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  • 1. Buckholtz, Ben
    et al.
    Ragai, Ihab
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Cloud Manufacturing: Current Trends and Future Implementations2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 4, article id 040902Article in journal (Refereed)
    Abstract [en]

    Manufacturing technology changes with the needs of consumers. The globalization of the world economy has helped to create the concept of cloud manufacturing (CM). The purpose of this paper is to provide both an overview and an update on the status of CM and define the key technologies that are being developed to make CM a dependable configuration in today's manufacturing industry. Topics covered include: cloud computing (CC), the role of small and medium enterprises (SMEs), pay-as-you-go, resource virtualization, interoperability, security, equipment control, and the future outlook of the development of CM.

  • 2.
    Ji, Wei
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Harbin University of Science and Technology, China.
    Shi, J.
    Liu, X.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Liang, S. Y.
    A Novel Approach of Tool Wear Evaluation2017In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 139, no 9, article id 091015Article in journal (Refereed)
    Abstract [en]

    The high-efficiency utilization of cutting tool resource is closely related to the flexible decision of tool life criterion, which plays a key role in manufacturing systems. Targeting a flexible method to evaluate tool life, this paper presents a data-driven approach considering all the machining quality requirements, e.g., surface integrity, machining accuracy, machining stability, chip control, and machining efficiency. Within the context, to connect tool life with machining requirements, all patterns of tool wear including flank face wear and rake face wear are fully concerned. In this approach, tool life is evaluated systematically and comprehensively. There is no generalized system architecture currently, and a four-level architecture is therefore proposed. Workpiece, cutting condition, cutting parameter, and cutting tool are the input parameters, which constrain parts of the independent variables of the evaluation objective including first-level and second-level indexes. As a result, tool wears are the remaining independent variables, and they are calculated consequently. Finally, the performed processes of the method are experimentally validated by a case study of turning superalloys with a polycrystalline cubic boron nitride (PCBN) cutting tool.

  • 3. Liu, X.
    et al.
    Li, Y.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A Cloud Manufacturing Architecture for Complex Parts Machining2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 6, article id 061009Article in journal (Refereed)
    Abstract [en]

    Service provider (SP) know-hows are essential in machining service (MS) encapsulation in the cloud. However, since the acquisition of the know-hows for complex parts machining requires investing considerable manpower and resources in R&D, this kind of machining know-hows is usually considered as one of the core competences of the SP who makes them unshareable. Targeting the problem, this paper presents a new cloud manufacturing (CM) architecture in which MSs are encapsulated within each SP with standardized machining task description strategies (SMTDS). Only the capability information about what the SP can do is provided to the cloud. During service matching, SMTDS is also applied for user request formulation to improve the matching efficiency and quality. For complex parts in large size, high machining requirements, high value, short delivery cycle, and complex structures, e.g., aircraft structural parts, unacceptable machining quality or delivery delay may cause a much greater loss not only in economy. In the proposed CM architecture, to guarantee the feasibility of the MSs for complex structural parts, machining operations for the user preferred services could be generated by mapping the corresponding typical machining plans (TMP) to the part based on the dynamic feature concept to support accurate evaluations of the MSs. The machining of an aircraft structural part is then applied as a test user request to demonstrate how the proposed method works for finding MS for complex parts.

  • 4.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, B.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Energy-Efficient Robot Configuration for Assembly2017In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 139, no 5, article id 051007Article in journal (Refereed)
    Abstract [en]

    Optimizing the energy consumption of robot movements has been one of the main focuses for most of today's robotic simulation software. This optimization is based on minimizing a robot's joint movements. In many cases, it does not take into consideration the dynamic features. Therefore, reducing energy consumption is still a challenging task and it involves studying the robot's kinematic and dynamic models together with application requirements. This research aims to minimize the robot energy consumption during assembly. Given a trajectory and based on the inverse kinematics and dynamics of a robot, a set of attainable configurations for the robot can be determined, perused by calculating the suitable forces and torques on the joints and links of the robot. The energy consumption is then calculated for each configuration and based on the assigned trajectory. The ones with the lowest energy consumption are selected. Given that the energyefficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be embedded in energy-efficient robotic assembly.

  • 5. Tao, Fei
    et al.
    Zhang, Lin
    Liu, Yongkui
    Cheng, Ying
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, Xun
    Manufacturing Service Management in Cloud Manufacturing: Overview and Future Research Directions2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 4, article id 040912Article in journal (Refereed)
    Abstract [en]

    As a new service-oriented manufacturing paradigm, cloud manufacturing (CMfg) has experienced rapid development in the past five years. The research on its theories, key technologies, developments, and applications still keeps attracting attentions from more and more researchers. One of the most important issues to its improvements and quality of service (QoS) is the manufacturing service management (MSM). CMfg aims to realize the full-scale sharing, free circulation and transaction, and on-demand use of various manufacturing resource and capabilities in the form of manufacturing service. Without the effective operation and technical support of MSM, the implementation of CMfg and its aim cannot be achieved. It is therefore necessary to summarize the existing works and technologies on MSM in CMfg. This paper first provides a brief overview of CMfg and then focuses on the problem of MSM in CMfg from the service lifecycle perspective. The advances on MSM technology from eleven aspects are investigated and summarized. Finally, future research directions are identified and discussed. It is evident that the future MSM in CMfg is closely related to Internet of things (IoT), big data, and cloud computing.

  • 6.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Xu, Xun
    Advances and Challenges in Cloud Manufacturing2015In: Journal of manufacturing science and engineering, ISSN 1087-1357, E-ISSN 1528-8935, Vol. 137, no 4, p. 040301-040301-2Article in journal (Refereed)
  • 7.
    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)
  • 8.
    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.

  • 9. 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.

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