Xi Vincent Wang

Bio: Xi Vincent Wang is an academic researcher from Royal Institute of Technology. The author has contributed to research in topics: Cloud manufacturing & Cloud computing. The author has an hindex of 19, co-authored 83 publications receiving 1689 citations. Previous affiliations of Xi Vincent Wang include University of Auckland.

An interoperable solution for Cloud manufacturing

Abstract: Cloud manufacturing is a new concept extending and adopting the concept of Cloud computing for manufacturing. The aim is to transform manufacturing businesses to a new paradigm in that manufacturing capabilities and resources are componentized, integrated and optimized globally. This study presents an interoperable manufacturing perspective based on Cloud manufacturing. A literature search has been undertaken regarding Cloud architecture and technologies that can assist Cloud manufacturing. Manufacturing resources and capabilities are discussed in terms of Cloud service. A service-oriented, interoperable Cloud manufacturing system is proposed. Service methodologies are developed to support two types of Cloud users, i.e., customer user and enterprise user, along with standardized data models describing Cloud service and relevant features. Two case studies are undertaken to evaluate the proposed system. Cloud technology brings into manufacturing industry with a number of benefits such as openness, cost-efficiency, resource sharing and production scalability.

Scheduling in cloud manufacturing: state-of-the-art and research challenges

Abstract: For the past eight years, cloud manufacturing as a new manufacturing paradigm has attracted a large amount of research interest worldwide. The aim of cloud manufacturing is to deliver on-demand man ...

Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.0

Abstract: The waste electrical and electronic equipment (WEEE) recovery can be categorised into two types, i.e. recycling at the material level and remanufacturing at the component level. However, the WEEE r...

Human-robot collaborative assembly in cyber-physical production: Classification framework and implementation

Abstract: The production industry is moving towards the next generation of assembly, which is conducted based on safe and reliable robots working in the same workplace alongside with humans. Focusing on assembly tasks, this paper presents a review of human-robot collaboration research and its classification works. Aside from defining key terms and relations, the paper also proposes means of describing human-robot collaboration that can be relied on during detailed elaboration of solutions. A human-robot collaborative assembly system is developed with a novel and comprehensive structure, and a case study is presented to validate the proposed framework. © 2017.

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.

From cloud computing to cloud manufacturing

Abstract: Cloud computing is changing the way industries and enterprises do their businesses in that dynamically scalable and virtualized resources are provided as a service over the Internet. This model creates a brand new opportunity for enterprises. In this paper, some of the essential features of cloud computing are briefly discussed with regard to the end-users, enterprises that use the cloud as a platform, and cloud providers themselves. Cloud computing is emerging as one of the major enablers for the manufacturing industry; it can transform the traditional manufacturing business model, help it to align product innovation with business strategy, and create intelligent factory networks that encourage effective collaboration. Two types of cloud computing adoptions in the manufacturing sector have been suggested, manufacturing with direct adoption of cloud computing technologies and cloud manufacturing-the manufacturing version of cloud computing. Cloud computing has been in some of key areas of manufacturing such as IT, pay-as-you-go business models, production scaling up and down per demand, and flexibility in deploying and customizing solutions. In cloud manufacturing, distributed resources are encapsulated into cloud services and managed in a centralized way. Clients can use cloud services according to their requirements. Cloud users can request services ranging from product design, manufacturing, testing, management, and all other stages of a product life cycle.

Characterising the Digital Twin: A systematic literature review

Abstract: While there has been a recent growth of interest in the Digital Twin, a variety of definitions employed across industry and academia remain. There is a need to consolidate research such to maintain a common understanding of the topic and ensure future research efforts are to be based on solid foundations. Through a systematic literature review and a thematic analysis of 92 Digital Twin publications from the last ten years, this paper provides a characterisation of the Digital Twin, identification of gaps in knowledge, and required areas of future research. In characterising the Digital Twin, the state of the concept, key terminology, and associated processes are identified, discussed, and consolidated to produce 13 characteristics (Physical Entity/Twin; Virtual Entity/Twin; Physical Environment; Virtual Environment; State; Realisation; Metrology; Twinning; Twinning Rate; Physical-to-Virtual Connection/Twinning; Virtual-to-Physical Connection/Twinning; Physical Processes; and Virtual Processes) and a complete framework of the Digital Twin and its process of operation. Following this characterisation, seven knowledge gaps and topics for future research focus are identified: Perceived Benefits; Digital Twin across the Product Life-Cycle; Use-Cases; Technical Implementations; Levels of Fidelity; Data Ownership; and Integration between Virtual Entities; each of which are required to realise the Digital Twin.