next, we present a summary of the evaluation approaches for special cases such as continuous actions and dynamic settings. We then summarize the findings on the returns to personalization across various domains, including content recommendation, advertising, and promotions. Next, we discuss the work on the intersection between personalization and welfare. We focus on four of these welfare notions that have been studied in the literature: (1) search costs, (2) privacy, (3) fairness, and (4) polarization. We conclude with a discussion of the remaining challenges and some directions for future research.

This paper aims to present an overall framework of big data-based analytics to optimize the production performance of additive manufacturing (AM) process.

Four components, namely, big data application, big data sensing and acquisition, big data processing and storage, model establishing, data mining and process optimization were presented to comprise the framework. Key technologies including the big data acquisition and integration, big data mining and knowledge sharing mechanism were developed for the big data analytics for AM.

The presented framework was demonstrated by an application scenario from a company of three-dimensional printing solutions. The results show that the proposed framework benefited customers, manufacturers, environment and even all aspects of manufacturing phase.

This study only proposed a framework, and did not include the realization of the algorithm for data analysis, such as association, classification and clustering.

The proposed framework can be used to optimize the quality, energy consumption and production efficiency of the AM process.

This paper introduces the concept of big data in the field of AM. The proposed framework can be used to make better decisions based on the big data during manufacturing process.