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  • 301. Xu, Yuefei
    et al.
    Song, Ronggong
    Korba, Larry
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council Canada,.
    Shen, Weiming
    Lang, Sherman
    Distributed Device Networks With Security Constraints2005In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 1, no 4, p. 217-225Article in journal (Refereed)
    Abstract [en]

    In today's globalized business world, outsourcing, joint ventures, mobile and cross-border collaborations have led to work environments distributed across multiple organizational and geographical boundaries. The new requirements of portability, configurability and interoperability of distributed device networks put forward new challenges and security risks to the system's design and implementation. There are critical demands on highly secured collaborative control environments and security enhancing mechanisms for distributed device control, configuration, monitoring, and interoperation. This paper addresses the collaborative control issues of distributed device networks under open and dynamic environments. The security challenges of authenticity, integrity, confidentiality, and execution safety are considered as primary design constraints. By adopting policy-based network security technologies and XML processing technologies, two new modules of Secure Device Control Gateway and Security Agent are introduced into regular distributed device control networks to provide security and safety enhancing mechanisms. The core architectures, applied mechanisms, and implementation considerations are presented in detail in this paper.

  • 302. Yamaguchi, H.
    et al.
    Shih, A. J.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Dods, B. G.
    Bartles, D. L.
    Wavering, A. J.
    Fratini, L.
    Ragai, I.
    Mears, L.
    Moylan, S. P.
    Paul, B.
    Mullany, B.
    Budzinski, J.
    History of NAMRI and NAMRC2019In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 34, p. 3-5Article in journal (Refereed)
  • 303.
    Yang, Chen
    et al.
    Univ Hong Kong, Dept Ind & Mfg Syst Engn, HKU ZIRI Lab Phys Internet, Hong Kong, Peoples R China. an, Shulin.
    Lan, Shulin
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Research on coordinated development between metropolitan economy and gistics using big data and Haken model2019In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 57, no 4, p. 1176-1189Article in journal (Refereed)
    Abstract [en]

    To quantitatively study the relationship and mutual effects between tropolitan economy and logistics is an important, yet pending issue, ich can scientifically guide the urban planning and investment. rough the identified evaluation indexes of metropolitan logistics and onomic development, this paper first builds up an evaluation process del of metropolitan economic and logistics development, based on big ta analytics (BDA), the entropy evaluation method, and the maximum viation method. BDA can help extract the exact data about the dicators of metropolitan economy and logistics. Then a Haken model is opted to ravel out the dynamic co-evolutionary law of economy and gistics in five Chinese cities, which complements the above static aluation. The results show that the economic development is an order rameter and plays a key role in the coordinated development of tropolitan logistics and economy. However, from 2013 to 2014, these ve cities had not established an orderly evolved positive-feedback chanism through which economic development promotes the coordinated velopment of metropolitan logistics and economic development.

  • 304. Yang, Y.
    et al.
    Gao, R. X.
    Fan, Z.
    Wang, J.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Cloud-based prognosis: Perspective and challenge2014Conference paper (Refereed)
    Abstract [en]

    Comprehensive acquisition, distribution, and utilization of information about machine equipment and/or processes across spatial boundaries for improved productivity and decision have increasingly become the hallmark of advanced manufacturing. The emergence of cloud computing has created ample opportunities to achieve this goal. This paper presents a review of the state-of-the-art of prognosis technique for manufacturing and its future development motivated by the cloud infrastructure. Prevailing methods of prognosis are summarized, and their respective performance is comparatively evaluated. Basic principles and recent advances in cloud computing, as well as its application to cloud manufacturing, are introduced. Based on the survey, the concept of cloud-based prognosis is proposed, and its architecture as well as associated challenges are discussed.

  • 305.
    Yao, Bitao
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. School of Mechanical and Electronic Engineering Wuhan University of Technology Wuhan China; Hubei Key Laboratory of Broadband Wireless Communication and Sensor Networks Wuhan University of Technology Wuhan China.
    Zhou, Z.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, W.
    Liu, Q.
    Sensor-less external force detection for industrial manipulators to facilitate physical human-robot interaction2018In: Journal of Mechanical Science and Technology, ISSN 1738-494X, E-ISSN 1976-3824, Vol. 32, no 10, p. 4909-4923Article in journal (Refereed)
    Abstract [en]

    Sensor-less external force detection is important for industrial robots which are usually not equipped with external force sensors to be applied in physical human-robot interaction (pHRI). This paper adopts the dynamic models of the robot in both dynamic mode and quasistatic mode to detect the external force. In the dynamic mode, the inertia and friction parameters of the robot are identified with the weighted least squares. The excitation trajectory for parameter identification is optimised. The un-modelled peak points in the joint torque residual are removed by a statistical method. The torque changes of joints in quasi-static mode which are equivalent to the joint pre-sliding friction is modelled with a lumped parameter model, generalised Maxwell slip (GMS) element model. Therefore, there is no need for the switching between the friction models in different modes and this and facilitates the application of dynamic model in the external force detection. The dynamic models of robots both in dynamic mode and quasi-static mode and their effectiveness for external force detection in pHRI are verified by experimental results.

  • 306.
    Yao, Bitao
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Wuhan University of Technology, China.
    Zhou, Z.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, W.
    Liu, Q.
    Liu, A.
    Sensorless and adaptive admittance control of industrial robot in physical human−robot interaction2018In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 51, p. 158-168Article in journal (Refereed)
    Abstract [en]

    As industrial robots are applied in manufacturing industry on a large-scale and human intelligence is regarded as an important part in manufacturing, physical human−robot interaction (pHRI) which integrates the strength and accuracy of robot with human operator's ability of task cognition has drawn the attention of both academia and industry. However, an industrial robot without extra force/torque sensor for interacting force monitoring cannot be used directly in pHRI, and research on pHRI of industrial robots remains a challenge. In this research, a comprehensive dynamic model of an industrial robot in both dynamic mode and quasi-static mode is obtained to calculate the external force produced by human operator in pHRI and enables sensorless pHRI for industrial robots even in the environment with ambient vibration. Particularly, the dynamics in the process of mode switching which has not been investigated by researchers is studied and compensated by an empirical but effective method. Admittance control is used to transfer the detected force into reference position and velocity of the robot. RBF (Radial Basis Function) network is used to update the damping parameter online in order to reduce the contact force change and the contact force which makes pHRI more natural and easier. The stability of the controller is also discussed. The proposed methods of external force detection and adaptive admittance control show satisfactory behaviour in the experiments.

  • 307.
    Yao, Bitao
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. Wuhan Univ Technol, Sch Mech & ElWuhan Univ Technol, Hubei Key Lab Broadband Wireless Commun & Sensor, Wuhan 430070, Hubei, Peoples R China..
    Zhou, Zude
    Wuhan Univ Technol, Sch Mech & Elect Engn, Wuhan 430070, Hubei, Peoples R China..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Xu, Wenjun
    Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Hubei, Peoples R China.;Wuhan Univ Technol, Hubei Key Lab Broadband Wireless Commun & Sensor, Wuhan 430070, Hubei, Peoples R China..
    Yan, Junwei
    Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Hubei, Peoples R China.;Wuhan Univ Technol, Hubei Key Lab Broadband Wireless Commun & Sensor, Wuhan 430070, Hubei, Peoples R China..
    Liu, Quan
    Wuhan Univ Technol, Sch Informat Engn, Wuhan 430070, Hubei, Peoples R China.;Wuhan Univ Technol, Hubei Key Lab Broadband Wireless Commun & Sensor, Wuhan 430070, Hubei, Peoples R China..
    A function block based cyber-physical production system for physical human robot interaction2018In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 48, p. 12-23Article in journal (Refereed)
    Abstract [en]

    Human-robot collaboration (HRC) is becoming a trend in manufacturing industry. However, the dramatic changes of requirements from the market put a higher demand for the flexibility of manufacturing systems. Cyber-Physical Production System (CPPS) which offers benefits of autonomy, self-organisation, and interoperability can be adopted to increase the flexibility of manufacturing systems. IEC 61499 (International Electrotechnical Commission) function blocks (FBs) are modularised and reusable software components for distributed industrial control. It is a suitable technology to realise a CPPS. Therefore, CPPS and FBs can be combined to realise the HRC system. This paper proposes a framework and the implementation method of IEC 61499 FB based CPPS for physical human-robot interaction (pHRI) which is type of HRC. An industrial robot based CPPS for pHRI is decomposed into modularised FBs that can be networked to fulfil manufacturing tasks. An energy consumption FB based on a novel empirical energy consumption model is also added to the system for energy consumption monitoring of the Robot. An assembly case is used to demonstrate the feasibility of the proposed system. Results show that the FB based CPPS for pHRI possesses the potential capability for HRC based assembly. The future work is also discussed.

  • 308. Yeung, Millan K.
    et al.
    Wang, Lihui
    Orban, Peter
    Development of Machining Topology Knowledge Base2003Conference paper (Refereed)
  • 309. Yin, S.
    et al.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    He, G.
    Liu, X.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Experimental evaluation on texture of flank face on tool wear in chamfer milling of stainless steel2018In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 99, no 9-12, p. 2929-2937Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel grinding enabled texture, ‘V’ shaped texture (VST), on flank face. To implement the texture on a cutting performance, a set of chamfering experiments of stainless steel materials used as 3C product shell usually are presented. Cutting forces, surface qualities, and tool wear are measured and compared, of which results show that both smallest surface roughness and longest tool life are achieved by using a 30° VST chamfer tool. By comparing the results, a clear conclusion can be drawn that texture types and angles are not independent factors to cutting performance; therefore, a suitable combination of texture types and texture angles can provide a significant improvement of tool life and surface quality.

  • 310.
    Yin, S.
    et al.
    School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin, 150080, China.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A machine learning based energy efficient trajectory planning approach for industrial robots2019In: Procedia CIRP, Elsevier B.V. , 2019, p. 429-434Conference paper (Refereed)
    Abstract [en]

    Towards an energy efficient trajectory planning of industrial robot (IR), this paper proposes a machine learning based approach. Within the context, the IR’s movements are digitalised in joint space first, which allows using data attributes to represent IR’s trajectories. Moreover, a set of designed trajectories which can address IRs workspace are followed by the IR, and meanwhile, the energy consumption is measured. Then data sets are generated by combining the trajectory data and measured energy consumption data, and they are used to train a machine learning model. On top of that, the trained model provides a fitness function to evolution based or swarm-intelligence based algorithms to obtain a near-optimal or optimal trajectory. Finally, a simplified case study is demonstrated to validate the proposed method. The method provides a direct connection between joint control and energy efficiency objective, by which the solution space can be obviously relaxed, compared to the existing methods.

  • 311.
    Yue, C.
    et al.
    China.
    Gao, H.
    China.
    Liu, X.
    China.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Liang, S. Y.
    China.
    Analytical prediction of part dynamics and process damping for machining stability analysis2018In: Procedia CIRP, Elsevier, 2018, p. 1463-1468Conference paper (Refereed)
    Abstract [en]

    The milling of titanium alloy thin-walled parts is confronted with the double challenges of hard to machined materials and hard machined structures. Aiming at the problem that the effect of the damping process is significant and difficult to measure in the process of machining titanium thin-walled parts, the mathematical model of the process damping is established. The tangential and radial ploughing force coefficients that characterize the damping of the process are obtained based on the power spectral density matrix and the principle of energy balance. The structural dynamic modification method is used to solve the nonlinear problem of the workpiece characteristics with the material removal and the change of the relative position of the tool and the workpiece. The time delay differential equation which considers the damping effect of the process and the dynamic characteristic of the workpiece is solved by the full-discretization method, and the three-dimensional stability lobe diagram of the milling thin-walled parts is obtained. A series of experiments have been conducted to verify the accuracy of the stability prediction.

  • 312.
    Yue, Caixu
    et al.
    Harbin Univ Sci & Technol, Harbin 150080, Heilongjiang, Peoples R China..
    Gao, Haining
    Harbin Univ Sci & Technol, Harbin 150080, Heilongjiang, Peoples R China..
    Liu, Xianli
    Harbin Univ Sci & Technol, Harbin 150080, Heilongjiang, Peoples R China..
    Liang, Steven Y.
    Georgia Inst Technol, Atlanta, GA 30332 USA..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    A review of chatter vibration research in milling2019In: CHINESE JOURNAL OF AERONAUTICS, ISSN 1000-9361, Vol. 32, no 2, p. 215-242Article, review/survey (Refereed)
    Abstract [en]

    Chatter is a self-excited vibration of parts in machining systems. It is widely present across a range of cutting processes, and has an impact upon both efficiency and quality in production processing. A great deal of research has been dedicated to the development of technologies that are able to predict and detect chatter. The purpose of these technologies is to facilitate the avoidance of chatter during cutting processes, which leads to better surface precision, higher productivity, and longer tool life. This paper summarizes the current state of the art in research regarding the problems of how to arrive at stable chatter prediction, chatter identification, and chatter control/suppression, with a focus on milling processes. Particular focus is placed on the theoretical relationship between cutting chatter and process damping, tool runout, and gyroscopic effect, as well as the importance of this for chatter prediction. The paper concludes with some reflections regarding possible directions for future research in this field. 2019 Chinese Society of Aeronautics and Astronautics.

  • 313. Zhang, D.
    et al.
    Wang, Lihui
    Centre for Intelligent Automation, University of Skövde, Sweden.
    Gao, Z.
    Su, X.
    On performance enhancement of parallel kinematic machine2013In: Journal of Intelligent Manufacturing, ISSN 0956-5515, E-ISSN 1572-8145, Vol. 24, no 2, p. 267-276Article in journal (Refereed)
    Abstract [en]

    This paper proposes a spatial three degrees of freedom (DOF) parallel kinematic machine enhanced by a passive leg and a web-based remote control system. First, the geometric model of the parallel kinematic machine is addressed. In the mechanism, a fourth kinematic link—a passive link connecting the base center to the moving platform center—is introduced. Each of the three parallel limbs is actuated by one prismatic joint, respectively. The additional link has three passive DOF, namely two rotations around x and y axes and one translation along z axis. With the existence of this link, the unwanted motion of the tool (located in the moving platform) is constrained. The fourth link also enhances the global stiffness of the structure and distributes the torque from machining. With the kinematic model, a web-based remote control approach is applied. The concept of the web-based remote manipulation approach is introduced and the principles behind the method are explored in detail. Finally, a remote manipulation is demonstrated to the proposed structure using web-based remote control concept.

  • 314. Zhang, Dan
    et al.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute.
    Lang, Sherman Y.
    Parallel Kinematic Machines: Design, Analysis and Simulation in an Integrated Virtual Environment2005In: Journal of mechanical design (1990), ISSN 1050-0472, E-ISSN 1528-9001, Vol. 127, p. 580-588Article in journal (Refereed)
  • 315. Zhang, Y.
    et al.
    Liu, Sichao
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Northwestern Polytechnical University, Shaanxi, China.
    Liu, Y.
    Yang, H.
    Li, M.
    Huisingh, D.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    The ‘Internet of Things’ enabled real-time scheduling for remanufacturing of automobile engines2018In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 185, p. 562-575Article in journal (Refereed)
    Abstract [en]

    Typical challenges that managers of remanufacturing face are composed of the lack of timely, accurate, and consistent information of remanufacturing resources. Therefore, it is difficult to implement real-time production scheduling for the shop floor. To address this problem, the authors applied the concept of the ‘Internet of Things’ to the remanufacturing of automobile engines to form an Internet of Manufacturing Things environment. Under the Internet of Manufacturing Things, an identification technology for disassembled engine parts was designed, and the real-time status of the remanufacturable resources can be monitored. Based on the captured remanufacturing information, a real-time production scheduling method was developed, and a mathematical model was developed to achieve cost reduction, dynamic management of remanufacturable resources, and energy consumption decrease. To obtain an optimal solution, a Pareto-based optimization method was used. Finally, a case study was performed to analyze the effectivity of the proposed method. The results showed that the remanufacturing cost and energy consumption were reduced by 34% and 34% respectively, and the worker load rate was more balanced. These improvements can contribute to more sustainable development and greener production within the remanufacturing industry, especially for remanufacturing of automobile engines.

  • 316.
    Zhang, Yuyan
    et al.
    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan, Hubei, Peoples R China..
    Li, Xinyu
    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan, Hubei, Peoples R China..
    Gao, Liang
    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan, Hubei, Peoples R China..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wen, Long
    Huazhong Univ Sci & Technol, State Key Lab Digital Mfg Equipment & Technol, Wuhan, Hubei, Peoples R China..
    Imbalanced data fault diagnosis of rotating machinery using synthetic oversampling and feature learning2018In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 48, p. 34-50Article in journal (Refereed)
    Abstract [en]

    Imbalanced data problems are prevalent in the real rotating machinery applications. Traditional data-driven diagnosis methods fail to identify the fault condition effectively for lack of enough fault samples. Therefore, this study proposes an effective three-stage fault diagnosis method towards imbalanced data. First, a new synthetic oversampling approach called weighted minority oversampling (WMO) is devised to balance the data distribution. It adopts a new data synthesis strategy to avoid generating incorrect or unnecessary samples. Second, to select useful features automatically, an enhanced deep auto-encoder (DA) approach is adopted. DA is improved in two aspects: 1) a new cost function based on maximum correntropy and sparse penalty is designed to learn sparse robust features; 2) a fine-tuning operation with a self-adaptive learning rate is developed to ensure the good convergence performance. Finally, the C4.5 decision tree identifies the learned features. The proposed method named WMODA is evaluated on 25 benchmark imbalanced datasets. It achieves better results than five well-known imbalanced data learning methods. It is also evaluated on a real engineering dataset. The experimental results show that WMODA can detect more fault samples than the traditional data-driven methods.

  • 317. 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.

  • 318. Zhong, Ray
    et al.
    Xu, Xun
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Food supply chain management: systems, implementations, and future research2017In: Industrial management + data systems, ISSN 0263-5577, E-ISSN 1758-5783, Vol. 117, no 9, p. 2085-2114Article, review/survey (Refereed)
    Abstract [en]

    Purpose - The purpose of this paper is to review the food supply chain management (FSCM) in terms of systems and implementations so that observations and lessons from this research could be useful for academia and industrial practitioners in the future. Design/methodology/approach - A systematical and hierarchical framework is proposed in this paper to review the literature. Categorizations and classifications are identified to organize this paper. Findings - This paper reviews total 192 articles related to the data-driven systems for FSCM. Currently, there is a dramatic increase of research papers related to this topic. Looking at the general interests on FSCM, research on this topic can be expected to increase in the future. Research limitations/implications - This paper only selected limited number of papers which are published in leading journals or with high citations. For simplicity without generality, key findings and observations are significant from this research. Practical implications - Some ideas from this paper could be expanded into other possible domains so that involved parties are able to be inspired for enriching the FSCM. Future implementations are useful for practitioners to conduct IT-based solutions for FSCM. Social implications - As the increasing of digital devices in FSCM, large number of data will be used for decision-makings. Data-driven systems for FSCM will be the future for a more sustainable food supply chain. Originality/value - This is the first attempt to provide a comprehensive review on FSCM from the view of data-driven IT systems.

  • 319. Zhong, Ray Y.
    et al.
    Xu, Xun
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    IoT-enabled Smart Factory Visibility and Traceability using Laser-scanners2017In: 45TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 45) / [ed] Wang, L Fratini, L Shih, AJ, 2017, p. 1-14Conference paper (Refereed)
    Abstract [en]

    Smart Factory is one of the critical components in Industry 4.0 which is our next industrial generation. This paper introduces an Internet of Things (IoT) -enabled Smart Factory Visibility and Traceability Platform (iVTP for short) to ultimately achieve real-time production visualization within a smart factory. iVTP uses IoT technology to identify various manufacturing objects. Specifically, radio frequency identification (RFID) devices are used for converting various resources into smart manufacturing objects (SMOs) and their interactions thus are able to real-time reflect the production operations and behaviors. By innovatively using a laser-scanner in the shopfloor, iVTP is able to real-time display the movements of various SMOs and twin the real-time RFID data to show their states. A Cloud-based system architecture which enables all the services packaged and deployed in a Cloud allows typical end-users to easily define their production logics, download useful services, and develop their customized services. Several demonstrative scenarios are presented to show how iVTP can facilitate the typical decision-making, production and logistics operations in a smart factory. (C) 2017 The Authors. Published by Elsevier B.V.

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