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  • 1. Adamson, G.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Holm, M.
    The state of the art of cloud manufacturing and future trends2013In: ASME 2013 International Manufacturing Science and Engineering Conference Collocated with the 41st North American Manufacturing Research Conference, MSEC 2013, 2013Conference paper (Refereed)
    Abstract [en]

    Cloud manufacturing has emerged as a new manufacturing paradigm, which combines technologies (such as Internet of Things, Cloud computing, semantic Web, virtualisation and service-oriented technologies) with advanced manufacturing models, information and communication technologies. It aims to be networked, intelligent, service-oriented, knowledge-based and energy efficient, and promises a variety of benefits and advantages by providing fast, reliable and secure on-demand services for users. 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, will then be made accessible to presumptive consumers on a worldwide basis. After surveying a vast array of available publications, this paper presents an up-to-date literature review together with future trends and research directions in Cloud manufacturing.

  • 2. Adamson, G.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Holm, M.
    Moore, P.
    Adaptive robotic control in cloud environments2014In: FAIM 2014 - Proceedings of the 24th International Conference on Flexible Automation and Intelligent Manufacturing: Capturing Competitive Advantage via Advanced Manufacturing and Enterprise Transformation, DEStech Publications Inc , 2014, p. 37-44Conference paper (Refereed)
    Abstract [en]

    The increasing globalization is a trend which forces manufacturing industry of today to focus on more cost-effective manufacturing systems and collaboration within global supply chains and manufacturing networks. Cloud Manufacturing (CM) is evolving as a new manufacturing paradigm to match this trend, enabling the mutually advantageous sharing of resources, knowledge and information between distributed companies and manufacturing units. Providing a framework for collaboration within complex and critical tasks, such as manufacturing and design, it increases the companies' ability to successfully compete on a global marketplace. One of the major, crucial objectives for CM is the coordinated planning, control and execution of discrete manufacturing operations in a collaborative and networked environment. This paper describes the overall concept of adaptive Function Block control of manufacturing equipment in Cloud environments, with the specific focus on robotic assembly operations, and presents Cloud Robotics as "Robot Control-as-a-Service" within CM. © Copyright 2014 by DEStech Publications, Inc. All rights reserved.

  • 3. 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.

  • 4. Adamson, Goran
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. University of Skövde, Sweden.
    Holm, Magnus
    Moore, Philip
    ADAPTIVE ROBOT CONTROL AS A SERVICE IN CLOUD MANUFACTURING2015In: PROCEEDINGS OF THE ASME 10TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2015, VOL 2, ASME Press, 2015, Vol. 2Conference paper (Refereed)
    Abstract [en]

    The interest for implementing the concept of Manufacturing-as-a-Service is increasing as concepts for letting the manufacturing shop-floor domain take advantage of the cloud appear. Combining technologies such as Internet of Things, Cloud Computing, Semantic Web, virtualisation and service-oriented technologies with advanced manufacturing models, information and communication technologies, Cloud Manufacturing is emerging as a new manufacturing paradigm. The ideas of on-demand, scalable and pay-for-usage resource-sharing in this concept will move manufacturing towards distributed and collaborative missions in volatile partnerships. This will require a control approach for distributed planning and execution of cooperating manufacturing activities. Without control based on both global and local environmental conditions, the advantages of Cloud Manufacturing will not be fulfilled. By utilising smart and distributable decision modules such as event-driven Function Blocks, run-time manufacturing operations in a. distributed environment may be adjusted to prevailing manufacturing conditions. Packaged in a cloud service for manufacturing equipment control, they will satisfy the control needs. By combining different resource types, such as hard, soft and capability resources, the cloud service Robot Control-as-a-Service can be realised. This paper describes the functional perspective and enabling technologies for a distributed control approach for robotic assembly tasks in Cloud Manufacturing.

  • 5. Adamson, Goran
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Holm, Magnus
    Moore, Philip
    FEATURE-BASED ADAPTIVE MANUFACTURING EQUIPMENT CONTROL FOR CLOUD ENVIRONMENTS2016In: PROCEEDINGS OF THE ASME 11TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2016, VOL 2, AMER SOC MECHANICAL ENGINEERS , 2016Conference paper (Refereed)
    Abstract [en]

    The ideas of on-demand, scalable and pay-for-usage resource-sharing in Cloud Manufacturing are steadily attracting more interest. For implementing the concept of Manufacturing as-a-Service in a cloud environment, description models and implementation language for resources and their capabilities are required. A standardized approach for systemived virtualization, servisilisation, retrieval, selection and composition into higher levels of functionality is necessary. For the collaborative sharing and use of networked manufacturing resources there is also a need for a control approach for distributed manufacturing equipment. In this paper, the technological perspective for an adaptive cloud service-based control approach is described, and a supporting information model for its implementation. The control is realized through the use of a network of intelligent and distributable Function Block decision modules, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the cloud service management functionality is described, as well as a feature-level capability model and the use of ontologies and the Semantic Web.

  • 6. Adamson, Göran
    et al.
    Holm, Magnus
    Moore, Philip
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Univ Skövde, Sweden.
    A cloud service control approach for distributed and adaptive equipment control in cloud environments2016In: RESEARCH AND INNOVATION IN MANUFACTURING: KEY ENABLING TECHNOLOGIES FOR THE FACTORIES OF THE FUTURE - PROCEEDINGS OF THE 48TH CIRP CONFERENCE ON MANUFACTURING SYSTEMS, 2016, p. 644-649Conference paper (Refereed)
    Abstract [en]

    A developing trend within the manufacturing shop-floor domain is the move of manufacturing activities into cloud environments, as scalable, on-demand and pay-per-usage cloud services. This will radically change traditional manufacturing, as borderless, distributed and collaborative manufacturing missions between volatile, best suited groups of partners will impose a multitude of advantages. The evolving Cloud Manufacturing (CM) paradigm will enable this new manufacturing concept, and on-going research has described many of its anticipated core virtues and enabling technologies. However, a major key enabling technology within CM which has not yet been fully addressed is the dynamic and distributed planning, control and execution of scattered and cooperating shop-floor equipment, completing joint manufacturing tasks. In this paper, the technological perspective for a cloud service-based control approach is described, and how it could be implemented. Existing manufacturing resources, such as soft, hard and capability resources, can be packaged as cloud services, and combined to create different levels of equipment or manufacturing control, ranging from low-level control of single machines or devices (e.g. Robot Control-as-a-Service), up to the execution of high level multi-process manufacturing tasks (e.g. Manufacturing-as-a-Service). A multi-layer control approach, featuring adaptive decision-making for both global and local environmental conditions, is proposed. This is realized through the use of a network of intelligent and distributable decision modules such as event-driven Function Blocks, enabling run-time manufacturing activities to be performed according to actual manufacturing conditions. The control system's integration to the CM cloud service management functionality is also described.

  • 7. Adamson, Göran
    et al.
    Holm, Magnus
    Wang, Lihui
    Moore, Philip
    Adaptive Assembly Feature Based Function Block Control of Robotic Assembly Operations2012Conference paper (Refereed)
    Abstract [en]

    Many manufacturing systems are exposed to a variety of unforeseen changes, negatively restricting their performances. External variations depending on market demand (e.g. changes in design, quantity and product mix) and internal variations in production capability and flexibility (e.g. equipment breakdowns, missing/worn/broken tools, delays and express orders) all contribute to an environment of uncertainty. In these dynamically changing environments, adaptability is a key feature for manufacturing systems to be able to perform at a maximum level, while keeping unscheduled downtime to a minimum. Targeting manufacturing equipment adaptability, this paper reports an assembly feature (AF) based approach for robotic assembly, using IEC 61499 compliant Function Blocks (FBs). Through the use of a network of event-driven FBs, an adaptive controller system for an industrial gantry robot’s assembly operations has been designed, implemented and tested. Basic assembly operations have been mapped as AFs into Assembly Feature Function Blocks (AF-FBs). Through their combination in FB networks, they can be aggregated to perform higher level assembly tasks. The AF-FBs dynamic execution and behavior can be adaptively controlled through embedded eventdriven algorithms, enabling the ability of adaptive decisions to handle unforeseen changes in the runtime environment.

  • 8. Aslam, Tehseen
    et al.
    Hedenstierna, Philip
    Ng, Amos H. C.
    Wang, Lihui
    Multi-objective Optimisation in Manufacturing Supply-chain Systems Design: A Comprehensive Survey and New Directions2011In: Multi-objective Evolutionary Optimisation for Product Design and Manufacturing, Springer London, 2011, p. 35-70Chapter in book (Refereed)
  • 9. Azeem, A.
    et al.
    Feng, Hsi-Yung
    Wang, Lihui
    A Simplified Approach for Determining Empirical Cutting Force Coefficients for Ball-End Milling2003In: Transactions of the North American Manufacturing Research Institution of SME, ISSN 1047-3025, Vol. 131, p. 121-128Article in journal (Refereed)
  • 10. Azeem, A.
    et al.
    Feng, Hsi-Yung
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council of Canada.
    Simplified and Efficient Calibration of a Mechanistic Cutting Force Model for Ball-End Milling2004In: International journal of machine tools & manufacture, ISSN 0890-6955, E-ISSN 1879-2170, Vol. 44, no 2-3, p. 291-298Article in journal (Refereed)
    Abstract [en]

    Accurate evaluation of the empirical coefficients of a mechanistic cutting force model is critical to the reliability of the predicted cutting forces. This paper presents a simplified and efficient method to determine the cutting force coefficients of a ball-end milling model. The unique feature of this new method is that only a single half-slot cut is to be performed to calibrate the empirical force coefficients that are valid over a wide range of cutting conditions. The instantaneous cutting forces are used with the established helical cutting edge profile on the ball-end mill. The half-slot calibration cut enables successive determination of the lumped discrete values of the varying cutting mechanics parameters along the cutter axis whereas the size effect parameters are determined from the known variation of undeformed chip thickness with cutter rotation. The effectiveness of the present method in determining the cutting force coefficients has been demonstrated experimentally with a series of verification test cuts.

  • 11. Bi, Z. M.
    et al.
    Lang, S. Y. T.
    Shen, W.
    Wang, Lihui
    Reconfigurable Manufacturing Systems: The State of the Art2008In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 46, no 4, p. 967-992Article in journal (Refereed)
    Abstract [en]

    In this paper, general requirements of next generation manufacturing systems are discussed, and the strategies to meet these requirements are considered. The production paradigms which apply these strategies are also classified. Particular emphasis is put on the paradigm of Reconfigurable Manufacturing System (RMS). Some key issues of the RMS design are discussed, and a critical review is presented concerning the developments of RMSs. Finally, suggestions of the RMS research are made and future research directions are identified.

  • 12. Bi, Z. M.
    et al.
    Lang, Sherman Y. T.
    Wang, Lihui
    Improved Control and Simulation Models of a Tricycle Collaborative Robot2008In: Journal of Intelligent Manufacturing, ISSN 0956-5515, E-ISSN 1572-8145, Vol. 19, no 6, p. 715-722Article in journal (Refereed)
    Abstract [en]

    The objective of collaborative manufacturing is to create the synergism from the collaboration of manufacturing resources. Most of the studied collaborations are made among intelligent machines; however, the collaboration can be realized even between machines and human being, and a collaborative robot (Cobot) belongs to the latter. A cobot is a robot designed to assist human beings as a guide or assistor in a constrained motion. Various prototypes have been developed and the potentials of these robots have been demonstrated. The research presented in this paper focuses on the control and simulation models of a tricycle cobot with three steered wheels, with the following two contributions: (i) A concise model for the closed-loop control is developed. Existing closed-loop control has been implemented in an intuitive way, and some control parameters have to be determined by a trial-and-error method. (ii) A simulation model is proposed to validate the control algorithms. No simulation model is available and the control models of other existing systems have to be validated experimentally. The developed control and simulation models have been implemented. Graphic simulation is also developed. Case studies are provided and the simulation results are analyzed.

  • 13. Bi, Z. M.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Manufacturing Paradigm Shift Towards Better Sustainability2013In: Cloud Manufacturing: Distributed Computing Technologies for Global and Sustainable Manufacturing / [ed] Weidong Li and Jörn Mehnen, London: Springer London, 2013, p. 99-119Chapter in book (Refereed)
    Abstract [en]

    A system paradigm is an abstract representation of the system; it is thesystem architecture that determines the types and numbers of the components andtheir relations in operation and interaction of the system. Its selection relies oncustomers’ requirements and manufacturing environment. Many system paradigmshave been proposed. However, most of them are based on an assumption that thelife-cycle and boundary of a system can be defined based on the customers’requirements. Since sustainability becomes essential to today’s manufacturingsystems, a new concern is how to evolve existing paradigms to meet new chal-lenges. The objectives of this chapter are, therefore, to examine the manufacturingrequirements in a wider scope, to revisit existing paradigms to clarify the limi-tations and bottlenecks, and eventually to identify future research directionstowards sustainable manufacturing. Within the context, this chapter focuses moreon Reconfigurable and Cloud manufacturing system paradigms, and highlights thefuture endeavors towards better sustainability.

  • 14.
    Bi, Z. M.
    et al.
    Indiana University-Purdue University Indianapolis.
    Wang, Lihui
    University of Skövde.
    Optimization of machining processes from the perspective of energy consumption: A case study2012In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 31, no 4, p. 420-428Article in journal (Refereed)
    Abstract [en]

    One of the primary objectives of sustainable manufacturing is to minimize energy consumption in its manufacturing processes. A strategy of energy saving is to adapt new materials or new processes; but its implementation requires radical changes of the manufacturing system and usually a heavy initial investment. The other strategy is to optimize existing manufacturing processes from the perspective of energy saving. However, an explicit relational model between machining parameters and energy cost is required: while most of the works in this field treat the manufacturing processes as black or gray boxes. In this paper, analytical energy modeling for the explicit relations of machining parameters and energy consumption is investigated, and the modeling method is based on the kinematic and dynamic behaviors of chosen machine tools. The developed model is applied to optimize the machine setup for energy saving. A new parallel kinematic machine Exechon is used to demonstrate the procedure of energy modeling. The simulation results indicate that the optimization can result in 67% energy saving for the specific drilling operation of the given machine tool. This approach can be extended and applied to other machines to establish their energy models for sustainable manufacturing

  • 15. Bi, Zhuming
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wu, Chong
    Yang, Guilin
    Zhang, Dan
    Multidisciplinary Design Optimization in Engineering2013In: Mathematical problems in engineering (Print), ISSN 1024-123X, E-ISSN 1563-5147, p. 351097-Article in journal (Other academic)
  • 16. Bi, Z.M.
    et al.
    Lang, Sherman Y. T.
    Wang, Lihui
    Design of Reconfigurable Manufacturing System with Strongly Coupled Nature2006Conference paper (Refereed)
  • 17. Bi, Z.M.
    et al.
    Lang, Sherman Y. T.
    Wang, Lihui
    Design of Reconfigurable Manufacturing Systems with Strongly Coupled Nature2007In: Chinese Journal of Mechanical Engineering, Vol. 20, no 1, p. 91-95Article in journal (Refereed)
    Abstract [en]

    Today's manufacturing environment forces manufacturing companies to make as many product variations as possible at affordable costs within a short time. Mass customisation is one of most important technologies for companies to achieve their objectives. Efforts to mass customisation should be made on two aspects: (1) To modularize products and make them as less differences as possible; (2) To design manufacturing resources and make them provide as many processes variations as possible. This paper reports our recent work on aspect (2), i.e. how to design a reconfigurable manufacturing system (RMS) so that it can be competent to accomplish various processes optimally; Reconfigurable robot system (RRS) is taken as an example. RMS design involves architecture design and configuration design, and configuration design is further divided in design analysis and design synthesis. Axiomatic design theory (ADT) is applied to architecture design, the features and issues of RRS configuration design are discussed, automatic modelling method is developed for design analysis, and concurrent design methodology is presented for design synthesis.

  • 18. Bi, Z.M.
    et al.
    Wang, Lihui
    A Study on Optimal Machine Setups Using an Energy Modeling Approach2012In: Transactions of the North American Manufacturing Research Institution of SME, 2012, Vol. 40, p. 571-579Conference paper (Refereed)
    Abstract [en]

    In this paper, energy models are developed based on the kinematic and dynamic behaviors of chosen machine tools. One significant benefit of the developed energy models is their inherited relationship to the design variables involved in the manufacturing processes. Therefore, they can be readily applied to optimize process parameters to reduce energy consumption. A new parallel kinematic machine Exechon is used as a case study to demonstrate the procedures of energy model development with direct relation to appropriate process parameters. The derived energy model is then used for simulation of drilling operations on aircraft components to demonstrate its feasibility. Simulation results indicate that the developed energy model has led to an optimized machine setup which only consumes less than one-third of the energy of an average machine setup over the workspace. This approach can be extended and applied to other machines to establish their energy models for green manufacturing.

  • 19. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Advances in 3D Data Acquisition and Processing for Industrial Applications2010In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 26, no 5, p. 403-413Article in journal (Refereed)
    Abstract [en]

    A critical task of vision-based manufacturing applications is to generate a virtual representation of a physical object from a dataset of point clouds. Its success relies on reliable algorithms and tools. Many effective technologies have been developed to solve various problems involved in dataacquisition and processing. Some articles are available on evaluating and reviewing these technologies and underlying methodologies. However, for most practitioners who lack a strong background on mathematics and computer science, it is hard to understand theoretical fundamentals of the methodologies. In this paper, we intend to survey and evaluate recent advances in data acquisition and progressing, and provide an overview from a manufacturing perspective. Some potential manufacturing applications have been introduced, the technical gaps between the practical requirements and existing technologies discussed, and research opportunities identified.

  • 20. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Current Status of 3D Data Acquisition and Processing Technologies2010Conference paper (Refereed)
  • 21. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Design of a Cobot with Three Omni-Wheels2009Conference paper (Refereed)
    Abstract [en]

    Collaborative robots (Cobots) have been proposed to guide and assist human operators to move heavy objects in a given trajectory. Most of the existing cobots us steering wheels; typical drawbacks of using steering wheels include (i) the difficulty to follow a trajectory with a curvature larger than that of the base platform, (ii) the difficulty to mount encoders on steering wheels due to self-spinning of the wheels, and (iii) the difficulty to quarantine dynamic control performance since it is purely kinematic control. In this paper, a new cobot with the omni-wheels has been proposed, and its design model has been developed, and a simulation has been conducted to validate this control performance.

  • 22. Bi, Z.M.
    et al.
    Wang, Lihui
    Design of a Reconfigurable Tripod Machine System and Its Application in Web-based Machining2008In: Smart Devices and Machines for Advanced Manufacturing, Springer London, 2008, p. 189-218Chapter in book (Refereed)
  • 23. Bi, Z.M.
    et al.
    Wang, Lihui
    Development and Simulation for the Control of a Collaborative Robot2008Conference paper (Refereed)
  • 24. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Dynamic Control Model of a Cobot with Three Omni-Wheels2010In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 26, no 6, p. 558-563Article in journal (Refereed)
    Abstract [en]

    In this paper, a new collaborative robot with omni-wheels has been proposed and its dynamic control has been developed and validated. Collaborative robots (Cobots) have been introduced to guide and assist human operators to move heavy objects in a given trajectory. Most of the existing cobots use steering wheels: typical drawbacks of using steering wheels include the difficulties to (i) follow a trajectory with a curvature larger than that of the base platform, (ii) mount encoders on steering wheels due to self-spinning of the wheels, and (iii) quarantine dynamic control performance since it is purely kinematic control. The new collaborative robot is proposed to overcome the above-mentioned shortcomings. The methodologies for its dynamic control are focused and the simulation has been conducted to validate the control performance of the system.

  • 25. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Energy Modelling of Machine Tools for Optimisation of Machine Setups2012In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 9, no 3, p. 607-613Article in journal (Refereed)
    Abstract [en]

    In this paper, a new energy model is developed based on the kinematic and dynamic behaviors of a chosen machine tool. One significant benefit of the developed energy model is their inherited relationship to the design variables involved in the manufacturing processes. Without radical changes of the machine tool's structure, the proposed model can be readily applied to optimize process parameters to reduce energy consumption. A new parallel kinematic machine Exechon is used as a case study to demonstrate the modeling procedure. The derived energy model is then used for simulation of drilling operations on aircraft components to verify its feasibility. Simulation results indicate that the developed energy model has led to an optimized machine setup which only consumes less than one-third of the energy of an average machine setup over the workspace. This approach can be extended and applied to other machines to establish their energy models for green and sustainable manufacturing.

  • 26. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Feasibility Study on a Collaborative Robot with Omni-Wheels2010Conference paper (Refereed)
    Abstract [en]

    Robotics has brought radical changes to maximise the productivity of modern manufacturing. However, a full  automation  is  not  always  advantageous;  sometimes  robots  and  human  being  must  work  together  in  a shared  environment  to  meet  specific  requirements.  A  robot  used  in  a  collaborative  environment  is  a collaborative robot. In this paper, a collaborative robot to assist human being’s locomotion is considered: omni-wheels  are  used  to  increase  the  flexibility  and  mobility  of  the  robot  and  they  are  controlled dynamically  to  confine  the  robot  in  a  prescribed  trajectory.  The  new  control  algorithms  are  developed  to meet the following challenges (a) unpredictable driving force from a human operator; (b) the rotation of an omni-wheel along two axes but with one independent motion; and (c) the strongly-coupled kinematics and dynamics of the mobile robot.

  • 27. Bi, Z.M.
    et al.
    Wang, Lihui
    Multidisciplinary Design Optimization of Reconfigurable Parallel Machining Systems2008Conference paper (Refereed)
  • 28. Bi, Z.M.
    et al.
    Wang, Lihui
    University of Skövde.
    Optimal Design of Reconfigurable Parallel Machining Systems2009In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 25, no 6, p. 951-961Article in journal (Refereed)
    Abstract [en]

    A reconfigurable machining system is usually a modularized system, and its configuration design concerns the selections of modules and the determination of geometric dimensions in some specific modules. All of its design perspectives from kinematics, dynamics, and control have to be taken into considerations simultaneously, and a multidisciplinary design optimization (MDO) tool is required to support the configuration design process. This paper presents a new MDO tool for reconfigurable machining systems, and it includes the following works: (i) the literatures on the computer-aided design of reconfigurable parallel machining systems have been reviewed with a conclusion that the multidisciplinary design optimization is essential, but no comprehensive design tool is available to reconfigurable parallel machining systems; (ii) a class of reconfigurable systems called reconfigurable tripod-based machining system has been introduced, its reconfiguration problem is identified, and the corresponding design criteria have been discussed; (iii) design analysis in all of the disciplines including kinematics, dynamics, and control have been taken into considerations, and design models have been developed to evaluate various design candidates; in particular, the innovative solutions to direct kinematics, stiffness analysis for the design configurations of tripod-based machines with a passive leg, and concise dynamic modelling have been provided; and (iv) A design optimization approach is proposed to determine the best solution from all possible configurations. Based on the works presented in this paper, a computer-aided design and control tool have been implemented to support the system reconfiguration design and control processes. Some issues relevant to the practical implementation have also been discussed.

  • 29. Bi, Z.M.
    et al.
    Wang, Lihui
    Visualisation and Verification of Communication Protocols for Networked Distribute Systems2010In: Enterprise Networks and Logistics for Agile Manufacturing, Springer London, 2010, p. 333-357Chapter in book (Refereed)
  • 30. Bi, Z.M.
    et al.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council of Canada .
    Lang, Sherman
    Current Status of Reconfigurable Assembly Systems2007In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 2, no 3, p. 303-328Article in journal (Refereed)
    Abstract [en]

    Reconfigurable Manufacturing System (RMS) is one of most promising paradigms that provide an effective solution to changes and uncertainties in a competitive manufacturing environment. A Reconfigurable Assembly System (RAS) is a key component of an RMS. In this paper, our survey on the development of RAS has been summarised. The objectives of this literature survey are to: clarify the needs and drivers in developing reconfigurable assembly systems identify both academic and practical issues critical to the development of reconfigurable assembly systems understand the state of the art of R&D related to the studies on the critical issues reveal the future research directions, which are mostly beneficial to manufacturing industries.

  • 31. Björkman, M.
    et al.
    Ståhl, J. -E
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Editorial2014In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 9, no 1, p. 1-3Article in journal (Refereed)
  • 32. Björkman, M.
    et al.
    Ståhl, J.-E.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Swedish Production Symposium 20122014In: International Journal of Manufacturing Research, Vol. 9, no 1Article in journal (Refereed)
  • 33. Björkman, M.
    et al.
    Ståhl, J.-E.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    The 5th International Swedish Production Symposium 20122014In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 9, no 1, p. 1-3Article in journal (Refereed)
  • 34. Buckholtz, B.
    et al.
    Ragai, I.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Remote equipment security in cloud manufacturing systems2016In: International Journal of Manufacturing Research, ISSN 1750-0591, Vol. 11, no 2, p. 126-143Article in journal (Refereed)
    Abstract [en]

    With the growing development of cloud manufacturing (CM) applications in industry, one concern potential users have is security of the data, remote machines and operators. Potential security risks in communication with remotely operated manufacturing equipment have been of recent interest. The purpose of this paper is to provide an overview of security measures being considered to ensure the protection of data being sent to physical machines in a CM system. Topics covered include: internet of things, remote equipment control, security concerns in remote equipment control, existing proposed security measures for remote equipment control, and the future outlook of remote equipment control and security in CM systems.

  • 35. 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.

  • 36. Cai, Ningxu
    et al.
    Wang, Lihui
    National Research Council of Canada.
    Feng, Hsi-Yung
    Adaptive Setup Planning of Prismatic Parts by Tool Accessibility Examination2005Conference paper (Refereed)
    Abstract [en]

    Setup planning for machining a part is to determine the number and sequence of setups (including machining features grouping in setups) and the part orientation of each setup. Tool accessibility plays a key role in this process. An adaptive setup planning approach for different types of multi-axis machine tools is proposed in this paper by investigating Tool Access Directions (TADs) of machining features, Tool Orientation Spaces (TOSs) of machine tools, and Primary Locating Directions (PLDs) of workpieces. In our approach, feasible TADs of a machining feature are predefined based on feature geometry and best practice knowledge, and denoted by unit vectors; The TOS of a machine tool is generated according to its configuration through kinematic analysis, and represented by a unit spherical surface patch; Primary locating directions and their priorities of a workpiece are determined based on the surface areas and the surface accuracy grades of non-machining surfaces. Starting from a 3-axis based machining feature grouping, setups for a 3-, 4- (or 3-axis with indexing table), or 5-axis machine can be achieved effectively by tool accessibility examination. A so-generated setup plan can provide not only the best coverage of machining features but the optimal orientation for each setup. Prismatic parts are considered in the proof-of-concept phase. Algorithms introduced here are implemented in MATLAB, and a case study is used to show the results.

  • 37. Cai, Ningxu
    et al.
    Wang, Lihui
    Feng, Hsi-Yung
    Adaptive setup planning of prismatic parts for machine tools with varying configurations2008In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 46, no 3, p. 571-594Article in journal (Refereed)
    Abstract [en]

    Setup planning for machining a part is to determine the number and sequence of setups (including machining features grouping in setups) and the part orientation of each setup. Tool accessibility plays a key role in this process. An adaptive setup planning approach for various multi-axis machine tools is proposed in this paper focusing on kinematic analysis of tool accessibility and optimal setup plan selection. In our approach, feasible Tool Access Directions (TADs) of machining features are denoted by partially sequenced unit vectors; The Tool Orientation Spaces (TOS) of different multi-axis machine tools are generated according to their configurations through a kinematic model, and represented on a unit spherical surface. Starting from a 3-axis-based machining feature grouping, all possible setup plans of a given part for different types of machine tools (3-axis, 3-axis with an indexing table, 4-axis, and 5-axis machines) can be achieved effectively by tool accessibility examination. The optimal setup plans are selected from obtained candidates by evaluating both their locating and grouping factors. A so-generated setup plan can provide not only the best coverage of machining features and the primary locating directions but the optimal orientations of the work-piece for each setup. Only prismatic parts are considered in this proof-of-concept study, and the algorithms introduced in this paper are implemented in MATLAB. A case study is conducted to validate the algorithms.

    Setup planning for machining a part is to determine the number and sequence of setups (including machining features grouping in setups) and the part orientation of each setup. Tool accessibility plays a key role in this process. An adaptive setup planning approach for various multi-axis machine tools is proposed in this paper focusing on kinematic analysis of tool accessibility and optimal setup plan selection. In our approach, feasible Tool Access Directions (TADs) of machining features are denoted by partially sequenced unit vectors; The Tool Orientation Spaces (TOS) of different multi-axis machine tools are generated according to their configurations through a kinematic model, and represented on a unit spherical surface. Starting from a 3-axis-based machining feature grouping, all possible setup plans of a given part for different types of machine tools (3-axis, 3-axis with an indexing table, 4-axis, and 5-axis machines) can be achieved effectively by tool accessibility examination. The optimal setup plans are selected from obtained candidates by evaluating both their locating and grouping factors. A so-generated setup plan can provide not only the best coverage of machining features and the primary locating directions but the optimal orientations of the work-piece for each setup. Only prismatic parts are considered in this proof-of-concept study, and the algorithms introduced in this paper are implemented in MATLAB. A case study is conducted to validate the algorithms.

  • 38. Cai, Ningxu
    et al.
    Wang, Lihui
    Feng, Hsi-Yung
    Enriched Machining Features and their Representation Scheme for Distributed Process Planning2004Conference paper (Refereed)
  • 39. Cai, Ningxu
    et al.
    Wang, Lihui
    National Research Council of Canada.
    Feng, Hsi-Yung
    GA based Adaptive Setup Planning toward Process Planning and Scheduling Integration2009In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 47, no 10, p. 2745-2766Article in journal (Refereed)
    Abstract [en]

    Setup planning of a part for more than one available machine is a typical combinatorial optimisation problem under certain constraints. It has significant impact not only on the whole process planning but also on scheduling, as well as on the integration of process planning and scheduling. Targeting the potential adaptability of process plans associated with setups, a cross-machine setup planning approach using genetic algorithms (GA) for machines with different configurations is presented in this paper. First, based on tool accessibility analysis of different machine configurations, partially sequenced machining features can be grouped into certain setups; then by responding to the requirements from a scheduling system, optimal or near-optimal setup plans are selected for certain criteria, such as cost, makespan and/or machine utilisation. GA is adopted for the combinatorial optimisation, which includes gene pool generation based on tool accessibility examination, setup plan encoding and fitness evaluation, and optimal setup plan selection through GA operations. The proposed approach is implemented in a GA toolbox, and tested using a sample part. The results demonstrate that the proposed approach is applicable to machines with varying configurations, and adaptive to different setup requirements from a scheduling system due to machine availability changes. It is expected that this approach can contribute to process planning and scheduling integration when a process plan is combined with setups for alternative machines during adaptive setupplanning.

  • 40. Cai, Ningxu
    et al.
    Wang, Lihui
    Feng, Hsi-Yung
    GA-based Adaptive Setup Planning with Machine Tool Capability and Availability2007In: Transactions of the North American Manufacturing Research Institution of SME, ISSN 1047-3025, Vol. 35, p. 25-32Article in journal (Refereed)
    Abstract [en]

    In a machine shop, setup planning of a part for more than one available machine is a typical combinatorial optimization problem under certain constraints. Targeting adaptability of setup plans for multiple machines, an across-machine setup planning approach using genetic algorithms is presented in this paper, including (1) gene pool generation, (2) setup plan encoding and fitness evaluation, and (3) optimal setup plan selection through GA operations. The proposed approach is implemented In a GA toolbox, and tested by a sample part. The results demonstrate that this approach is not only applicable to machines with varying configurations, but also adaptive to shop floor schedule changes due to uncertainty.

  • 41. Chang, Q.
    et al.
    Gao, R.
    Lei, Y.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wu, C.
    Cyber-Physical Systems in Manufacturing and Service Systems2015In: Mathematical problems in engineering (Print), ISSN 1024-123X, E-ISSN 1563-5147, Vol. 2015, p. 1-2Article in journal (Refereed)
  • 42. Chou, Y.-C.
    et al.
    Chen, C.-J.
    Tang, C.-W.
    Su, J.-H.
    Wang, Lihui
    Integration of Supply Chain Scheduling by Constraint Satisfactory2004Conference paper (Refereed)
  • 43.
    de Giorgio, Andrea
    et al.
    KTH.
    Romero, Mario
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Onori, Mauro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Human-machine Collaboration in Virtual Reality for Adaptive Production Engineering2017In: Procedia Manufacturing, ISSN 2351-9789, Vol. 11, p. 1279-1287Article in journal (Refereed)
    Abstract [en]

    This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.

  • 44.
    de Giorgio, Andrea
    et al.
    KTH.
    Romero, Mario
    KTH, School of Computer Science and Communication (CSC), Computational Science and Technology (CST).
    Onori, Mauro
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Human-machine Collaboration in Virtual Reality for Adaptive Production Engineering2017In: 27th International Conference on Flexible Automation and Intelligent Manufacturing, Elsevier, 2017, Vol. 11, p. 1279-1287Conference paper (Refereed)
    Abstract [en]

    This paper outlines the main steps towards an open and adaptive simulation method for human-robot collaboration (HRC) in production engineering supported by virtual reality (VR). The work is based on the latest software developments in the gaming industry, in addition to the already commercially available hardware that is robust and reliable. This allows to overcome VR limitations of the industrial software provided by manufacturing machine producers and it is based on an open-source community programming approach and also leads to significant advantages such as interfacing with the latest developed hardware for realistic user experience in immersive VR, as well as the possibility to share adaptive algorithms. A practical implementation in Unity is provided as a functional prototype for feasibility tests. However, at the time of this paper, no controlled human-subject studies on the implementation have been noted, in fact, this is solely provided to show preliminary proof of concept. Future work will formally address the questions that are raised in this first run.

  • 45. Endrias, D.H.
    et al.
    Feng, H.-Y.
    Ma, J.
    Wang, Lihui
    University of Skövde.
    Taher, M.A.
    A Combinatorial Optimization Approach for Evaluating Minimum-Zone Spatial Straightness Errors2012In: Measurement: Journal of the International Measurement Confederation, ISSN 0263-2241, Vol. 45, no 5, p. 1170-1179Article in journal (Refereed)
    Abstract [en]

    This paper presents a new and robust approach for the accurate evaluation of minimum-zone spatial straightness error from a set of coordinate measurement data points. The algorithm iteratively searches for the specific data points that define the minimum bound of the spatial straightness zone using combinatorial optimization. It is based on the fact that the minimum circumscribed cylinder of a point set, which is equivalent to the minimum spatial straightness zone of the measurement data, will pass through three, four, or five of the data points that constitute the convex hull vertices of the entire data set. Computed results have shown that although the presented approach may lead to increased computational time, it is robust and able to construct the exact minimum circumscribed cylinder for a given point set. The minimum-zone spatial straightness error can thus be evaluated with the best possible accuracy. The advantage of the presented algorithm is demonstrated via comparison with published computed results of existing algorithms.

  • 46. Fan, Zhaoyan
    et al.
    Gao, Robert X.
    Wang, Lihui
    Architecture Design of a Sensor-to-Web Interface for Remote Machine Condition Monitoring and Control2006Conference paper (Refereed)
  • 47. Feng, Hsi-Yung
    et al.
    Han, Zhengyu
    Banerjee, Avisekh
    Wang, Lihui
    University of Skövde.
    A Composite Fitting Model of Discrete Handbook Data for Peripheral End Milling2009In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 44, no 5-6, p. 437-446Article in journal (Refereed)
    Abstract [en]

    Machining data handbooks are important reference books in the machining industry, as they provide recommended process parameter values for common machining operations. The machining data, although covering a wide range of relevant cutting conditions, are only listed under discrete cutting conditions. Rough interpolation-based calculations are often needed in order to estimate the process parameter values at the desired cutting condition. In this work, a compositefitting model is presented to fit a composite functional curve through the discrete handbook data of recommended cutting speeds and feeds with respect to the cutting condition of radial depth of cut for peripheral end milling. The objective is to establish a functional relationship from the handbook data such that recommended cutting speed and feed can be obtained for any given radial depth of cut. According to the tabulated layout of the machining data, the entire range of the radial depth of cut is divided into three segments having distinctive formulations and trends. Constraints are then imposed to preserve the trends and smoothly connect the adjacent segments. As a possible application of the presented model, a case study of machining a rectangular pocket is provided. Machining time of a potential process plan is readily evaluated based on the cutting speeds and feeds obtained from the composite model.

  • 48. Gao, R.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Teti, R.
    Dornfeld, D.
    Kumara, S.
    Mori, M.
    Helu, M.
    Cloud-enabled prognosis for manufacturing2015In: CIRP annals, ISSN 0007-8506, E-ISSN 1726-0604, Vol. 64, no 2, p. 749-772Article in journal (Refereed)
    Abstract [en]

    Advanced manufacturing depends on the timely acquisition, distribution, and utilization of information from machines and processes across spatial boundaries. These activities can improve accuracy and reliability in predicting resource needs and allocation, maintenance scheduling, and remaining service life of equipment. As an emerging infrastructure, cloud computing provides new opportunities to achieve the goals of advanced manufacturing. This paper reviews the historical development of prognosis theories and techniques and projects their future growth enabled by the emerging cloud infrastructure. Techniques for cloud computing are highlighted, as well as the influence of these techniques on the paradigm of cloud-enabled prognosis for manufacturing. Finally, this paper discusses the envisioned architecture and associated challenges of cloud-enabled prognosis for manufacturing.

  • 49. Gernhardt, Benjamin
    et al.
    Miltner, Franz
    Vogel, Tobias
    Brocks, Holger
    Hemmje, Matthias
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A SEMANTIC REPRESENTATION FOR PROCESS-ORIENTED KNOWLEDGE MANAGEMENT BASED ON FUNCTIONBLOCK DOMAIN MODELS SUPPORTING DISTRIBUTED AND COLLABORATIVE PRODUCTION PLANNING2015In: PROCEEDINGS OF THE ASME 10TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE, 2015, VOL 2, AMER SOC MECHANICAL ENGINEERS , 2015Conference paper (Refereed)
    Abstract [en]

    Semantic knowledge representation, management, sharing, access, and re-use approaches can support collaborative production planning in a flexible and efficient as well as an effective way. Therefore, semantic-technology based representations of Collaborative Production Process Planning (CAPP) knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based semantic-enabled knowledge repositories supporting CAPP scenarios as required in the CAPP4SMES project [1]. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP4SMES request for a standardized CAPP-oriented product-knowledge- and production-feature representation that can be achieved by applying function-block based knowledge representation models. Semantic Web- and at the same time Cloud-based technologies, tool suites and application solutions which are based on process-oriented semantic knowledge representation methodologies such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozesess-orientiertes Innovationsmanagement, WPIM) [2] can satisfy these needs, supporting the semantic integration, management, access and re-use in a machine readable and integrated representation of distributed CAPP knowledge that is shared within a cloud-based centralized semantic-enabled knowledge repository. Furthermore semantic knowledge representation and querying add value to knowledge-based and computer-aided re-use of such knowledge within CAPP activities and, finally, pave the way towards further automating planning, simulation and optimization support in a semantic web for CAPP.

  • 50. Gernhardt, Benjamin
    et al.
    Miltner, Franz
    Vogel, Tobias
    Brocks, Holger
    Hemmje, Matthias
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A Semantic Representation for Process-Oriented Knowledge Management to Support Production Planning based on Function Block Domain Models and a Three-level Mediator Architecture2015Conference paper (Refereed)
    Abstract [en]

    Semantic knowledge representation, management, sharing, access, and re-use approaches can support collaborative production planning in a flexible and efficient as well as an effective way. Therefore, semantic-technology based representations of Collaborative Production Process Planning (CAPP) knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based semantic-enabled knowledge repositories supporting CAPP scenarios as required in the CAPP4SMES project [1]. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP4SMES request for a standardized CAPP-oriented product-knowledge- and production-feature representation that can be achieved by applying function-block based knowledge representation models. Semantic Web- and at the same time Cloud-based technologies, tool suites and application solutions which are based on process-oriented semantic knowledge representation methodologies such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozesess-orientiertes Innovationsmanagement, WPIM) [2] can satisfy these needs, supporting the semantic integration, management, access and re-use in a machine readable and integrated representation of distributed CAPP knowledge that is shared within a cloud-based centralized semantic-enabled knowledge repository. Furthermore semantic knowledge representation and querying add value to knowledge-based and computer-aided re-use of such knowledge within CAPP activities and, finally, pave the way towards further automating planning, simulation and optimization support in a semantic web for CAPP.

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