Ying Cheng

Bio: Ying Cheng is an academic researcher from Beihang University. The author has contributed to research in topics: Cloud manufacturing & Computer science. The author has an hindex of 19, co-authored 52 publications receiving 3454 citations. Previous affiliations of Ying Cheng include Hong Kong Polytechnic University & University of Michigan.

Cloud manufacturing: a new manufacturing paradigm

Abstract: Combining with the emerged technologies such as cloud computing, the Internet of things, service-oriented technologies and high performance computing, a new manufacturing paradigm – cloud manufacturing CMfg – for solving the bottlenecks in the informatisation development and manufacturing applications is introduced. The concept of CMfg, including its architecture, typical characteristics and the key technologies for implementing a CMfg service platform, is discussed. Three core components for constructing a CMfg system, i.e. CMfg resources, manufacturing cloud service and manufacturing cloud are studied, and the constructing method for manufacturing cloud is investigated. Finally, a prototype of CMfg and the existing related works conducted by the authors' group on CMfg are briefly presented.

CCIoT-CMfg: Cloud Computing and Internet of Things-Based Cloud Manufacturing Service System

Abstract: Recently, Internet of Things (IoT) and cloud computing (CC) have been widely studied and applied in many fields, as they can provide a new method for intelligent perception and connection from M2M (including man-to-man, man-to-machine, and machine-to-machine), and on-demand use and efficient sharing of resources, respectively. In order to realize the full sharing, free circulation, on-demand use, and optimal allocation of various manufacturing resources and capabilities, the applications of the technologies of IoT and CC in manufacturing are investigated in this paper first. Then, a CC- and IoT-based cloud manufacturing (CMfg) service system (i.e., CCIoT-CMfg) and its architecture are proposed, and the relationship among CMfg, IoT, and CC is analyzed. The technology system for realizing the CCIoT-CMfg is established. Finally, the advantages, challenges, and future works for the application and implementation of CCIoT-CMfg are discussed.

Cloud manufacturing: a computing and service-oriented manufacturing model:

Abstract: Combining the emerged advanced technologies (such as cloud computing, ‘internet of thing’, virtualization, and service-oriented technologies, advanced computing technologies) with existing advanced manufacturing models and enterprise ‘informationization’ technologies, a new computing- and service-oriented manufacturing model, called cloud manufacturing (CMfg), is proposed. The concept, architecture, core enabling technologies, and typical characteristics of CMfg are discussed and investigated, as well as the differences and relationship between cloud computing and CMfg. Four typical CMfg service platforms, i.e. public, private, community, and hybrid CMfg service platforms, are introduced. The key advantages and challenges for implementing CMfg are analysed, as well as the key technologies and main research findings.

Big Data in product lifecycle management

Abstract: Recently, “Big Data” has attracted not only researchers’ but also manufacturers’ attention along with the development of information technology. In this paper, the concept, characteristics, and applications of “Big Data” are briefly introduced first. Then, the various data involved in the three main phases of product lifecycle management (PLM) (i.e., beginning of life, middle of life, and end of life) are concluded and analyzed. But what is the relationship between these PLM data and the term “Big Data”? Whether the “Big Data” concept and techniques can be employed in manufacturing to enhance the intelligence and efficiency of design, production, and service process, and what are the potential applications? Therefore, in order to answer these questions, the existing applications of “Big Data” in PLM are summarized, and the potential applications of “Big Data” techniques in PLM are investigated and pointed out.

Advanced manufacturing systems: socialization characteristics and trends

Abstract: Since 1960s, with the development of societal and related technologies, many advanced manufacturing systems (AMSs) and modes have been put forward, and they have attracted the attention of a large number of researchers in manufacturing, information and management fields. However, existing studies are mainly focused on the specific theoretical research of each AMS, and the horizontal comparison of the difference and evolution of these AMSs are not significant. Furthermore, most of the existing studies try to realize concrete technical implementation, and discussions on the relationship among these AMSs and social factors are relatively rare. Therefore, this paper aims to address this issue, and a brief overview of the development process of AMSs is first presented. Next, a tri-view model is established to analyze the evolution and socialization characteristics of AMSs. It is found that the sharing of manufacturing resources and capabilities, the value creation carriers, the value measuring criteria, the composition of the value chain and enterprise collaboration, and the user participation in manufacturing are all moving towards socialization. It is essential that the evolution and development of AMSs should also adapt this trend towards socialization in order to achieve better sharing of limited resources and efficient adding of value.

The internet of things: a survey

Abstract: In recent year, the Internet of Things (IoT) has drawn significant research attention. IoT is considered as a part of the Internet of the future and will comprise billions of intelligent communicating `things'. The future of the Internet will consist of heterogeneously connected devices that will further extend the borders of the world with physical entities and virtual components. The Internet of Things (IoT) will empower the connected things with new capabilities. In this survey, the definitions, architecture, fundamental technologies, and applications of IoT are systematically reviewed. Firstly, various definitions of IoT are introduced; secondly, emerging techniques for the implementation of IoT are discussed; thirdly, some open issues related to the IoT applications are explored; finally, the major challenges which need addressing by the research community and corresponding potential solutions are investigated.

Internet of Things in Industries: A Survey

Abstract: Internet of Things (IoT) has provided a promising opportunity to build powerful industrial systems and applications by leveraging the growing ubiquity of radio-frequency identification (RFID), and wireless, mobile, and sensor devices. A wide range of industrial IoT applications have been developed and deployed in recent years. In an effort to understand the development of IoT in industries, this paper reviews the current research of IoT, key enabling technologies, major IoT applications in industries, and identifies research trends and challenges. A main contribution of this review paper is that it summarizes the current state-of-the-art IoT in industries systematically.

Industry 4.0: state of the art and future trends

Abstract: Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines ...

Digital twin-driven product design, manufacturing and service with big data

Abstract: Nowadays, along with the application of new-generation information technologies in industry and manufacturing, the big data-driven manufacturing era is coming. However, although various big data in the entire product lifecycle, including product design, manufacturing, and service, can be obtained, it can be found that the current research on product lifecycle data mainly focuses on physical products rather than virtual models. Besides, due to the lack of convergence between product physical and virtual space, the data in product lifecycle is isolated, fragmented, and stagnant, which is useless for manufacturing enterprises. These problems lead to low level of efficiency, intelligence, sustainability in product design, manufacturing, and service phases. However, physical product data, virtual product data, and connected data that tie physical and virtual product are needed to support product design, manufacturing, and service. Therefore, how to generate and use converged cyber-physical data to better serve product lifecycle, so as to drive product design, manufacturing, and service to be more efficient, smart, and sustainable, is emphasized and investigated based on our previous study on big data in product lifecycle management. In this paper, a new method for product design, manufacturing, and service driven by digital twin is proposed. The detailed application methods and frameworks of digital twin-driven product design, manufacturing, and service are investigated. Furthermore, three cases are given to illustrate the future applications of digital twin in the three phases of a product respectively.