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  • 1. Cui, Y.
    et al.
    Liu, Q.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ding, W.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liu, Y.
    Li, D.
    Research on milling temperature measuring tool embedded with NiCr/NiSi thin film thermocouple2018In: 51st CIRP Conference on Manufacturing Systems, Elsevier, 2018, Vol. 72, p. 1457-1462Conference paper (Refereed)
    Abstract [en]

    In order to measure the milling area temperature in-situ, the milling tool embedded with NiCr/NiSi thin film thermocouple (TFTC) is prepared. TFTC capable well temperature performance is embedded on the tool tip by successively depositing SiO2 insulating film, NiCr/NiSi thermoelectric film, and SiO2 protective film. Surface morphology and thin film properties are confirmed to achieve expectation by means of TEM and SEM. Imitation reflects that TFTC abrasion has minor effect on dynamic and static characteristic. The in-situ milling area temperature is successfully detected by TFTC temperature measuring tool in field test.

  • 2. Cui, Y.
    et al.
    Liu, Y.
    Wang, Xi Vincent
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Ding, W.
    Liu, Q.
    Research on measurement of cutting area temperature and its prediction model2018In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 13, no 3, p. 209-226Article in journal (Refereed)
    Abstract [en]

    In this paper, the temperature measuring tool based on NiCr/NiSi thin film thermocouple is developed. 6,061 aluminium alloys is selected as the experiment object. Based on the cutting area temperature result during field test, the central composite design is utilised, which contains the parameters of cutting speed, feed rate and cutting depth. Regarding each parameter, three levels are selected and then the second-order regression equation between cutting area temperature and three cutting parameters is established. The data of experimental measurement corresponds well with the mathematical prediction, which confirms that the experimental and mathematical methods are valid in the research on cutting area temperature.

  • 3.
    Lian, Binbin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Elastodynamic modeling and parameter sensitivity analysis of a parallelmanipulator with articulated traveling plate2019In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015Article in journal (Refereed)
    Abstract [en]

    This paper deals with the elastodynamic modeling and parameter sensitivity analysis of a parallel manipulator with articulated traveling plate (PM-ATP) for assembling large components in aviation and aerospace. In the elastodynamic modeling, the PM-ATP is divided into four levels, i.e., element, part, substructure, and the whole mechanism. Herein, three substructures, including translation, bar, and ATP, are categorized according to the composition of the PM-ATP. Based on the kineto-elastodynamic (KED) method, differential motion equations of lower levels are formulated and assembled to build the elastodynamic model of the upper level. Degrees of freedom (DoFs) at connecting nodes of parts and deformation compatibility conditions of substructures are considered in the assembling. The proposed layer-by-layer method makes the modeling process more explicit, especially for the ATP having complex structures and multiple joints. Simulations by finite element software and experiments by dynamic testing system are carried out to verify the natural frequencies of the PM-ATP, which show consistency with the results from the analytical model. In the parameter sensitivity analysis, response surface method (RSM) is applied to formulate the surrogate model between the elastic dynamic performances and parameters. On this basis, differentiation of performance reliability to the parameter mean value and standard variance are adopted as the sensitivity indices, from which the main parameters that greatly affect the elastic dynamic performances can be selected as the design variables. The present works are necessary preparations for future optimal design. They can also provide reference for the analysis and evaluation of other PM-ATPs.

  • 4.
    Lian, Binbin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Wang, Xi Vincent
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Static and dynamic optimization of a pose adjusting mechanism considering parameter changes during constructionIn: Article in journal (Refereed)
  • 5.
    Lian, Binbin
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.).
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Static and dynamic optimization of a pose adjusting mechanism considering parameter changes during construction2019In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 59, p. 267-277Article in journal (Refereed)
    Abstract [en]

    Having potentially high stiffness and good dynamic response, a parallel pose adjusting mechanism was proposed for being an attachment to a big serial robot of a macro-micro robotic system. This paper addresses its design optimization problem mainly concerning arrangements of design variables and objectives. Parameter changes during construction are added to the design variables in order to prevent the negative effects to the physical prototype. These parameter changes are interpreted as parameter uncertainty and modeled by probabilistic theory. For the objectives, both static and dynamic performances are simultaneously optimized by Pareto-based method. The involved performance indices are instantaneous energy based stiffness index, first natural frequency and execution mass. The optimization procedure is implemented as: (1) carrying out performance modeling and defining performance indices, (2) reformulating statistical objectives and probabilistic constraints considering parameter uncertainty, (3) conducting Pareto-based optimization with the aid of response surface method (RSM) and particle swarm optimization (PSO), (4) selecting optimal solution by searching for cooperative equilibrium point (CEP). By addressing parameter uncertainty and the best compromise among multiple objectives, the presented optimization procedure provides more reliable optimal parameters that would not be affected by minor parameter changes during construction, and less biased optimum between static and dynamic performances comparing with the conventional optimization methods. The proposed optimization method can also be applied to the other similar mechanisms.

  • 6.
    Liu, Sichao
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Yuquan
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Energy-efficient trajectory planning for an industrial robot using a multi-objective optimisation approach2018Conference paper (Refereed)
    Abstract [en]

    This paper presents an approach for energy-efficient trajectory planning of an industrial robot. A model that can be used to formulate the energy consumption of the robot with the kinematics constraints is developed. Given the trajectory in the Cartesian space, the septuple B-spline is applied in joint space trajectory planning to make the velocities, accelerations, and jerks bounded and continuous, with constraints on the initial and ending values. Then, energy-efficient optimisation problem with nonlinear constraints is discussed. Simulation results show that, the proposed approach is effective solution to trajectory planning, with ensuring a good energy improvement and fluent movement for the robot manipulators.

  • 7.
    Liu, Sichao
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Zhang, Yingfeng
    Northwestern Polytech Univ, Key Lab Contemporary Design & Integrated Mfg Tech, Minist Educ, Xian 710072, Shaanxi, Peoples R China.;Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen 518055, Guangdong, Peoples R China..
    Liu, Yang
    Linkoping Univ, Dept Management & Engn, SE-58183 Linkoping, Sweden.;Univ Vaasa, Dept Prod, Vaasa 65200, Finland..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    An 'Internet of Things' enabled dynamic optimization method for smart vehicles and logistics tasks2019In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 215, p. 806-820Article in journal (Refereed)
    Abstract [en]

    Centralized and one-way logistics services and the lack of real-time information of logistics resources are common in the logistics industry. This has resulted in the increased logistics cost, energy consumption, logistics resources consumption, and the decreased loading rate. Therefore, it is difficult to achieve efficient, sustainable, and green logistics services with dramatically increasing logistics demands. To deal with such challenges, a real-time information-driven dynamic optimization strategy for smart vehicles and logistics tasks towards green logistics is proposed. Firstly, an 'Internet of Things'-enabled real-time status sensing model of logistics vehicles is developed. It enables the vehicles to obtain and transmit real-time information to the dynamic distribution center, which manages value-added logistics information. Then, such information can be shared among logistics companies. A dynamic optimization method for smart vehicles and logistics tasks is developed to optimize logistics resources, and achieve a sustainable balance between economic, environmental, and social objectives. Finally, a case study is carried out to demonstrate the effectiveness of the proposed optimization method. The results show that it contributes to reducing logistics cost and fuel consumption, improving vehicles' utilization rate, and achieving real-time logistics services with high efficiency. reserved.

  • 8.
    Liu, Yongkui
    et al.
    Xidian Univ, Ctr Smart Mfg Syst, Sch Mechano Elect Engn, Xian, Shaanxi, Peoples R China..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, Xun
    Univ Auckland, Dept Mech Engn, Auckland, New Zealand..
    Jiang, Pingyu
    Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian, Shaanxi, Peoples R China..
    Cloud manufacturing: key issues and future perspectives2019In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052Article in journal (Refereed)
    Abstract [en]

    Since the introduction of the concept of cloud manufacturing in 2010, research on it has been ongoing for more than eight years, and much progress has been made. However, existing research indicates that people lack common and comprehensive understandings of some of the key issues with cloud manufacturing such as the concept, operation model, service mode, technology system, architecture, and essential characteristics. Moreover, few studies discuss in depth the relationships between cloud manufacturing and some closely related concepts such as cloud computing-based manufacturing, Cyber-Physical Systems (CPS), smart manufacturing, Industry 4.0, and Industrial Internet. Knowledge as a core supporting factor in cloud manufacturing has rarely been discussed systematically. Also, so far there has been no standardised definition for cloud manufacturing yet. All these are key issues to be further discussed and analysed in cloud manufacturing. In order to clarify the issues above and provide reference for future research and implementation, this paper conducts a comprehensive, systematic, and in-depth discussion and analysis of the aforementioned issues in cloud manufacturing and presents an alternative definition for cloud manufacturing based on the analysis of 12 existing definitions. Future perspectives of cloud manufacturing are also discussed with respect to both academic research and industrial implementation.

  • 9.
    Liu, Yongkui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Xidian Univ, Ctr Complex Syst, Sch Mechanoelect Engn, Xian, Shaanxi, Peoples R China.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Xi Vincent
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Xu, Xun
    Univ Auckland, Dept Mech Engn, Auckland, New Zealand..
    Zhang, Lin
    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing, Peoples R China..
    Scheduling in cloud manufacturing: state-of-the-art and research challenges2019In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 57, no 15-16, p. 4854-4879Article, review/survey (Refereed)
    Abstract [en]

    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 manufacturing services to consumers over the Internet. Scheduling is one of the critical means for achieving the aim of cloud manufacturing. Thus far, about 158 articles have been published on scheduling in cloud manufacturing. However, research on scheduling in cloud manufacturing faces numerous challenges. Thus, there is an urgent need to ascertain the current status and identify issues and challenges to be addressed in the future. Covering articles published on the subject over the past eight years, this article aims to provide a state-of-the-art literature survey on scheduling issues in cloud manufacturing. A detailed statistical analysis of the literature is provided based on the data gathered from the Elsevier's Scopus abstract and citation database. Typical characteristics of scheduling issues in cloud manufacturing are systematically summarised. A comparative analysis of scheduling issues in cloud manufacturing and other scheduling issues such as cloud computing scheduling, workshop scheduling and supply chain scheduling is also carried out. Finally, future research issues and challenges are identified.

  • 10.
    Liu, Yongkui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Yuquan
    KTH.
    Wang, Xi Vincent
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Zhang, L.
    China.
    Multi-agent-based scheduling in cloud manufacturing with dynamic task arrivals2018In: Procedia CIRP, Elsevier, 2018, p. 953-960Conference paper (Refereed)
    Abstract [en]

    Scheduling is a critical means for providing on-demand manufacturing services in cloud manufacturing. Multi-agent technologies provide an effective approach for addressing scheduling issues in cloud manufacturing, which, however, have rarely been used for solving the issue. This paper addresses scheduling issues in cloud manufacturing using multi-agent technologies. A multi-agent architecture for scheduling in cloud manufacturing is proposed firstly. Then, a corresponding multi-agent model is presented, which incorporates many-to-many negotiations based on an extended contract net protocol and takes into account dynamic task arrivals. Simulation results indicate the feasibility of the model and approach proposed.

  • 11. Senington, R.
    et al.
    Pataki, B.
    Hungary.
    Wang, Xi Vincent
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Using docker for factory system software management: Experience report2018In: Procedia CIRP, Elsevier, 2018, p. 659-664Conference paper (Refereed)
    Abstract [en]

    As factories become increasingly computerised, and with the increasing interest in Cyber-Physical-Systems and the Internet-of-Things, the issues of software management, deployment, configuration and integration are expected to become increasingly important. This paper reports on the ongoing experiences of using the Docker container technology in a major EU research project targeting smart factories. Docker is used to distribute, deploy and manage the configuration of multiple software modules between multiple teams and demonstrator sites in multiple locations, where each module can use its own mixture of protocols, programming languages and platforms.

  • 12.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, R.
    Case Western Reserve Univ, Dept Mech & Aerosp Engn, Cleveland, OH 44106 USA..
    Vancza, J.
    Hungarian Acad Sci, Inst Comp Sci & Control, Budapest, Hungary.;Budapest Univ Technol & Econ, Dept Mfg Sci & Engn, Budapest, Hungary..
    Krueger, J.
    Tech Univ, Inst Machine Tools & Factory Management, Berlin, Germany.;Fraunhofer Inst Prod Syst & Design Technol, Berlin, Germany..
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Makris, S.
    Univ Patras, Lab Mfg Syst & Automat, Patras, Greece..
    Chryssolouris, G.
    Univ Patras, Lab Mfg Syst & Automat, Patras, Greece..
    Symbiotic human-robot collaborative assembly2019In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 68, no 2, p. 701-726Article in journal (Refereed)
    Abstract [en]

    In human-robot collaborative assembly, robots are often required to dynamically change their pre-planned tasks to collaborate with human operators in a shared workspace. However, the robots used today are controlled by pre-generated rigid codes that cannot support effective human-robot collaboration. In response to this need, multi-modal yet symbiotic communication and control methods have been a focus in recent years. These methods include voice processing, gesture recognition, haptic interaction, and brainwave perception. Deep learning is used for classification, recognition and context awareness identification. Within this context, this keynote provides an overview of symbiotic human-robot collaborative assembly and highlights future research directions. 2019 Published by Elsevier Ltd on behalf of CIRP.

  • 13.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Kjellberg, Torsten J. A.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Editorial: Smart Manufacturing at CIRP CMS 20182018In: Procedia CIRP, ISSN 2212-8271, E-ISSN 2212-8271, Vol. 72, p. 1-2Article in journal (Refereed)
  • 14.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    Univ Skövde, Sch Engn Sci, Skövde, Sweden..
    Energy-efficient robot applications towards sustainable manufacturing2018In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 31, no 8, p. 692-700Article in journal (Refereed)
    Abstract [en]

    The cloud technology provides sustainable solutions to the modern industrial robotic cells. Within the context, the objective of this research is to minimise the energy consumption of robots during assembly in a cloud environment. Given a robot path and based on the inverse kinematics and dynamics of the robot from the cloud, a set of feasible configurations of the robot can be derived, followed by calculating the desirable forces and torques on the joints and links of the robot. Energy consumption is then calculated for each feasible configuration along the path. The ones with the lowest energy consumption are chosen. Since the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be applied to energy-efficient robotic assembly. This cloud-based energy-efficient approach for robotic applications can largely enhance the current practice as demonstrated by the results of three case studies, leading towards sustainable manufacturing.

  • 15.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, Liang
    Váncza, Jozsef
    A cloud-based approach for WEEE remanufacturing2014In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 63, no 1, p. 409-412Article in journal (Refereed)
    Abstract [en]

    The modern manufacturing industry calls for a new generation of integration models that are more interoperable, intelligent, adaptable and distributed. Evolved from service-oriented architecture, web-based manufacturing and cloud computing, cloud manufacturing is considered worldwide a new enabling technology for manufacturing enterprises to respond quickly and effectively to the changing global market. For Waste Electrical and Electronic Equipment (WEEE) in particular, it is a critical necessity to recycle, reuse and remanufacture WEEE products by setting up a cloud-based information system. In this paper, a novel service-oriented remanufacturing platform is proposed based on the cloud manufacturing concept.

  • 16.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Kemeny, Zsolt
    Vancza, Jozsef
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Human-robot collaborative assembly in cyber-physical production: Classification framework and implementation2017In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 66, no 1, p. 5-8Article in journal (Refereed)
    Abstract [en]

    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.

  • 17.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Lopez, Brenda N. N.
    Ijomah, Winifred
    Wang, Lihui
    Li, Jinhui
    A Smart Cloud-Based System for the WEEE Recovery/Recycling2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 6, article id 061010Article in journal (Refereed)
    Abstract [en]

    Waste electrical and electronic equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus, it is necessary to develop a distributed and intelligent system to support WEEE component recovery and recycling. In recent years, the Cloud concept has gained increasing popularity since it provides a service-oriented architecture (SOA) that integrates various resources over the network. Cloud manufacturing systems are proposed worldwide to support operational manufacturing processes. In this research, Cloud manufacturing is further extended to the WEEE recovery and recycling context. The Cloud services are applied in WEEE recovery and recycling processes by tracking and management services. These services include all the stakeholders from the beginning to the end of life of the electric and electronic equipment. A Cloud-based WEEE recovery system is developed to provide modularized recovery services on the Cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also proposed with the help of the Quick Respond code method.

  • 18.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Lopez N, B. N.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Li, J.
    Ijomah, W.
    A smart Cloud-based system for the WEEE Recovery/recycling2014In: ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference, 2014Conference paper (Refereed)
    Abstract [en]

    Waste Electrical and Electronic Equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus it is necessary to develop a distributed and intelligent system to support WEEE recovery and recycling. In recent years, the Cloud concept has gained increasing popularity since it provides a service-oriented architecture that integrates various resources over the network. Cloud Manufacturing systems are proposed world-wide to support operational manufacturing processes. In this research, Cloud Manufacturing is further extended to the WEEE recovery and recycling context. A Cloud-based WEEE Recovery system is developed to provide modularized recovery services on the Cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also proposed with the help of the Quick Respond code method.

  • 19.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Seira, A.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Classification, personalised safety framework and strategy for human-robot collaboration2018In: Proceedings of International Conference on Computers and Industrial Engineering, CIE, Curran Associates Inc. , 2018Conference paper (Refereed)
    Abstract [en]

    The modern manufacturing system calls for a safe, efficient and user-friendly working environment to meet the expectation of Industry 4.0 and Smart Manufacturing. The Human-Robot Collaboration is considered as one of the promising approaches and it attracts major research interest in both academia and industry. However, in the past years the reported research results focus more on the advanced robot controlling methods, while the uniqueness of each individual human is not included in the planning or control loop. In this research, multiple types of relationships between the human operator and robot are first classified into four major types. Then the safety framework and strategy is developed towards a personalised solution in a Human-Robot Collaboration cell. The proposed approach is then implemented and evaluated through case studies and quantifiable result comparisons.

  • 20.
    Wang, Xi Vincent
    et al.
    KTH, Centres, XPRES, Excellence in production research. KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    A cloud-based production system for information and service integration: an internet of things case study on waste electronics2017In: Enterprise Information Systems, ISSN 1751-7575, E-ISSN 1751-7583, Vol. 11, no 7, p. 952-968Article in journal (Refereed)
    Abstract [en]

    Cloud computing is the new enabling technology that offers centralised computing, flexible data storage and scalable services. In the manufacturing context, it is possible to utilise the Cloud technology to integrate and provide industrial resources and capabilities in terms of Cloud services. In this paper, a function block-based integration mechanism is developed to connect various types of production resources. A Cloud-based architecture is also deployed to offer a service pool which maintains these resources as production services. The proposed system provides a flexible and integrated information environment for the Cloud-based production system. As a specific type of manufacturing, Waste Electrical and Electronic Equipment (WEEE) remanufacturing experiences difficulties in system integration, information exchange and resource management. In this research, WEEE is selected as the example of Internet of Things to demonstrate how the obstacles and bottlenecks are overcome with the help of Cloud-based informatics approach. In the case studies, the WEEE recycle/recovery capabilities are also integrated and deployed as flexible Cloud services. Supporting mechanisms and technologies are presented and evaluated towards the end of the paper.

  • 21.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Digital twin-based WEEE recycling, recovery and remanufacturing in the background of Industry 4.02019In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 57, no 12, p. 3892-3902Article in journal (Refereed)
    Abstract [en]

    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 recovery is facing enormous challenges of diversified individuals, lack of product knowledge, distributed location, and so forth. On the other hand, the latest ICT provides new methods and opportunities for industrial operation and management. Thus, in this research digital twin and Industry 4.0 enablers are introduced to the WEEE remanufacturing industry. The goal is to provide an integrated and reliable cyber-avatar of the individual WEEE, thus forming personalised service system. The main contribution presented in this paper is the novel digital twin-based system for the WEEE recovery to support the manufacturing/remanufacturing operations throughout the product's life cycle, from design to recovery. Meanwhile, the international standard-compliant data models are also developed to support WEEE recovery services with high data interoperability. The feasibility of the proposed system and methodologies is validated and evaluated during implementations in the cloud and cyber-physical system.

  • 22.
    Wang, Xi vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    From Cloud manufacturing to Cloud remanufacturing: A Cloud-based approach for WEEE recovery2014In: Manufacturing Letters, ISSN 2213-8463, Vol. 2, no 4, p. 91-95Article in journal (Refereed)
    Abstract [en]

    The modern manufacturing industry calls for a new generation of integration models that are more interoperable, intelligent, adaptable and distributed. Evolved from service-oriented architecture, web-based manufacturing and Cloud computing, a Cloud manufacturing model has been discussed worldwide which enables manufacturing enterprises to respond quickly and effectively to the changing global market. Especially for Waste Electrical and Electronic Equipment (WEEE), it is a critical necessity to reuse, remanufacture, recycle and recover it by re-shaping the lifecycle management patterns. In this paper, recent WEEE research works are briefly reviewed. Next, a novel service-oriented remanufacturing platform is introduced based on the Cloud manufacturing concept.

  • 23.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    FUNCTION BLOCK-BASED INTEGRATION MECHANISMS FOR ADAPTIVE AND FLEXIBLE CLOUD MANUFACTURING2015In: PROCEEDINGS OF THE ASME 10TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2015, VOL 2, AMER SOC MECHANICAL ENGINEERS , 2015Conference paper (Refereed)
    Abstract [en]

    Cloud Computing is the new enabling technology that offers centralised computing, flexible data storage, and scalable services. In the manufacturing context, it is possible to extend the Cloud technology for integrating and provisioning manufacturing facilities and capabilities in terms of Cloud services. In this paper, a function block-based integration mechanism is developed to integrate various types of manufacturing facilities. A Cloud-based architecture is also deployed to provide a service pool which maintains these facilities in terms of manufacturing services. The proposed framework and mechanisms are evaluated by implementations. In practice, it is possible to establish an integrated manufacturing environment across multiple levels with the support of manufacturing Cloud and function blocks. It provides a flexible architecture as well as adaptive and integration methodologies for the Cloud manufacturing system.

  • 24.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Interoperability in cloud manufacturing and practice on private cloud structure for SMEs2017In: ASME 2017 12th International Manufacturing Science and Engineering Conference, MSEC 2017 collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing, ASME Press, 2017, Vol. 3Conference paper (Refereed)
    Abstract [en]

    In recent years, Cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of production paradigm. However, the interoperability issue still requires more research due to the heterogeneous environment caused by multiple Cloud services and applications developed in different platforms and languages. Therefore, this research aims to combat the interoperability issue in Cloud Manufacturing System. During implementation, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), are normally short of budget for hardware and software investment due to financial stresses, but they are facing multiple challenges required by customers at the same time including security requirements, safety regulations. Therefore in this research work, the proposed Cloud manufacturing system is specifically tailored for SMEs.

  • 25.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    WR cloud: a Novel WEEE Remanufacturing Cloud System2015In: 22nd CIRP Conference on Life Cycle Engineering, Elsevier, 2015, Vol. 29, p. 786-791Conference paper (Refereed)
    Abstract [en]

    Cloud manufacturing is a new manufacturing paradigm that offers manufacturing capabilities in terms of Cloud services. As a specific type of manufacturing, Waste Electrical and Electronic Equipment (WEEE) remanufacturing experiences difficulties in system integration, data exchange and resource management, especially when the products reach the end of lifecycle. Thus it is possible to introduce the Cloud manufacturing paradigm into WEEE remanufacturing environment, to overcome the obstacles and bottlenecks. In this paper, a novel Cloud-based system is developed to support WEEE remanufacturing. The WEEE recycle/recovery capabilities are integrated and deployed as flexible services in the Cloud. Supporting mechanisms and technologies are also developed, which are presented and evaluated via case studies.

  • 26.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, Liang
    From Cloud Manufacturing to Cloud Remanufacturing: A Cloud-Based Approach for WEEE2013In: Proceedings - 2013 IEEE 10th International Conference on e-Business Engineering, ICEBE 2013 / [ed] James, A; Fei, X; Chao, KM; Chung, JY, IEEE conference proceedings, 2013, p. 399-406Conference paper (Refereed)
    Abstract [en]

    The modern manufacturing industry calls for a new generation of integration models that are more interoperable, intelligent, adaptable and distributed. Evolved from service-oriented architecture, web-based manufacturing and Cloud Computing, Cloud Manufacturing model is discussed world-widely which enables manufacturing enterprises to respond quickly and effectively to the changing global market. Especially for Waste Electrical and Electronic Equipments, it is a critical necessity to reuse, remanufacture, recycle and recover energy by re-shaping the lifecycle management patterns. In this paper, recent Cloud Manufacturing approaches are reviewed. Next, a novel service-oriented remanufacturing platform is introduced based on Cloud Manufacturing paradigm. During case studies, a LCD television model is taken to evaluate the proposed Cloud Remanufacturing service mechanism and information management methodologies.

  • 27.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    ICMS: A Cloud-Based System for Production Management2015In: ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: INNOVATIVE PRODUCTION MANAGEMENT TOWARDS SUSTAINABLE GROWTH (AMPS 2015), PT II, Springer Berlin/Heidelberg, 2015, p. 444-451Conference paper (Refereed)
    Abstract [en]

    Modern production industry calls for a new generation of production systems. As a novel information technology, Cloud provides new service models and business opportunities to manufacturing industry. In this research, a Cloud-based manufacturing system is developed to support distributed production management. Recent Cloud manufacturing approaches are reviewed. The Cloud-based production management and localisation mechanisms are proposed and evaluated during case study. It is shown that the Cloud-based manufacturing system is capable of supporting distributed and customised production services and managements.

  • 28.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Goerdes, Reinhold
    FORMTEC Engn Serv GmbH, Bottrop, Germany..
    Interoperability in cloud manufacturing: a case study on private cloud structure for SMEs2018In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 31, no 7, p. 653-663Article in journal (Refereed)
    Abstract [en]

    In recent years, cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of manufacturing paradigm. However, it also brings a new challenge which is caused by multiple cloud services and applications developed by different vendors in different platforms and programming languages. Based on the literature review, most of the cloud manufacturing research have focused on either the system or methodology level, and there are limited research works concentrating on the heterogeneous manufacturing environment and the related interoperability issues. Therefore, this research aims to tackle especially the interoperability issue in the cloud manufacturing environment. The interoperability research in computing is firstly reviewed, and the cloud manufacturing research is classified from an interoperability's perspective. During cloud practice, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), have demands on interoperability security, and safety. Therefore, in this research, the proposed cloud manufacturing system is particularly tailored as a private cloud to achieve data and service interoperability, where the demands from SMEs are also fulfilled. The proposed system is implemented in a private manufacturing cloud structure with mobile access. The system is validated and evaluated by a case study. The quantifiable results confirm the feasibility and advantage of the proposed system, compared with the performance of conventional IT solutions.

  • 29.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. KTH, Centres, XPRES, Excellence in production research.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Mohammed, Abdullah
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Ubiquitous manufacturing system based on Cloud: A robotics application2017In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 45, p. 116-125Article in journal (Refereed)
    Abstract [en]

    Modern manufacturing industry calls for a new generation of production system with better interoperability and new business models. As a novel information technology, Cloud provides new service models and business opportunities for manufacturing industry. In this research, recent Cloud manufacturing and Cloud robotics approaches are reviewed. Function block-based integration mechanisms are developed to integrate various types of manufacturing facilities. A Cloud-based manufacturing system is developed to support ubiquitous manufacturing, which provides a service pool maintaining physical facilities in terms of manufacturing services. The proposed framework and mechanisms are evaluated by both machining and robotics applications. In practice, it is possible to establish an integrated manufacturing environment across multiple levels with the support of manufacturing Cloud and function blocks. It provides a flexible architecture as well as ubiquitous and integrated methodologies for the Cloud manufacturing system.

  • 30.
    Wang, Xi Vincent
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, X.
    Cloud manufacturing in support of sustainability2014In: ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference, ASME Press, 2014Conference paper (Refereed)
    Abstract [en]

    In a modern manufacturing business, collaborations not only exist among its own departments, but also among business partners. Cloud Manufacturing can assist this type of collaborations. As a new paradigm of manufacturing network, Cloud Manufacturing combines Cloud Computing with networked manufacturing under service-oriented architecture. It is set to fundamentally change how products are designed, manufactured, shipped and maintained. Besides the support to collaborative and intelligent manufacturing processes, it is also possible to realize sustainability in the Cloud Manufacturing paradigm. In this paper, recent Cloud Manufacturing approaches are discussed from the sustainable manufacturing perspective. The major difference between Cloud Manufacturing and web-based manufacturing systems are specifically discussed. Cloud-based methods are analyzed to support reasonable and logic strategies. It is believed that Cloud Manufacturing can provide a strong support to the manufacturing industry, in particular for sustainability.

  • 31.
    Wang, Xi Vincent
    et al.
    University of Auckland, New Zealand.
    Xu, X W
    University of Auckland, New Zealand.
    A Collaborative Product Data Exchange Environment Based on STEP2013In: International Journal of Computer Integrated Manufacturing, ISSN 0951-192X, Vol. 28, no 1, p. 75-86Article in journal (Refereed)
    Abstract [en]

    In the modern manufacturing context, CAD/CAM and CNC solutions are normally provided by different vendors, which gives rise to a heterogeneous application environment. Despite many integration approaches developed in the last decades, software integration and product data exchange are still challenging issues that need to be addressed. In this article, a collaborative product data exchange mechanism is proposed for a Distributed Interoperable Manufacturing Platform (DIMP). In this platform, STEP (ISO 10303) and STEP-NC (ISO 14649) data models are utilised to support the data flow. A novel data exchange mechanism is developed to provide the right amount and right level of product data subset to the users based on these models. This mechanism enables the users to work with a reasonable scope of product data, without interfering others. To realise this concept, data-extracting algorisms are developed to provide a customised data domain, and meta-data model compliant with STEP is proposed to guarantee data tractability. Moreover, synchronisation is catered for after the data set is processed.

  • 32.
    Wang, Xi Vincent
    et al.
    University of Auckland, New Zealand.
    Xu, X W
    University of Auckland, New Zealand.
    An Interoperable Solution for Cloud Manufacturing2013In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 29, no 4, p. 232-247Article in journal (Refereed)
    Abstract [en]

    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.

  • 33.
    Wang, Xi Vincent
    et al.
    University of Auckland, New Zealand.
    Xu, X W
    University of Auckland, New Zealand.
    Virtual Function Block Mechanism in the Cloud Manufacturing Environment2013In: Advanced Materials Research, ISSN 1022-6680, E-ISSN 1662-8985, Vol. 694-967, p. 2438-2441Article in journal (Refereed)
    Abstract [en]

    CManufacturing is a new manufacturing model that has evolved from Service-Oriented Architecture, networked manufacturing and CComputing. It provides intelligent, interoperable and distributed manufacturing model for the industry. This paper introduces a resource integration mechanism in the Cloud Manufacturing environment. Function Block technology is discussed from the Cloud Manufacturing perspective in detail. Next, a novel integration mechanism is proposed, namely the Virtual Function Block. Based on physical Function Blocks and software agents, Virtual Function Blocks are able to manipulate and integrate manufacturing resources via event states and data flows. During implementation, Creo Parametric was integrated as a Cloud Service with the help of VFBs to evaluate the mechanism.

  • 34.
    Wang, Xi Vincent
    et al.
    University of Auckland.
    Xu, Xun William
    University of Auckland.
    DIMP: An Interoperable Solution for Software Integration and Product Data Exchange2013In: International Journal of Enterprise Information Systems, ISSN 1548-1115, E-ISSN 1548-1123, Vol. 6, no 3, p. 291-314Article in journal (Refereed)
    Abstract [en]

    Today, globalisation has become one of the main trends of manufacturing business that has led to a world-wide decentralisation of resources amongst not only individual departments within one company but also business partners. However, despite the development and improvement in the last few decades, difficulties in information exchange and sharing still exist in heterogeneous applications environments. This article is divided into two parts. In the first part, related research work and integrating solutions are reviewed and discussed. The second part introduces a collaborative environment called distributed interoperable manufacturing platform, which is based on a module-based, service-oriented architecture (SOA). In the platform, the STEP-NC data model is used to facilitate data-exchange among heterogeneous CAD/CAM/CNC systems.

  • 35.
    Wang, Xi
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, X.
    Virtualise manufacturing capabilities in the cloud: Requirements, architecture and implementation2014In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 9, no 4, p. 348-368Article in journal (Refereed)
    Abstract [en]

    In recent years, cloud manufacturing concept has been proposed by taking advantage of cloud computing to enhance the performance of manufacturing industry. Cloud manufacturing can be perceived as two types, i.e., manufacturing version of computing cloud, and a distributed environment that is networked around manufacturing cloud. This paper discusses manufacturing resources, abilities and relevant essentials from the service-oriented perspective. The functional requirements of a cloud manufacturing environment are also discussed, along with an interoperable manufacturing system framework. Cloud resource integration methods have been developed based on the function block and software agent technologies. It is possible to achieve a collaborative, intelligent, and distributed environment via cloud manufacturing technologies.

  • 36.
    Zhang, Yongping
    et al.
    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China..
    Cheng, Ying
    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China..
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM).
    Zhong, Ray Y.
    Univ Hong Kong, Dept Ind & Mfg Syst Engn, Hong Kong, Peoples R China..
    Zhang, Yingfeng
    Northwestern Polytech Univ, Key Lab Contemporary Design & Integrated Mfg Tech, Minist Educ, Xian 710072, Shaanxi, Peoples R China..
    Tao, Fei
    Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China..
    Data-driven smart production line and its common factors2019In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 103, no 1-4, p. 1211-1223Article in journal (Refereed)
    Abstract [en]

    Due to the wide usage of digital devices and easy access to the edge items in manufacturing industry, massive industrial data is generated and collected. A data-driven smart production line (SPL), which is a basic cell in a smart factory, is derived primarily. This paper studies the data-driven SPL and its common factors. Firstly, common factors such as integration, data-driven, service collaboration, and proactive service of SPL are investigated. Then, a data-driven method including data self-perception, data understanding, decision-making, and precise control for implementing SPL is proposed. As a reference, the research of the common factors and the data-driven method could offer a systematic standard for both academia and industry. Moreover, in order to validate this method, this paper presents an industrial case by taking an energy consumption forecast and fault diagnosis based on energy consumption data in a prototype of LED epoxy molding compound (EMC) production lines for example.

  • 37. Zhao, Wenyan
    et al.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Yang, Jianxin
    Li, Bo
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A CLOUD-BASED APPROACH TO SUPPORT THE MOBILE PHONE RECYCLING INDUSTRY IN CHINA2016In: ASME 2016 11th International Manufacturing Science and Engineering Conference, MSEC 2016, American Society of Mechanical Engineers , 2016Conference paper (Refereed)
    Abstract [en]

    In recent years, the waste mobile phones are generated in large quantity in China. Those e-wastes gain more and more attention because of both the sharp increase in quantity and the recyclable resources they contain. Furthermore, the mobile phone recycling industry has experienced a trend of rapid growth as well. However, due to the lack of national policies and legislations, the recycling industry is now facing problems in recycling processes. Thus in this paper, mobile phone recycling industry in China is systematically analyzed and a Cloud-based approach is developed which integrates tracking, interaction and coordinator mechanism through the recycling processes. With the integration of various stakeholders, the system can provide integrated data system throughout the whole life cycle of the mobile phones for the policy maker, and provide guidance for the operations during recycling service for the recycling stakeholders.

1 - 37 of 37
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