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  • 1. Adamson, G.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Holm, Magnus
    Moore, Philip
    Cloud Manufacturing – A Critical Review of Recent Development and Future Trends2017In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 4-5, p. 347-380Article in journal (Refereed)
    Abstract [en]

    There is an ongoing paradigm shift in manufacturing, in which the modern manufacturing industry is changing towards global manufacturing networks and supply chains. This will lead to the flexible usage of different globally distributed, scalable and sustainable, service-oriented manufacturing systems and resources. Combining recently emerged technologies, such as Internet of Things, Cloud Computing, Semantic Web, service-oriented technologies, virtualisation and advanced high-performance computing technologies, with advanced manufacturing models and information technologies, Cloud Manufacturing is a new manufacturing paradigm built on resource sharing, supporting and driving this change. It is envisioned that companies in all sectors of manufacturing will be able to package their resources and know-hows in the Cloud, making them conveniently available for others through pay-as-you-go, which is also timely and economically attractive. Resources, e.g. manufacturing software tools, applications, knowledge and fabrication capabilities and equipment, will then be made accessible to presumptive consumers on a worldwide basis. Cloud Manufacturing has been in focus for a great deal of research interest and suggested applications during recent years, by both industrial and academic communities. After surveying a vast array of available publications, this paper presents an up-to-date literature review together with identified outstanding research issues, and future trends and directions within Cloud Manufacturing.

  • 2.
    Dudas, Catarina
    et al.
    Högskolan i Skövde, Forskningscentrum för Virtuella system.
    Ng, Amos H.C.
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    Pehrsson, Leif
    Högskolan i Skövde, Institutionen för ingenjörsvetenskap.
    Boström, Henrik
    Department of Computer and Systems Sciences, Stockholm University, Stockholm, Sweden.
    Integration of data mining and multi-objective optimisation for decision support in production system development2014In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 27, no 9, p. 824-839Article in journal (Refereed)
    Abstract [en]

    Multi-objective optimisation (MOO) is a powerful approach for generating a set of optimal trade-off (Pareto) design alternatives that the decision-maker can evaluate and then choose the most-suitable configuration, based on some high-level strategic information. Nevertheless, in practice, choosing among a large number of solutions on the Pareto front is often a daunting task, if proper analysis and visualisation techniques are not applied. Recent research advancements have shown the advantages of using data mining techniques to automate the post-optimality analysis of Pareto-optimal solutions for engineering design problems. Nonetheless, it is argued that the existing approaches are inadequate for generating high-quality results, when the set of the Pareto solutions is relatively small and the solutions close to the Pareto front have almost the same attributes as the Pareto-optimal solutions, of which both are commonly found in many real-world system problems. The aim of this paper is therefore to propose a distance-based data mining approach for the solution sets generated from simulation-based optimisation, in order to address these issues. Such an integrated data mining and MOO procedure is illustrated with the results of an industrial cost optimisation case study. Particular emphasis is paid to showing how the proposed procedure can be used to assist decision-makers in analysing and visualising the attributes of the design alternatives in different regions of the objective space, so that informed decisions can be made in production systems development.

  • 3.
    Ji, Wei
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Harbin University of Science and Technology, China.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Haghighi, Azadeh
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Illinois at Chicago, United States.
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Liu, Xianli
    An enriched machining feature based approach to cutting tool selection2018In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 31, no 1, p. 1-10Article in journal (Refereed)
    Abstract [en]

    Cutting tools, considered as a basic prerequisite machining resource, are generally selected according to the selected machining methods, which cannot fit in the current manufacturing environment where small- and medium-sized enterprises (SMEs) are the major manufacturers. For the survival of SMEs, it is critical to develop methods for selecting proper cutting tools and reducing machining cost according to product data. Therefore, this study proposes an enriched machining feature (MF)-based approach towards adaptive cutting tool and machining method selection, in which both machinability and machining cost of MF are considered. It includes a two-step workflow: filtering and optimisation. In the filtering process, cutting tools are filtered according to workpiece materials, geometries of MFs and cutting tool inventory, respectively. Here, MF geometries depend on Machining Limit Value decided by sizes and interference relationships of MFs. Also, the client is suggested to choose proper new cutting tools. In the optimisation process, the filtered cutting tools are considered for all the MFs, and machining costs are calculated for each option, in order to select the cheapest one. In particular, if similar cutting tools are required for different MFs, the cutting tool selection for these MFs should be performed altogether.

  • 4.
    Li, Yujiang
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Computer Systems for Design and Manufacturing.
    Hedlind, Mikael
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Computer Systems for Design and Manufacturing.
    Kjellberg, Torsten
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Computer Systems for Design and Manufacturing.
    Sivard, Gunilla
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    System integration for kinematic data exchange2014In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052Article in journal (Refereed)
    Abstract [en]

    Industry needs a system neutral solution for exchange of kinematic models. In this article, the first known valid implementation of kinematic mechanisms based on ISO 10303 Standard for the Exchange of Product (STEP) is presented. The result includes an implementation framework and two developed prototypes. Two major challenges of standard-based development are identified and generalised: data integration and system integration, which are solved by the framework. The two prototypes are implemented to establish kinematic data exchange between Siemens NX® and STEP-NC MachineTM via STEP AP214 files. Experiences of design and development of the applications are presented, and a validated case study of data exchange using the developed applications is shown. There are other attempts of using STEP as basis for modelling, but as the first valid STEP implementation on kinematics, this approach demonstrates the feasibility of pure STEP-based data exchange for kinematic mechanisms. The prototypes also show potential of utilising the framework for general standard implementations. The research is expected to motivate deeper understanding and extensive applications of the STEP standard in industry and academia.

  • 5.
    Liu, Yongkui
    et al.
    Xidian Univ, Ctr Smart Mfg Syst, Sch Mechano Elect Engn, Xian, Shaanxi, Peoples R China..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Xi Vincent
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Xu, Xun
    Univ Auckland, Dept Mech Engn, Auckland, New Zealand..
    Jiang, Pingyu
    Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian, Shaanxi, Peoples R China..
    Cloud manufacturing: key issues and future perspectives2019In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052Article in journal (Refereed)
    Abstract [en]

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

  • 6.
    Mohammed, Abdullah
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Schmidt, Bernard
    University of Skövde.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Active collision avoidance for human–robot collaboration driven by vision sensors2016In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, p. 1-11Article in journal (Refereed)
    Abstract [en]

    Establishing safe human–robot collaboration is an essential factor for improving efficiency and flexibility in today’s manufacturing environment. Targeting safety in human–robot collaboration, this paper reports a novel approach for effective online collision avoidance in an augmented environment, where virtual three-dimensional (3D) models of robots and real images of human operators from depth cameras are used for monitoring and collision detection. A prototype system is developed and linked to industrial robot controllers for adaptive robot control, without the need of programming by the operators. The result of collision detection reveals four safety strategies: the system can alert an operator, stop a robot, move away the robot, or modify the robot’s trajectory away from an approaching operator. These strategies can be activated based on the operator’s existence and location with respect to the robot. The case study of the research further discusses the possibility of implementing the developed method in realistic applications, for example, collaboration between robots and humans in an assembly line.

  • 7.
    Onori, Mauro
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Semere, Daniel
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Lindberg, Bengt
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Evolvable systems: an approach to self-X production2011In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 24, no 5, p. 506-516Article in journal (Refereed)
    Abstract [en]

    Current major road mapping efforts, such as ManuFuture, FutMan and EUPASS, have all clearly underlined that true industrial sustainability will require far higher levels of systems' autonomy and adaptability. In accordance with these recommendations, the Evolvable Production Systems (EPS) has aimed at developing such technological solutions and support mechanisms. Since its inception in 2002 (Onori, M., 2002. In: ISR2002 - 33rd International Symposium on Robotics, Stockholm, 617-621) as a next generation of production systems, the concept is being further developed and tested to emerge as a production system paradigm. The essence of evolvability resides not only in the ability of system components to adapt to the changing conditions of operation but also to assist in the evolution of these components in time such that processes may become self-X, X standing for one or more desirable properties of a system subjected to a variable operation condition such as self-evolvable, self-reconfigurable, self-tuning, self-diagnosing, and so on. Characteristically, evolvable systems have distributed control and are composed of integrated intelligent modules. To assist the development and life cycle issues, comprehensive methodological framework is being developed. A concerted effort is being exerted through European research projects in collaboration with European manufacturers, technology/equipment suppliers and universities. After briefly stating the fundamental concepts of EPS, this article presents current developments and applications.

  • 8. Prasoon, R.
    et al.
    Das, D.
    Tiwari, M.K.
    Wang, Lihui
    University of Skovde.
    An Algorithm Portfolio Approach to Reconfigurable Setup Planning2011In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 24, no 8, p. 756-768Article in journal (Refereed)
    Abstract [en]

    This article discusses an algorithm portfolio approach to find optimal set-up plans in a dynamic shop floor environment where flexibility and promptness of the decision process is critical along with best possible utilisation of the available resources. An evolutionary algorithm based reconfigurable set-up planning approach is presented where the final set-up plan is determined in two steps: primitive set-up planning through feature grouping and reconfigurable set-up merging based on real time information from the scheduling system. The tendency of single algorithm approach to converge to sub-optimal solutions was countered by using portfolios of genetic algorithm and its three variants: Genetic Algorithm with Chromosome Differentiation, Sexual Genetic Algorithm and a modified version of Age Genetic Algorithm. Best performing portfolios selected after exhaustive experimentation showed dramatic computational improvements in achieving the optimal solution validating the appropriateness and effectiveness of algorithm portfolio approach.

  • 9. Putnik, G.D.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Ubiquitous and Cloud Enterprise for Manufacturing2017In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 4-5, p. 344-346Article in journal (Refereed)
  • 10. Ren, Lei
    et al.
    Zhang, Lin
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Tao, Fei
    Chai, Xudong
    Cloud manufacturing: key characteristics and applications2017In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 30, no 6, p. 501-515Article in journal (Refereed)
    Abstract [en]

    Cloud manufacturing is emerging as a new manufacturing paradigm as well as an integrated technology, which is promising in transforming today's manufacturing industry towards service-oriented, highly collaborative and innovative manufacturing in the future. In order to better understand cloud manufacturing, this paper provides a critical review of relevant concepts and ideas in cloud computing as well as advanced manufacturing technologies that contribute to the evolution of cloud manufacturing. The key characteristics of cloud manufacturing are also presented in order to clarify the cloud manufacturing concept. Furthermore, a four-process structure is proposed to describe the typical scenario in cloud manufacturing, hoping to provide a theoretical reference for practical applications. Finally, an application case of a private cloud manufacturing system for a conglomerate is presented.

  • 11.
    Rogstrand, Victoria
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Computer Systems for Design and Manufacturing.
    Kjellberg, Torsten
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Computer Systems for Design and Manufacturing.
    The representation of manufacturing requirements in model-driven parts manufacturing2009In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 22, no 11, p. 1065-1072Article in journal (Refereed)
    Abstract [en]

    Today there is a need to make process and production planning more cost-effective while not compromising the quality of the product. Manufacturing requirements are used to ensure producibility in early development phases and also as a source for continuous improvement of the manufacturing system. To make this possible it is essential to have correct, updated information available and to be able to trace the relations between requirements and their origin and subjects. To trace requirements' origin in resources or processes is today very difficult owing to system integration problems. This article discusses the relations that need to be represented and proposes the use of model-based methods to enable traceability of requirements. Because requirements are a collaborative effort a standard for information exchange is needed. The ISO10303 STEP application protocol AP233 System Engineering is proposed for this purpose.

  • 12.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Planning towards Enhanced Adaptability in Digital Manufacturing2011In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 24, no 5, p. 378-390Article in journal (Refereed)
    Abstract [en]

    This paper presents an integrated approach for developing a web-based system with enhanced adaptability, including distributed process planning, real-time monitoring and remote machining. The objective is to develop a new methodology and relevant processing algorithms for enhancing adaptability in digital manufacturing. This approach is enabled by a Wise-ShopFloor (Web-based integrated sensor-driven e-ShopFloor) framework targeting distributed yet collaborative manufacturing environments. Utilising the latest Java technologies (Java 3D and Java Servlet) for system implementation, it allows end-users to plan and control distant manufacturing operations based on runtime information from shop floors. Details on the principle of the Wise-ShopFloor framework, system architecture, and a prototype system are reported in this paper. An example of distributed process planning for remote machining is chosen as a case study to demonstrate the effectiveness of this approach toward web-based digital manufacturing.

  • 13.
    Wang, Lihui
    National Research Council of Canada.
    Web-based Decision Making for Collaborative Manufacturing2009In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 22, no 4, p. 334-344Article in journal (Refereed)
    Abstract [en]

    This paper presents methodologies of web-based decision making for collaborative manufacturing, including web-based knowledge sharing, distributed process planning, dynamic scheduling, real-time monitoring and remote control, targeting distributed yet collaborative manufacturing environments. The web-based decision making is enabled by a framework that allows users to plan and control manufacturing operations based on information either gathered via the Web or collected from manufacturing devices. The objective of this research is to develop an integrated system for web-based collaborative planning and control, supported by real-time monitoring for dynamic scheduling. Details on the principle of the framework, system architecture, and a proof-of-concept prototype are reported in this paper. An example of remote machining is chosen as a case study to demonstrate the effectiveness of this framework toward web-based collaborative manufacturing.

  • 14.
    Wang, Lihui
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Cai, Ningxu
    Feng, Hsi-Yung
    Function Blocks Enabled Dynamic Setup Dispatching and Execution Monitoring2009In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 22, no 1, p. 3-12Article in journal (Refereed)
  • 15. 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)
  • 16.
    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.

  • 17. 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)
  • 18. 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)
  • 19.
    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.

  • 20. Xu, Xun
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde.
    Newman, Stephen T.
    Computer-Aided Process Planning − A Critical Review of Recent Developments and Future Trends2011In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 24, no 1, p. 1-31Article in journal (Refereed)
    Abstract [en]

    For the past three decades, computer-aided process planning (CAPP) has attracted a large amount of research interest. A huge volume of literature has been published on this subject. Today, CAPP research faces new challenges owing to the dynamic markets and business globalisation. Thus, there is an urgent need to ascertain the current status and identify future trends of CAPP. Covering articles published on the subjects of CAPP in the past 10 years or so, this article aims to provide an up-to-date review of the CAPP research works, a critical analysis of journals that publish CAPP research works, and an understanding of the future direction in the field. First, general information is provided on CAPP. The past reviews are summarised. Discussions about the recent CAPP research are presented in a number of categories, i.e. feature-based technologies, knowledge-based systems, artificial neural networks, genetic algorithms, fuzzy set theory and fuzzy logic, Petri nets, agent-based technology, Internet-based technology, STEP-compliant CAPP and other emerging technologies. Research on some specific aspects of CAPP is also provided. Discussions and analysis of the methods are then presented based on the data gathered from the Elsevier's Scopus abstract and citation database. The concepts of ‘Subject Strength’ of a journal and ‘technology impact factor’ are introduced and used for discussions based on the publication data. The former is used to gauge the level of focus of a journal on a particular research subject/domain, whereas the latter is used to assess the level of impact of a particular technology, in terms of citation counts. Finally, a discussion on the future development is presented.

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