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  • 301.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Fratini, Livan
    Shih, Albert J.
    Latest developments in manufacturing processes at NAMRC 452017In: JOURNAL OF MANUFACTURING PROCESSES, ISSN 1526-6125, Vol. 28, p. 411-412Article in journal (Other academic)
  • 302.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Gao, R.
    Ragai, I.
    An integrated cyber-physical system for cloud manufacturing2014In: ASME 2014 International Manufacturing Science and Engineering Conference, ASME Press, 2014, Vol. 1Conference paper (Refereed)
    Abstract [en]

    This paper presents an integrated cyber-physical system for remote accessibility and controllability of factory equipment, e.g. CNC machines and robots. It is enabled by combining 3D models, sensor data and camera images in real-time. The aim of this research is to significantly reduce network traffic for much improved accessibility and controllability of any cyber-physical systems over the Internet. The ultimate goal is to build cloudbased services of monitoring, process planning, machining and assembly in decentralised environment. This paper covers the basis of the approach, system architecture and implementation, and a case study of remote control of a robotic assembly cell. Compared with camera-based systems, our approach consumes less than 1% of its network bandwidth, feasible and practical as a future cloud-based solution.

  • 303.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Gao, Robert X.
    Condition Monitoring and Control for Intelligent Manufacturing2006Collection (editor) (Refereed)
  • 304.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Gao, Robert X.
    Preface2006In: Condition Monitoring and Control for Intelligent Manufacturing, Springer London, 2006, p. v-viiChapter in book (Refereed)
  • 305.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Givehchi, M.
    Adamson, G.
    Holm, M.
    A Sensor-Driven 3D Model-Based Approach to Remote Real-Time Monitoring2011In: CIRP Annals – Manufacturing Technology, ISSN 0007-8506, Vol. 60, no 1, p. 493-496Article in journal (Refereed)
    Abstract [en]

    This paper presents an integrated approach for remote real-time monitoring of manufacturing operations. It is enabled by using virtual 3D models driven by real sensor data. The objectives of this research are twofold: (1) to significantly reduce network traffic for real-time monitoring over the Internet; and (2) to increase the controllability of manufacturing systems from anywhere in a decentralised environment. Particularly, this paper covers the principle of the approach, system architecture, prototype implementation, and a case study of remote control of a robotic assembly cell. Compared with camera-based monitoring systems, our approach only consumes less than 1% of its network bandwidth, feasible and practical as a web-based portable solution.

  • 306.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Högskolan i Skövde, Institutionen för teknik och samhälle, Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Givehchi, Mohammad
    Web-DPP: An Adaptive Approach to Planning and Monitoring of Job-Shop Machining Operations2011In: Proceedings of the 7th CIRP International Conference on Digital Enterprise Technology, 2011, p. 411-420Conference paper (Refereed)
    Abstract [en]

    Utilising the existing IT infrastructure, the objective of this research is to develop an integrated Web-based distributed process planning system (Web-DPP) for job-shop machining operations and their runtime execution monitoring. Our approach tries to engage a dispersed working group in a collaborative environment, allowing the team members to share real-time information through the Web-DPP. This paper analyses the challenges, and presents both the system design specification and the latest development of the Web-DPP system. Particularly, it proposes a two-tier architecture for effective decision making and introduces a set of event-driven function blocks for bridging the gap between high-level planning and low-level execution functions. By connecting to a Wise-ShopFloor framework, it enables real-time execution monitoring during the machining operations, locally or remotely. The closed-loop information flow makes adaptive planning possible.

  • 307.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Givehchi, Mohammad
    Schmidt, Bernard
    Adamson, Göran
    A Function Block Enabled Robotic Assembly Planning and Control System with Enhanced Adaptability2012In: Proceedings of the 45th CIRP Conference on Manufacturing Systems, 2012, p. 194-201Conference paper (Refereed)
  • 308.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Haghighi, Azadeh
    Combined strength of holons, agents and function blocks in cyber-physical systems2016In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 40, p. 25-34Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel approach to implementing cyber-physical systems (CPS) using the combined strength of holons, agents and function blocks. Within the context, a CPS is represented by a holarchy of multiple holons. Each holon possesses a logical part and a physical part, which mimic the cyber and physical entities of the CPS. During implementation, the two parts of a holon are realised by agents and function blocks for information processing and materials processing, respectively. The objective of this research is to provide a concept map and associate a CPS with holons, agents and function blocks for the ease of system implementation in decentralised or cloud environment.

  • 309.
    Wang, Lihui
    et al.
    Integrated Manufacturing Technologies Institute, National Research Council of Canada .
    Hao, Qi
    Shen, Weiming
    A Novel Function Block Based Integration Approach to Process Planning and Scheduling with Execution Control2007In: International Journal of Manufacturing Technology and Management (IJMTM), ISSN 1368-2148, E-ISSN 1741-5195, Vol. 11, no 2, p. 228-250Article in journal (Refereed)
    Abstract [en]

    In today's decentralised business environment, manufacturing enterprises are implementing advanced distributed manufacturing planning and control strategies to adapt to and win the fluctuating global market. Within the context, this paper presents a novel approach to the integration of process planning, scheduling and execution in dynamic machining shop floors. Based on the concept of distributed process planning (DPP), function blocks are adopted as information carriers to optimise and specialise the nonlinear process plans (NLPP) progressively throughout the three planning stages: supervisory planning, execution control and operation planning, with scheduling functionality integrated seamlessly. Architecture of DPP and function block based integration are proposed, followed by a system functional design using IDEF0 methodology. The advantages of adopting function block technology are demonstrated and recent research results as well as future directions are pointed out in this paper.

  • 310.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Hao, Qi
    Shen, Weiming
    Function Block Based Integration of Process Planning, Scheduling and Execution for RMS2003In: Proceedings of CIRP 2nd International Conference on Reconfigurable Manufacturing, 2003Conference paper (Refereed)
  • 311.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Holm, M.
    Adamson, G.
    Embedding a Process Plan in Function Blocks for Adaptive Machining2010In: CIRP Annals – Manufacturing Technology, ISSN 0007-8506, Vol. 59, no 1, p. 433-436Article in journal (Refereed)
    Abstract [en]

    This paper presents a function block enabled approach towards adaptive process planning and machining. A two-layer structure of supervisory planning and operation planning is proposed to separate generic data from machine-specific ones. The supervisory planning is only performed once, in advance, at the shop level to generate machine-neutral process plans, whereas the operation planning is carried out at runtime at the machine level to determine machine-specific operations. Such adaptive decision making is facilitated by event-driven algorithms embedded in the function blocks. It is expected that the new approach can greatly enhance the dynamism of fluctuating job-shop machining operations.

  • 312.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Cloud enabled CPS and big data in manufacturing2018In: Proceedings of 3rd International Conference on the Industry 4.0 Model for Advanced Manufacturing, Pleiades Publishing , 2018, no 9783319895628, p. 265-292Chapter in book (Refereed)
    Abstract [en]

    This paper presents a cloud enhanced cyber-physical system (cloud CPS) in manufacturing by combining CPS and cloud technologies. The cloud CPS is enhanced by using the combined strength of holons, agents and function blocks (FBs). Here, a holarchy of multiple holons is a sub-CPS within cloud CPS, and a logical part and a physical part are involved in each holon, and they mimic the cyber and physical entities of the CPS. They are able to be realised by agents and FBs for the manufacturing processes. In addition, to address the weakness in operation level, big data analytics (BDA) is applied to optimise machining jobs and to predict faults in scheduling. Within the processes, machining relevant factors, including workpiece, machining requirement, machine tools, cutting tool, cutting conditions, machining process and machining results, are represented by data, which is able to solve the many operational issues in cloud CPS.

  • 313. Wang, Lihui
    et al.
    Jin, W
    Feng, HY
    Embedding machining features in function blocks for distributed process planning2006In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 19, no 5, p. 443-452Article in journal (Refereed)
  • 314.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Jin, Wei
    Feng, Hsi-Yung
    Design and Event-Driven Control of Function Blocks for Adaptive Process Plan Execution2005In: Transactions of the North American Manufacturing Research Institution of SME 2005, Vol 33, 2005, Society of Manufacturing Engineers, North American Manufacturing Research Institution, 2005, Vol. 33, p. 343-350Conference paper (Refereed)
    Abstract [en]

    In addition to complex job shop operations, shop floor uncertainty is another issue regularly challenging manufacturing engineers, including job delay, urgent job insertion, fixture shortage, missing tool, and even machine break-down. Targeting the fluctuation, this research proposes a DPP (distributed process planning) approach to generating adaptive process plans. Enabled by function blocks, a so-generated process plan is responsive and tolerant to an unpredictable change. This paper introduces in detail how a function block is designed and what it can do during process plan execution. It is expected that the new approach can largely enhance the dynamism of fluctuating job shop operations.

  • 315.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Jin, Wei
    Feng, Hsi-Yung
    Function Block Design and Development in Distributed Process Planning2004In: Proceedings of the 14th International Conference on Flexible Automation and Intelligent Manufacturing, 2004, Vol. 2, p. 783-791Conference paper (Refereed)
  • 316.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Keshavarzmanesh, Shadi
    Feng, Hsi-Yung
    A Function Block Based Approach for Increasing Adaptability of Assembly Planning and Control2011In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 49, no 16, p. 4903-4924Article in journal (Refereed)
    Abstract [en]

    Today's market turbulences cause frequent changes in manufacturing environments. Products diversity, small batch sizes and short life cycles have increased production uncertainties and created a highly dynamic shop floor environment. One essential requirement of such an environment is an adaptive planning and control system that is sufficiently agile to respond to the variety of production requirements and enable easy system reconfiguration at run-time. When developing a product, assembly is a key area that impacts the manufacturing system's responsiveness to the changes. In this research, a framework and a new methodology are introduced to increase the adaptability and autonomy of job-shop assembly process planning and control using function blocks (FBs). A function block is a reusable functional module with an explicit event-driven model, and provides for data flow and finite state automata based control. Event-driven and FB-enabled decision-making is unique in adaptive assembly planning and control. It is explained through an example of a two-robot assembly work cell, where the result of the adaptive planning is wrapped in FBs for execution. The proposed approach has been implemented and simulated using Matlab Simulink in the case study. The simulation demonstrates how this approach would increase the adaptability and responsiveness to changes that may occur regularly in dynamic job-shop assembly operations.

  • 317.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Keshavarzmanesh, Shadi
    Feng, Hsi-Yung
    A Hybrid Approach for Dynamic Assembly Shop Floor Layout2010In: Automation Science and Engineering (CASE), 2010 IEEE Conference on, IEEE conference proceedings, 2010, p. 604-609Conference paper (Refereed)
    Abstract [en]

    Highly turbulent environment of dynamic job-shop operations affects the shop floor layout problem as well as other areas. Due to frequently altering needs of layout, essential requirements such as adaptability and proactive responsiveness to the dynamic changes need to be considered in addition to the materials handling and machine relocation costs when a shop floor is reconfigured from one layout to the next. Targeting the autonomy and adaptability of dynamic and distributed job-shop assembly operations, this paper proposes to incorporate function block methodology to deal with the layout issues of the frequently changing environment. This is an extension to the authors' previous work.

  • 318.
    Wang, Lihui
    et al.
    University of Skövde.
    Keshavarzmanesh, Shadi
    Feng, Hsi-Yung
    Reconfigurable Facility Layout Design for Job-shop Assembly Operations2011In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing, Springer London, 2011, p. 365-384Chapter in book (Refereed)
    Abstract [en]

    Highly turbulent environment of dynamic job-shop operations affects shop-floor layout as well as manufacturing operations. Due to the dynamic nature of layout changes, essential requirements such as adaptability and responsiveness to the changes need to be considered in addition to the cost issues of material handling and machine relocation when reconfiguring a shop floor’s layout. Here, based on the source of uncertainty, the shop-floor layout problem is split into two sub-problems and dealt with by two modules: re-layout and find-route. Genetic algorithm is used where changes cause the entire shop re-layout, while function blocks are utilised to find the best sequence of robots for the new conditions within the existing layout. This chapter reports the latest development to the authors’ previous work.

  • 319. Wang, Lihui
    et al.
    Keshavarzmanesh, Shadi
    Feng, Hsi-Yung
    Buchal, Ralph O.
    Assembly process planning and its future in collaborative manufacturing: a review2009In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 41, no 1-2, p. 132-144Article in journal (Refereed)
  • 320.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Keshavarzmanesh, Shadi
    Feng, Hsi-Yung
    Buchal, R.O.
    Literature Review of Assembly Process Planning and Future Trends to Collaborative Manufacturing2007In: Proceedings of the 17th International Conference on Flexible Automation and Intelligent Manufacturing, 2007, Vol. 2, p. 773-780Conference paper (Refereed)
  • 321. Wang, Lihui
    et al.
    Keshavarzmanesha, Shadi
    Feng, Hsi-Yung
    Design of Adaptive Function Blocks for Dynamic Assembly Planning and Control2008In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 27, no 1, p. 45-51Article in journal (Refereed)
    Abstract [en]

    In today's competitive market, the life cycle of products is shrinking while product variety is growing. The product mix in small batches contributes to manufacturing uncertainty. Meanwhile, ever-growing business globalization and outsourcing also influence manufacturing. In such a dynamic environment, adaptability is of great importance. It is essential to develop a system that enables not only adaptive decision making, but also effective decision execution. Targeting manufacturing uncertainty, this paper reports a new framework and methodology for adaptive assembly planning using function blocks, which can be used directly for assembly control.

  • 322.
    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)
  • 323.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Koh, S.C.L.
    Preface2010In: Enterprise Networks and Logistics for Agile Manufacturing , Springer London, 2010, p. v-viiChapter in book (Refereed)
  • 324.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Koh, S.C.L.
    Web-based Robot Control for e-Operations2007In: Proceedings of the 5th International Conference on Supply Chain Management and Information Systems, 2007Conference paper (Refereed)
  • 325.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Liu, X.Y.
    Proceedings of the Fifth International Workshop on Advanced Manufacturing Technologies: 16 - 18 May 2005, London, Canada2005Book (Refereed)
  • 326.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Liu, Zhenkai
    Shen, Weiming
    Lang, Sherman
    Function-Block Enabled Job Shop Planning and Control with Uncertainty2004Conference paper (Refereed)
    Abstract [en]

    The objective of this research is to develop a methodology of distributed process planning and its execution control for job shop operations. The manufacturing processes of job shop operations are rather complex, especially at shop floors where highly mixed products in small batch sizes are handled simultaneously. In addition to the fluctuating job shop operations, unpredictable events like job delay, urgent job insertion, fixture shortage, missing tool, and even machine break-down, are regularly challenging the job shop operations. Targeting the fluctuations, this research proposes a DPP (distributed process planning) approach to generate process plans that are responsive and adaptive to the changes. In this paper, a function block enabled approach is introduced. It is expected that the new approach can largely enhance the dynamism of fluctuating job shop operations.

  • 327.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Ma, Ji
    Feng, Hsi-Yung
    An Adaptive and Optimal Setup Planning System2008In: Proceedings of the 4th IEEE Conference on Automation Science and Engineering, Institute of Electrical and Electronics Engineers (IEEE), 2008, p. 67-72, article id 4626414Conference paper (Refereed)
    Abstract [en]

    This paper presents an adaptive setup planning system that considers both the availability and capability of machines on a shop floor. It integrates scheduling functions at setup planning stage, and utilises a two-step decision-making strategy for generating machine-neutral and machine-specific optimal setup plans. The objective is to enable adaptive setup planning for dynamic job shop operations. Particularly, this paper documents basic algorithms and architecture of the setup planning system for dynamically assigned machines. It is then validated through a case study.

  • 328.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Ma, Ji
    Feng, Hsi-Yung
    Web-DPP: A Distributed Process Planning System for Adaptive Machining Operations2009In: Proceedings of the 19th International Conference on Flexible Automation and Intelligent Manufacturing, 2009, p. 186-193Conference paper (Refereed)
    Abstract [en]

    Outsourcing, joint ventures, and cross-border collaborations have led to work environments geographically distributed across organizational and national boundaries. Targeting the distributed environment, the Web has been widely used for development of collaborative applications supporting dispersed working groups and organizations, because of its platform, network and operating system transparency, and its easy-to-use browser interface. The objective of this research is to develop an innovative Web-based distributed process planning system (Web-DPP) for machining operations. Our approach tries to engage a dispersed working group in a collaborative environment, allowing the team members to share real-time information through the Web-DPP. This paper presents both the system design specification and the latest development of this system.

  • 329.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. University of Skövde.
    Ma, Ji
    Feng, Hsi-Yung
    Web-DPP: Towards Job-Shop Machining Process Planning and Monitoring2011In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 6, no 4, p. 337-353Article in journal (Other academic)
    Abstract [en]

    Outsourcing, joint ventures and cross-border collaborations have led to job environments geographically distributed. Targeting the distributed environment, the web has been widely used for developing collaborative applications due to its platform, network and operating system transparency and easy-to-use interface. Utilising the existing infrastructure, the objective of this research is to develop an integrated Web-based Distributed Process Planning (Web-DPP) system for job-shop machining operations and execution monitoring. Our approach engages a dispersed working group in a collaborative environment, allowing team members to share real-time information through the Web-DPP. This paper presents both the system design specification and the latest development.

  • 330.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Harbin Univ Sci & Technol, Sch Mech & Power Engn, Harbin 150080, Heilongjiang, Peoples R China.
    Meng, Yue
    Ji, Wei
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Harbin Univ Sci & Technol, Sch Mech & Power Engn, Harbin 150080, Heilongjiang, Peoples R China.
    Cutting energy consumption modelling for prismatic machining features2019In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 103, no 5-8, p. 1657-1667Article in journal (Refereed)
    Abstract [en]

    Targeting energy-efficient machining process planning, this paper presents a follow-up research on cutting energy consumption modelling for prismatic machining features (PMFs). Based on the investigation of plastic deformation-based energy consumption, its energy consumption model is extended to PMFs by refining machining time and feed at corners. Material removal volume associated with machining strategies for the PMF machining is considered as well. Moreover, cutting energy consumption models are established for the selected PMFs, i.e. face, step, slot and pocket. Finally, energy consumptions in machining of a designed test part, involving the established models of cutting energy consumption for the selected PMFs, are measured and compared with estimated energy consumptions to validate the developed models.

  • 331.
    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)
  • 332.
    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.

  • 333.
    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.

  • 334.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Mohammed, Abdullah
    Wang, Xi Vincent
    Schmidt, Bernard
    Recent Advancements of Smart Manufacturing: An Example of Energy-Efficient Robot2016In: Proceedings of the 26th International Conference on Flexible Automation and Intelligent Manufacturing, 2016, p. 884-892Conference paper (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 trajectory and based on the inverse kinematics and dynamics of a 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 trajectory. 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.

  • 335.
    Wang, Lihui
    et al.
    Integrated Manufacturing Technologies Institute, National Research Council Canada.
    Moriwaki, T.
    A Novel Meshing Algorithm for Dynamic Finite Element Analysis2003In: Precision engineering, ISSN 0141-6359, E-ISSN 1873-2372, Vol. 27, no 3, p. 245-257Article in journal (Refereed)
    Abstract [en]

    This paper describes a new algorithm to handle problems in dynamic finite element analysis and run-time simulation, where mesh re-generation or dynamic adjustment is required. Based on a concept called coded box cell (CBC) substitution, this algorithm can be applied to both initial mesh generation and dynamic mesh adjustment along the border zones of multiple primitives that form an entire model. During the initial mesh generation, appropriate labels are assigned to the nodes and the faces of each finite element. These labels are used to facilitate decision-making in dynamic mesh adjustment. A mapping technique is adopted to transform curved surfaces to plain surfaces for the ease of automatic mesh adjustment while still using the same algorithm. The results of a case study show that a finite element mesh can be adjusted dynamically and locally around its border zone; and the algorithm can be utilized effectively to simulate the thermal behavior of a device under real operating conditions.

  • 336.
    Wang, Lihui
    et al.
    Toyohashi University Technology, Japan.
    Moriwaki, T.
    An Approach to Dynamic Mesh Adjustment for Finite Element Analysis of Machines1996In: Transactions of the North American Manufacturing Research Institution of SME, ISSN 1047-3025, Vol. 24, p. 163-168Article in journal (Refereed)
  • 337.
    Wang, Lihui
    et al.
    Kobe University and Toyohashi University of Technology, Japan.
    Moriwaki, T.
    An Approach to Dynamic Thermal Analysis of Machine Tools1996Conference paper (Refereed)
  • 338.
    Wang, Lihui
    et al.
    Kobe University and Toyohashi University of Technology, Japan.
    Moriwaki, T.
    Modelling System for CAD/CAE of Machine Tools (5th Report, Application of CBC Substitution Approach to Curved Geometries)1996In: Proceedings of 1996 Spring Annual Meeting of Japan Society for Precision Engineering, 1996, p. 435-436Conference paper (Refereed)
  • 339.
    Wang, Lihui
    et al.
    Kobe University and Toyohashi University of Technology, Japan.
    Moriwaki, T.
    Sugimura, N.
    Study on Solid Modelling for Basic Design of Machine Tools1991In: Proceedings of the 66th Annual Meeting of Japan Society of Mechanical Engineers, 1991, p. 263-265Conference paper (Refereed)
  • 340. 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)
  • 341. Wang, Lihui
    et al.
    Nace, Adam
    Web-based Collaborative Planning and Control in a Wise-ShopFloor Environment2006Conference paper (Refereed)
  • 342.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Nace, Adam
    Orban, Peter
    Remote Device Control via Data Streaming and 3D Models2005Conference paper (Refereed)
  • 343.
    Wang, Lihui
    et al.
    Integrated Manufacturing Technologies Institute, National Research Council of Canada.
    Nace, Adam
    Orban, Peter
    Web-based Rapid Machining in Distributed Manufacturing Environment2006In: 2006 IEEE International Conference on Mechatronics and Automation, ICMA 2006, Institute of Electrical and Electronics Engineers (IEEE), 2006, p. 441-446Conference paper (Refereed)
    Abstract [en]

    In the area of discrete part machining, companies in job shop operations are challenged frequently by the variety of products in small batch sizes. These challenges become even more critical with the manufacturing decentralization and outsourcing, where design offices and machining shop floors may not be co-located. To remain competitive in a global market, collaborative manufacturing is the norm for such companies. The objective of this research is to develop a framework named Wise-ShopFloor as well as the enabling technologies for collaborative manufacturing in a decentralized environment. Particularly, this paper presents our latest development on Web-based rapid machining. Once a product design is given, its process plan and NC codes are generated by using a distributed process planning (DPP) system. The NC codes are then used for remote machining through a standard Web browser and a Java GUI interface running inside of the browser. In this paper, the focus is given to the concept, architecture and prototype implementation of the enabling technology. A case study of a test part machining on a 5-axis milling machine is also completed for testing and validation. It is expected that the developed baseline technology can be applied to design verification through rapid machining and real part production in distributed manufacturing environment.

  • 344.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Nee, Andrew Y.C.
    Collaborative Design and Planning for Digital Manufacturing: 2009Collection (editor) (Refereed)
  • 345.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Nee, Andrew Y.C.
    Preface2009In: Collaborative Design and Planning for Digital Manufacturing, Springer London, 2009, p. v-viiChapter in book (Refereed)
  • 346. 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)
  • 347.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Ng, Amos H. C.Deb, Kalyanmoy
    Multi-objective Evolutionary Optimisation for Product Design and Manufacturing2011Collection (editor) (Refereed)
  • 348.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Ng, Amos H. C.
    Deb, Kalyanmoy
    Preface2011In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing, Springer London, 2011, p. v-viiiChapter in book (Other academic)
  • 349.
    Wang, Lihui
    et al.
    Kobe University and Toyohashi University of Technology, Japan.
    Norrie, D.H.
    Process Planning and Control in a Holonic Manufacturing Environment2001In: Journal of Applied Systems Studies, Vol. 2, no 1, p. 106-126Article in journal (Refereed)
  • 350.
    Wang, Lihui
    et al.
    National Research Council of Canada.
    Orban, Peter
    Cunningham, A.
    Lang, Sherman Y. T.
    An Enabling Technology for Remote Real-Time CNC Machining2003In: Proceedings of the 13th International Conference on Flexible Automation and Intelligent Manufacturing, 2003, Vol. 1, p. 182-194Conference paper (Refereed)
45678910 301 - 350 of 470
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