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  • 251.
    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.
    VISION-ASSISTED AND 3D MODEL-BASED REMOTE ASSEMBLY2012In: Proceedings of International Conference on Innovative Design and Manufacturing, 2012Conference paper (Refereed)
  • 252.
    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.
    Onori, Mauro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Remote robotic assembly guided by 3D models linking to a real robot2014In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 63, no 1, p. 1-4Article in journal (Refereed)
    Abstract [en]

    This paper presents a 3D model-driven remote robotic assembly system. It constructs 3D models at runtime to represent unknown geometries at the robot side, where a sequence of images from a calibrated camera in different poses is used. Guided by the 3D models over the Internet, a remote operator can manipulate a real robot instantly for remote assembly operations. Experimental results show that the system is feasible to meet industrial assembly requirements with an acceptable level of modelling quality and relatively short processing time. The system also enables programming-free robotic assembly where the real robot follows the human's assembly operations instantly.

  • 253.
    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.

  • 254. Wang, Lihui
    et al.
    Nace, Adam
    A sensor-driven approach to Web-based machining2009In: Journal of Intelligent Manufacturing, ISSN 0956-5515, E-ISSN 1572-8145, Vol. 20, no 1, p. 1-14Article in journal (Refereed)
  • 255. Wang, Lihui
    et al.
    Nee, A.Y.C.
    Advanced Technologies for Collaborative Manufacturing2008In: Journal of Intelligent Manufacturing, ISSN 0956-5515, E-ISSN 1572-8145, Vol. 19, no 6, p. 623-624Article in journal (Refereed)
  • 256.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Orban, Peter
    Cunningham, Andrew
    Lang, Sherman
    Remote Real-Time CNC Machining for Web-Based Manufacturing2004In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 20, no 4, p. 563-571Article in journal (Refereed)
  • 257.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, B.
    Nee, A.Y.C.
    Vision-guided active collision avoidance for human-robot collaborations2013In: Manufacturing Letters, ISSN 2213-8463, Vol. 1, no 1, p. 5-8Article in journal (Refereed)
    Abstract [en]

    This paper reports a novel methodology of real-time active collision avoidance in an augmented environment, where virtual 3D models of robots and real camera images of operators are used for monitoring and collision detection. A prototype system is developed and linked to robot controllers for adaptive robot control, with zero robot programming for end users. According to the result of collision detection, the system can alert an operator, stop a robot, or modify the robot's trajectory away from an approaching operator. Through a case study, it shows that this method can be applied to real-world applications such as human-robot collaborative assembly to safeguard human operators.

  • 258.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Adamson, Göran
    Robotic assembly planning and control with enhanced adaptability through function blocks2015In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 77, no 1-4, p. 705-715Article in journal (Refereed)
    Abstract [en]

    Manufacturing companies today need to maintain a high level of flexibility and adaptability to deal with uncertainties on dynamic shop floors, including, e.g. cutting tool shortage, part supply interruption, urgent job insertion or delay and machine unavailability. Such uncertainties are characteristic in component assembly operations. Addressing the problem, we propose a new method using function blocks to achieve much improved adaptability in assembly planning and robot control. In this paper, we propose to use event-driven function blocks for robotic assembly, aiming to plan trajectory and execute assembly tasks in real time. It is envisioned that this approach will achieve better adaptability if applied to real-world applications.

  • 259. Wang, Lihui
    et al.
    Shen, Weiming
    DPP: An Agent-Based Approach for Distributed Process Planning2003In: Journal of Intelligent Manufacturing, ISSN 0956-5515, E-ISSN 1572-8145, Vol. 14, no 5, p. 429-439Article in journal (Refereed)
    Abstract [en]

    A changing shop floor environment characterized by larger variety of products in smaller batch sizes requires creating an intelligent and dynamic process planning system that is responsive and adaptive to the rapid adjustment of production capacity and functionality. In response to the requirement, this research proposes a new methodology of distributed process planning (DPP). The primary focus of this paper is on the architecture of the new process planning approach, using multi-agent negotiation and cooperation. The secondary focus is on the other supporting technologies such as machining feature-based planning and function block-based control. Different from traditional methods, the proposed approach uses two-level decision-making - supervisory planning and operation planning. The former focuses on product data analysis, machine selection, and machining sequence planning, while the latter considers the detailed working steps of the machining operations inside of each process plan and is accomplished by intelligent NC controllers. By the nature of decentralization, the DPP shows promise of improving system performance within the continually changing shop floor environment.

  • 260.
    Wang, Lihui
    et al.
    Integrated Manufacturing Technologies Institute, National Research Council of Canada .
    Shen, Weiming
    Hao, Qi
    An Overview of Distributed Process Planning and Its Integration with Scheduling2006In: International journal of computer applications in technology, ISSN 0952-8091, E-ISSN 1741-5047, Vol. 26, no 1-2, p. 3-14Article, review/survey (Refereed)
    Abstract [en]

    Process planning and scheduling are considered as two separate and distinct phases in manufacturing. Traditional approaches to these problems do not consider the constraints of both domains simultaneously and can only result in sub-optimal solutions. This separation becomes a barrier to further improving manufacturing performance. Most process planning and scheduling systems are off-line and centralized. The process plans generated off-line may become invalid at the time of plan execution. On the other hand, scheduling based on rigid process plans may have already lost the optimal options. Today, there is an increasing need for the integration of process planning and scheduling to generate more realistic and practical solutions. This paper provides a literature review on the integration of process planning and scheduling, particularly on agent-based approaches. It is followed by an overview of our approach toward distributed process planning and scheduling. The paper is finally concluded with future research opportunities.

  • 261. Wang, Lihui
    et al.
    Shen, Weiming
    Lang, Sherman
    Wise-ShopFloor: a web-based and sensor-driven shop floor environment2004In: Journal of Computing and Information Science in Engineering, ISSN 1530-9827, E-ISSN 1944-7078, Vol. 4, no 1, p. 56-60Article in journal (Refereed)
  • 262.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Shih, Albert J.
    Challenges in smart manufacturing2016In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 40, p. 1-1Article in journal (Other academic)
  • 263.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Törngren, Martin
    KTH, School of Industrial Engineering and Management (ITM), Machine Design (Dept.), Mechatronics.
    Onori, Mauro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Current status and advancement of cyber-physical systems in manufacturing2015In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 37, p. 517-527Article in journal (Refereed)
    Abstract [en]

    This paper presents the current status and the latest advancement of cyber-physical systems (CPS) in manufacturing. In order to understand CPS and its future potential in manufacturing, definitions and characteristics of CPS are explained and compared with cloud manufacturing concept. Research and applications are outlined to highlight the latest advancement in the field. CPS shows great promise in factories of the future in the areas of future trends as identified at the end of this paper.

  • 264.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Wang, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liu, Dawei
    Dynamic feature based adaptive process planning for energy-efficient NC machining2017In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 66, no 1, p. 441-444Article in journal (Refereed)
    Abstract [en]

    This paper presents a dynamic feature based adaptive process planning approach that can optimise machining, cost, machining time and energy consumption simultaneously. The material removal volume of a dynamic feature is refined into non-overlapping volumes removed respectively by a single machining operation in which unified cutting mode is performed. Benefitting from this refinement, energy consumption is estimated analytically based on instantaneous cutting force as a function of real cutting parameters. Moreover, the cutting parameters assigned to each machining operation are optimised effectively in the unified cutting mode. This novel approach enhances the energy efficiency of NC machining through process planning. (C) 2017 Published by Elsevier Ltd on behalf of CIRP.

  • 265.
    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.

  • 266. Wang, Lihui
    et al.
    WM, Shen
    H, Xie
    J, Neelamkavil
    A, Pardasani
    Collaborative conceptual design - state of the art and future trends2002In: COMPUTER-AIDED DESIGN, Vol. 34, p. 981-996Article in journal (Refereed)
  • 267. Wang, Lihui
    et al.
    Xi, F.
    Challenges in Design and Manufacturing2006In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 19, no 5, p. 409-410Article in journal (Refereed)
  • 268. Wang, Lihui
    et al.
    Xi, F.
    FAIM 20042005In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 21, no 4-5Article in journal (Refereed)
  • 269. Wang, Lihui
    et al.
    Xi, F
    Zhang, D
    Verner, M
    Design optimization and remote manipulation of a tripod2005In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 18, no 1, p. 85-95Article in journal (Refereed)
  • 270.
    Wang, Lihui
    et al.
    Integrated Manufacturing Technologies Institute, National Research Council of Canada.
    Xi, Fengfeng
    Zhang, Dan
    A parallel robotic attachment and its remote manipulation2006In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 22, no 5-6, p. 515-525Article in journal (Refereed)
    Abstract [en]

    This paper discusses a 3-dof (degree of freedom) parallel robotic attachment and its remote manipulation. This attachment is designed as a tripod that provides two rotary motions and one linear motion. The attachment can be mounted onto a variety of machines for different applications, including CNC milling machines, industrial robots, and CMM. Java technologies are used to develop a remote manipulation system for the parallel robotic attachment, including remote monitoring and control. The main difference of this system from the existing web-based or internet-based remote systems is the way to control the motion of the machine from a remote site. Instead of using a camera for monitoring, the tripod is modeled using 3D computer graphics with behavioral control nodes embedded.

    Compared with camera-based solutions, network traffic is largely reduced, thereby making real-time remote device manipulation practical on the web. Our parallel robotic attachment is one type of parallel kinematic mechanisms (PKM). With PKM emerging as a new way of building flexible systems or agile machines, its advantage over serial mechanism is also presented.

  • 271.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, Xun
    Special Section: Advances and Challenges in Cloud Manufacturing2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 4, article id 040301Article in journal (Other academic)
  • 272.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, Xun
    Univ Auckland, Auckland, New Zealand..
    Gao, Robert
    Case Western Reserve Univ, Cleveland, OH 44106 USA..
    Nee, Andrew Y. C.
    Natl Univ Singapore, Singapore, Singapore..
    Sustainable cybernetic manufacturing2019In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 57, no 12, p. 3799-3801Article in journal (Other academic)
  • 273. Wang, Lihui
    et al.
    Zhao, W.
    Ma'ruf, A.
    Hoshi, T.
    Setup-Less Fabrication Technology Incorporated with Machining Feature-Based CAD/CAM System for Low Volume and High Product-Mix Machining Centre Workshop1996Conference paper (Refereed)
  • 274.
    Wang, Peng
    et al.
    Case Western Reserve Univ, Dept Mech & Aerosp Engn, Cleveland, OH 44106 USA..
    Liu, Hongyi
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, Robert X.
    Case Western Reserve Univ, Dept Mech & Aerosp Engn, Cleveland, OH 44106 USA..
    Deep learning-based human motion recognition for predictive context-aware human-robot collaboration2018In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 67, no 1, p. 17-20Article in journal (Refereed)
    Abstract [en]

    Timely context awareness is key to improving operation efficiency and safety in human-robot collaboration (HRC) for intelligent manufacturing. Visual observation of human workers' motion provides informative clues about the specific tasks to be performed, thus can be explored for establishing accurate and reliable context awareness. Towards this goal, this paper investigates deep learning as a data driven technique for continuous human motion analysis and future HRC needs prediction, leading to improved robot planning and control in accomplishing a shared task. A case study in engine assembly is carried out to validate the feasibility of the proposed method.

  • 275.
    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.

  • 276.
    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.

  • 277.
    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.

  • 278.
    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.

  • 279.
    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.

  • 280.
    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.

  • 281.
    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.

  • 282.
    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.

  • 283.
    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.

  • 284.
    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.

  • 285.
    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.

  • 286.
    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.

  • 287.
    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.

  • 288.
    Wang, Yuquan
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Applicability analysis of generalized inverse kinematics algorithms with respect to manipulator geometric uncertainties2017In: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) / [ed] Bicchi, A Okamura, A, IEEE , 2017, p. 2813-2820Conference paper (Refereed)
    Abstract [en]

    Accurate kinematic models and measurements are needed in many robotic applications. However uncertainties related to joint angle measurements and manipulator geometry are unavoidable, especially when grasping and using different tools or when we do not have access to an accurate robot model, e.g. when we construct a robotic system by hand. The generalized inverse kinematics methods are not applicable when a manipulator stay inside its singular region. We derive the upper bounds on the joint measurement errors and geometric uncertainties, in order to guarantee that the open-chain serial manipulators stay outside the singular region. These bounds in other words enable en effective execution of generalized inverse kinematics methods for a robotic system which is prone to geometric uncertainties. In addition to the analytic derivation, We validate the proposed bounds through a trajectory tracing task performed by a PR2 robot simulator.

  • 289.
    Wang, Yuquan
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Reactive task-oriented redundancy resolution using constraint-based programming2016In: IEEE International Conference on Intelligent Robots and Systems, IEEE, 2016, p. 5689-5694Conference paper (Refereed)
    Abstract [en]

    Constraint based programming provides a versatile framework for combining several different constraints into a single robot control scheme. We take advantage of the redundancy of a robot manipulator to improve the execution of a reactive tracking task, in terms of a task-dependent measure which is a weighted sum of velocity transmissions along the current directions of motion. With inspiration from recent work, we provide analytical gradients and computable weights of the task-dependent measure, which enable us to include it in a reactive constraint based programming framework, without relying on inexact numerical approximations and manually tuning weights. The proposed approach is illustrated in a set of simulations, comparing the performance with a standard constraint based programming method.

  • 290.
    Wang, Yuquan
    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.
    Resolve reactive robot control with perturbed constraints using a second order cone programming approach2017In: 2017 13TH IEEE CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), IEEE , 2017, p. 124-129Conference paper (Refereed)
    Abstract [en]

    As a modular and reactive control approach, constraint-based programming helps us to formulate and solve complex robotic tasks in a systematic way. In different fields ranging from industrial manipulators to humanoids, robots are supposed to work in an uncertain environment. However, how to address uncertainties is missing in the state-of-the-art of different constraint-based programming frameworks. In this paper, we introduce a Second Order Cone Programming (SOCP) approach to integrate constraints with norm bounded uncertainties. The proposed SOCP is convex and through simulations with controlled uncertainty level, we can clearly tell that the proposed approach guarantees the constraints satisfaction compared to the state-of-the-art.

  • 291.
    Wen, L.
    et al.
    China.
    Gao, L.
    China.
    Li, X.
    China.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Zhu, J.
    China.
    A Jointed Signal Analysis and Convolutional Neural Network Method for Fault Diagnosis2018In: Procedia CIRP, Elsevier, 2018, p. 1084-1087Conference paper (Refereed)
    Abstract [en]

    Fault diagnosis plays a vital role in the modern industry. In this research, a joint vibration signal analysis and deep learning method for fault diagnosis is proposed. The vibration signal analysis is a well-established technique for condition monitoring, and deep learning has shown its potential in fault diagnosis. In the proposed method, the time-frequency technique, named as S transform, is applied to transfer the vibration signals to images, and then an improved convolutional neural network (CNN) is applied to classify these images. The results show the proposed method has achieved the significant improvement.

  • 292. Wu, D.
    et al.
    Rosen, D. W.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schaefera, D.
    Cloud-based manufacturing: Old wine in new bottles?2014In: Variety management in manufacturing: Proceedings of the 47th cirp conference on manufacturing systems, 2014, p. 94-99Conference paper (Refereed)
    Abstract [en]

    Cloud-based manufacturing (CBM), also referred to as cloud manufacturing, is a form of decentralized and networked manufacturing evolving from other relevant manufacturing systems such as web- and agent-based manufacturing. An ongoing debate on CBM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, programming models, file systems, operational processes, information and communication models, and new business models pertaining to CBM. One question, in particular, has often been raised: Is cloud-based manufacturing a new paradigm, or is it just old wine in newbottles? Based on the discussion of the key characteristics of CBM, the derivation of requirements that an ideal CBM system should satisfy, and a thorough comparison between CBM and other relevant manufacturing systems, we provide supporting evidence that allows us to conclude that CBM is definitely a new paradigm that will revolutionize manufacturing.

  • 293. Wu, Dazhong
    et al.
    Rosen, David W.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schaefer, Dirk
    Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation2015In: Computer-Aided Design, ISSN 0010-4485, E-ISSN 1879-2685, Vol. 59, p. 1-14Article in journal (Refereed)
    Abstract [en]

    Cloud-based design manufacturing (CBDM) refers to a service-oriented networked product development model in which service consumers are enabled to configure, select, and utilize customized product realization resources and services ranging from computer-aided engineering software to reconfigurable manufacturing systems. An ongoing debate on CBDM in the research community revolves around several aspects such as definitions, key characteristics, computing architectures, communication and collaboration processes, crowdsourcing processes, information and communication infrastructure, programming models, data storage, and new business models pertaining to CBDM. One question, in particular, has often been raised: is cloud-based design and manufacturing actually a new paradigm, or is it just "old wine in new bottles"? To answer this question, we discuss and compare the existing definitions for CBDM, identify the essential characteristics of CBDM, define a systematic requirements checklist that an idealized CBDM system should satisfy, and compare CBDM to other relevant but more traditional collaborative design and distributed manufacturing systems such as web- and agent-based design and manufacturing systems. To justify the conclusion that CBDM can be considered as a new paradigm that is anticipated to drive digital manufacturing and design innovation, we present the development of a smart delivery drone as an idealized CBDM example scenario and propose a corresponding CBDM system architecture that incorporates CBDM-based design processes, integrated manufacturing services, information and supply chain management in a holistic sense.

  • 294.
    Wu, Dazhong
    et al.
    Univ Cent Florida, Orlando, FL 32816 USA..
    Weiss, Brian A.
    NIST, Gaithersburg, MD 20899 USA..
    Kurfess, Thomas
    Georgia Inst Technol, Atlanta, GA 30332 USA..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Davis, Jim
    Univ Calif Los Angeles, Los Angeles, CA 90024 USA..
    Introduction to the special issue on smart manufacturing2018In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 48, p. 1-2Article in journal (Other academic)
  • 295. Xia, K.
    et al.
    Gao, L.
    Li, W.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Chao, K. -M
    A Q-learning based selective disassembly planning service in the cloud based remanufacturing system for WEEE2014In: 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]

    Cloud based approach for remanufacturing is becoming a new technical solution for sustainable management of Waste Electrical and Electronic Equipment (WEEE). This paper presents a service-oriented framework of a Cloud Based Remanufacturing System (CBRS) for WEEE. In remanufacturing of WEEE, disassembly plays an important role. However, complete disassembly is rarely an ideal solution due to the high disassembly cost, with the increasing customization and diversity, and more complex assembly processes of Electrical and Electronic Equipment (EEE). Selective disassembly focusing on disassembling only a few selected components is a better choice. In this paper, a Q-Learning based Selective Disassembly Planning (QL-SDP) approach embedded with a multi-criteria decision making model is developed. The multi-criteria decision making model is built according to the legislative and economic considerations of specific stakeholders of WEEE. And the QLSDP approach is used to achieve optimized selective disassembly planning. An implementation example has been used to verify and demonstrate the effectiveness and robustness of the approach. The developed QL-SDP approach is designed as a service implemented in the presented CBRS for WEEE.

  • 296. Xia, K.
    et al.
    Gao, L.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Li, W.
    Chao, K. -M
    A Semantic Information Services Framework for Sustainable WEEE Management Toward Cloud-Based Remanufacturing2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 6, article id 061011Article in journal (Refereed)
    Abstract [en]

    Sustainable management of waste electrical and electronic equipment (WEEE) has attracted escalating concerns of researchers and industries. Closer information linking among the participants in the products's lifecycle should take place. How to interoperate among the distributed and heterogeneous information systems of various participants is a challenge faced. Targeting the cloud-based remanufacturing, this article aims to develop a semantic information services framework for sustainable WEEE management. In the proposed framework, an ontology based approach is developed to integrate and represent the lifecycle information from multiple local data sources within an information services provider. Meanwhile, a semantic information services management platform is introduced for the advertisement, matchmaking and retrieval of semantic information services. Some relevant techniques used to build the framework are introduced extensively. A demonstration case study on waste LCD TV is used to illustrate the effectiveness and significance of the proposed framework.

  • 297. Xia, K.
    et al.
    Gao, L.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Li, W.
    Chao, K.-M.
    A simplified teaching-learning-based optimization algorithm for disassembly sequence planning2013In: Proceedings - 2013 IEEE 10th International Conference on e-Business Engineering, ICEBE 2013, IEEE , 2013, p. 393-398Conference paper (Refereed)
    Abstract [en]

    Disassembly plays an important role in recovery and remanufacturing of Waste Electrical and Electronic Equipment (WEEE). A novel Simplified Teaching-Learning-Based Optimization (STLBO) algorithm is proposed for optimization of Disassembly Sequence Planning (DSP). The proposed STLBO is on the basis of a teaching-learning-based optimization method which is a new population based meta-heuristic algorithms. In the proposed STLBO algorithm, three operators are designed namely Feasible Solution Generator (FSG), Teacher Phase Operator (TPO) and Learner Phase Operator (LPO). The proposed algorithm is successfully tested against previous best known solutions for a set of public benchmarks.

  • 298. Xia, K.
    et al.
    Gao, L.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Li, W.
    Li, X.
    Ijomah, W.
    Service-oriented disassembly sequence planning for electrical and electronic equipment waste2016In: Electronic Commerce Research and Applications, ISSN 1567-4223, E-ISSN 1873-7846, Vol. 20, p. 59-68Article in journal (Refereed)
    Abstract [en]

    Disassembly sequence planning plays an important role in the end-of-life treatment of electrical and electronic equipment waste (e-waste). Effective planning methods can improve recovery rates and reduce environmental impacts of e-waste. In previous work, neither mathematical models nor optimization algorithms offered a satisfactory solution for this multi-objective disassembly problem. We present a multi-objective model for the problem and a modified teaching-learning-based optimization (MTLBO) algorithm to find the Pareto-optimal frontier. We use numerical simulations to demonstrate and verify the effectiveness and robustness of the algorithm. To do effective disassembly planning, all the participants in the lifecycle of e-waste should work together. Disassembly and recovery of e-waste involve complex processes across the lifecycle. Information support services, disassembly modeling and optimization services must be integrated using computer networks. We also propose a service-oriented framework to support business integration for the participants in the e-waste lifecycle. Effective and optimized disassembly planning can be achieved by invoking the related distributed services. The proposed framework is a novel e-business application for the end-of-life treatment of e-waste. © 2016 Elsevier B.V.

  • 299. Xia, Kai
    et al.
    Gao, Liang
    Chao, Kuo-Ming
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A Cloud-based Disassembly Planning Approach towards Sustainable Management of WEEE2015In: 2015 IEEE 12TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE), IEEE , 2015, p. 203-208Conference paper (Refereed)
    Abstract [en]

    Waste Electrical and Electronic Equipment (WEEE) is becoming an important and challenging waste stream in terms of quantity and toxicity. Developing technical solutions for sustainable management of WEEE is becoming a global trend. Disassembly planning plays an important role in End-of-Life treatment of WEEE. Effective disassembly planning can improve the recovery rate and reduce the environmental impact of WEEE significantly. Targeting sustainable WEEE management, this paper aims to propose a cloud-based approach for disassembly planning. The approach provides a comprehensive and standardized service-oriented environment for distributed information sharing, disassembly modeling, evaluation and optimization.

  • 300. Xu, X.W.
    et al.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, London, UK.
    Rong, Yiming
    STEP-NC and function blocks for interoperable manufacturing2006In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 3, no 3, p. 297-308Article in journal (Refereed)
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