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  • 51. 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)
  • 52. 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.

  • 53.
    Fratini, Livan
    et al.
    Univ Palermo, Palermo, Italy..
    Ragai, Ihab
    Penn State Univ, Erie, PA 16563 USA..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    New trends in manufacturing processes research2019In: JOURNAL OF MANUFACTURING PROCESSES, ISSN 1526-6125, Vol. 43, p. 1-1Article in journal (Other academic)
  • 54.
    Fratini, Livan
    et al.
    Univ Palermo, Palermo, Italy.
    Ragai, Ihab
    Penn State Univ, Erie, PA 16563 USA.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    New trends in manufacturing systems research2019In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 52, p. 209-210Article in journal (Refereed)
  • 55.
    Fratini, Livan
    et al.
    University of Palermo, Palermo, Italy.
    Ragai, Ihab
    Penn State University, PA, United States.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Preface2019In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 34, p. 1-2Article in journal (Refereed)
  • 56.
    Fratini, Livan
    et al.
    University of Palermo, Palermo, Italy.
    Ragai, Ihab
    Penn State University, PA, United States.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Special issue of journal of manufacturing processes on new trends in manufacturing processes research2019In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 34, p. 8-9Article in journal (Refereed)
  • 57.
    Fratini, Livan
    et al.
    University of Palermo, Palermo, Italy.
    Ragai, Ihab
    Penn State University, PA, United States.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Special issue of journal of manufacturing systems on new trends in manufacturing systems research2019In: Procedia Manufacturing, E-ISSN 2351-9789, Vol. 34, p. 6-7Article in journal (Refereed)
  • 58. 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.

  • 59. 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.

  • 60. 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.

  • 61. Gernhardt, Benjamin
    et al.
    Vogel, Tobias
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Hemmje, Matthias
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Supporting production planning through semantic mediation of processing functionality2016Conference paper (Refereed)
    Abstract [en]

    Semantic approaches for knowledge representation and mana­gement as well as knowledge sharing, access and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient and effective way. Therefore, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required in the CAPP-4-SMEs project. Beyond that, Small and Medium Enterprises (SMEs) as represented in CAPP-4-SMEs request for a standardized production-feature representation. That can be achieved by applying so-called Function Block (FB) based knowledge representation models. Web-based and at the same time Cloud-based tool suites which are based on process-oriented semantic knowledge-representation metho­dologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy these needs. In this way, WPIM can be applied to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in a machine readable and integrated representation. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. Furthermore, semantic knowledge representation and querying will add value to the knowledge-based and computer-aided re-use of such machine-readable knowledge resources within CAPP activities. Finally, it will pave the way towards further automating planning, simulation and optimization in a semantic-web for CAPP.

  • 62. Gernhardt, Benjamin
    et al.
    Vogel, Tobias
    Givehchi, Mohammad
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Hemmje, Matthias
    Knowledge-Based Production Planning Within the Reference Planning Process Supporting Manufacturing Change Management2016In: Proceedings of the ASME 11TH International Manufacturing Science and Engineering Conference, 2016, VOL 2, AMER SOC MECHANICAL ENGINEERS , 2016Conference paper (Refereed)
    Abstract [en]

    The manufacturing of a product takes place in several partial steps and these mostly in different locations to save tax or to use the best providers. Therefore, in the era of Internet of Things (IoT) and modem Intelligent Production Environments (IPE) are going to be inevitably based on a cloud-based repository and distributed architecture to make data and information accessible everywhere as well as development processes and knowledge available for worldwide cooperation. Semantic approaches for knowledge representation and management as well as knowledge sharing, access, and re-use can support Collaborative Adaptive Production Process Planning (CAPP) in a flexible, efficient, and effective way. Thus, semantic representations of such CAPP knowledge integrated into a machine readable process formalization is a key enabling factor for sharing such knowledge in cloud-based knowledge repositories supporting CAPP scenarios as required for e.g., Small and Medium Enterprises (SMEs). When such contributors work together on a product component production planning, they exchange component production and manufacturing change information between different planning subsystems which require, e.g., a standardized product-feature and production-machine feature representation. These data exchanges are mostly based on applying the already established Standard for the Exchange of Product model data (STEP) for the computer-interpretable representation and exchange of product manufacturing information. Furthermore, the planning process can be supported by so-called Function Block (FB) based knowledge representation models, serving as a high-level planning-process knowledge-resource template. Web-based and at the same time Cloud-based tool suites, which are based on process-oriented semantic knowledge-representation methodologies, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM) can satisfy the needs of representing such planning processes and their knowledge resources. In this way, WPIM can be used to support the integration and management of distributed CAPP knowledge, as well as its access and re-use in Manufacturing Change Management (MCM) including Assembly-, Logistics and Layout Planning (ALLP). Therefore, also a collaborative planning and optimization for mass production in a machine readable and integrated representation is possible. On the other hand, that knowledge can be shared within a cloud-based semantic knowledge repository. To integrate all these functionalities, this paper introduces a new method, called Knowledge-based Production Planning (KPP) and outlines the advantages of integrating CAPP with Collaborative Manufacturing Change Management (CMCM). In this way, an enabling basis for achieving ALLP interoperability in Distributed Collaborative Manufacturing and Logistics will be demonstrated.

  • 63. Gernhardt, Benjamin
    et al.
    Vogel, Tobias
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Hemmje, Matthias
    IMPLEMENTATION OF A KNOWLEDGE-BASED PRODUCTION PLANNING INCLUDING A DIRECT MANIPULATIVE PROCESS EDITOR AND A MEDIATOR ARCHITECTURE2017In: PROCEEDINGS OF THE ASME 12TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE - 2017, VOL 3, AMER SOC MECHANICAL ENGINEERS , 2017Conference paper (Refereed)
    Abstract [en]

    Today, in the era of modern Intelligent Production Environments (IPE) and Industry 4.0, the manufacturing of a product takes place in various partial steps and these mostly in different locations, potentially distributed all over the world. The producing companies must assert in the global market and always find new ways to cut costs by saving tax, changing to the best providers, and by using the most efficient and fastest production processes. Furthermore, they must be inevitably based on a cloud-based repository and distributed architectures to make data and information accessible everywhere as well as development processes and knowledge available for a worldwide cooperation. A so called Collaborative Adaptive (Production) Process Planning (CAPP) can be supported by semantic approaches for knowledge representation and management as well as knowledge sharing, access, and re-use in a flexible and efficient way. In this way, to support CAPP scenarios, semantic representations of such knowledge integrated into a machine-readable process formalization is a key enabling factor for sharing in cloud-based knowledge repositories. This is especially required for, e.g., Small and Medium Enterprises (SMEs). When SMEs work together on a production planning for a joint product, they exchange component production and manufacturing change information between different planning subsystems. These exchanges are mostly based on the already well-established Standard for the Exchange of Product model data (STEP), not least to obtain a computer-interpretable representation. Moreover, so-called Function Block (FB) Domain Models could support these planning process. FBs serve as a high-level planning-process knowledge-resource template and to the representation of knowledge. Furthermore, methodologies are required, which based on process-oriented semantic knowledge-representation, such as Process-oriented Knowledge-based Innovation Management (German: Wissens-basiertes Prozess-orientiertes Innovations Management, WPIM). WPIM is already a web and cloud-based tool suites and can represent such planning processes and their knowledge resources and can therefore be used to support the integration and the management of distributed CAPP knowledge in Manufacturing Change Management (MCM), as well as its access and re-use. That is also valid for Assembly-, Logistics- and Layout Planning (ALLP). On the one hand, a collaborative planning in a machine-readable and integrated representation will be possible as well as an optimization for mass production. On the other hand, within a cloud-based semantic knowledge repository, that knowledge can be shared with all partners and contributors. To combine all these functionalities, in 2016 we have already introduced a method, called Knowledge-based Production Planning (KPP). We outlined the theoretical advantages of integrating CAPP with Collaborative Manufacturing Change Management (CMCM) in the last year at MSEC16. In this Paper, we will demonstrate our first implementations of the KPP application with an integrated visual direct manipulative process editor as well as a first prototype of our mediator architecture with a semantic integration including a query library based on the KPP ontology.

  • 64. Givehchi, M.
    et al.
    Ng, A.H.C.
    Wang, Lihui
    University of Skövde.
    Spot-Welding Sequence Planning and Optimization Using a Hybrid Rule-Based Approach and Genetic Algorithm2011In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 27, no 4, p. 714-722Article in journal (Refereed)
    Abstract [en]

    Performing assembly planning to find a valid hierarchical assembling structure of a product (i.e. Manufacturing Bill of Materials or MBOM) based on the constraints and necessities inferred from or declared by different sources is potentially complicated. On the other hand, Engineering Changes (EC) may drastically affect the constraints and necessities which the planning of an MBOM was based on. Managing ECs to evaluate and propagate their effects on the upstream data used in assembly planning and downstream activities and information is crucial but problematic. Often it is possible to define a set of rules for the constraints and necessities of assembly planning and find solutions or check validity of solutions based on the rule-set. This paper proposes a rule-based assembly planning method and introduces the concepts and standard notations on how structured rule-sets can be derived from descriptive rules and then used in an algorithm for generating or validating MBOMs. The method was partially automated and successfully employed along with a commercial Virtual Manufacturing package integrated with an in-house developed GA-based sequence optimizer and applied to the sequence optimization in minimizing the cycle time of the robotic spot welding operations for a sheet-metal assembly found in automotive industry.

  • 65. Givehchi, Mohammad
    et al.
    Haghighi, Azadeh
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Adaptive Distributed Process Planning and Executions for Multi-tasking Machining Centers with Special Functionalities2015Conference paper (Refereed)
    Abstract [en]

    Today, the dynamic market requires manufacturing firms to possess a high degree of adaptability to deal with shop-floor uncertainties. Specifically targeting SMEs active in the metal cutting sector who normally deal with intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Cloud-DPP elaborates a two-layer distributed adaptive process planning based on function-block technology and cloud concept. One of the challenges of companies is to machine as many part features as possible in a single setup on a single machine. Nowadays, multi-tasking machines are widely used due to their various advantages such as reducing setup times and increasing part accuracy. However, they also possess programming challenges because of their complex configuration and multiple machining functions. This paper reports the latest state of design and implementation of Cloud-DPP methodology to support parts with a combination of milling and turning features, and process planning for multi-tasking machining centers with special functionalities to minimize the number of setups. The contributions of this work are: representation of machining states and part transfer functionality, support of multi-tasking machines in adaptive setup merging, development of special function blocks to handle sub-setups and transitions, and finally generation of function-block network for the merged setups. The developed prototype is validated through a case study.

  • 66.
    Givehchi, Mohammad
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Haghighi, Azadeh
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Cloud-DPP for distributed process planning of mill-turn machining operations2017In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 47, p. 76-84Article in journal (Refereed)
    Abstract [en]

    Today, the dynamic market requires manufacturing firms to possess a high degree of adaptability to deal with shop-floor uncertainties. Specifically targeting SMEs active in the metal cutting sector who normally deal with intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Cloud-DPP elaborates a two-layer distributed adaptive process planning based on function-block technology and cloud concept. One of the challenges of companies is to machine as many part features as possible in a single setup on a single machine. Nowadays, multi-tasking machines are widely used due to their various advantages such as reducing setup times and increasing part accuracy. However, they also possess programming challenges because of their complex configuration and multiple machining functions. This paper reports the latest state of design and implementation of Cloud-DPP methodology to support parts with a combination of milling and turning features, and process planning for multi-tasking machining centers with special functionalities to minimize the number of setups. The contributions of this work are: representation of machining states and part transfer functionality, support of multi-tasking machines in adaptive setup merging, development of special function blocks to handle sub-setups and transitions, and finally generation of function block network for the merged setups. The developed prototype is validated through a case study.

  • 67.
    Givehchi, Mohammad
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Haghighi, Azadeh
    KTH, School of Chemical Science and Engineering (CHE), Chemical Engineering and Technology, Chemical Technology.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Generic machining process sequencing through a revised enriched machining feature concept2015In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 37, p. 564-575Article in journal (Refereed)
    Abstract [en]

    Nowadays, small and medium-sized enterprises (SMEs) require a highly competitive process planning approach in order to survive. This mainly is due to the abrupt and continuous changes that occur every day in the production plant. This paper proposes a generic process sequencing approach that due to its independency to available resources can increase adaptability and flexibility of the system. The proposed method can be used by the Cloud-DPP (distributed process planning) in an integrated cyber-physical system. This rule-based approach requires the definition of a new revised enriched machining feature concept. The proposed concept not only possesses information of the machining feature itself (geometrical information, tolerances and coordinates system), but also contains additional information that are discussed in detail throughout the paper. A data format has been defined for the introduced additional data and the machinability rule has been defined as the key rule for sequencing. The sequencing approach in this work applies four sets of rules but can be extended if new rules are needed. The proposed method is then validated through a case study.

  • 68.
    Givehchi, Mohammad
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Haghighi, Azadeh
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Latest Advances in Function Block Enabled Adaptive Process Planning2015In: Virtual Machining Process Technology, 2015Conference paper (Refereed)
    Abstract [en]

    Due to various changes and uncertainties on machining shop floors, flexibility and adaptability become the key factors for a company’s survival. Small and medium-sized enterprises (SMEs) are subject to higher uncertainties as they are facing small volumes and high product mix. This paper gives an overview of the recent advances in function block enabled adaptive process planning that can deal with the mentioned challenges. The function block enabled approach for process planning and CNC control has been studied through a case study. According to this approach, a process plan is generated at two different levels. The higher generic level which performs machine-neutral planning is achieved according to the enriched machining feature concept. The generic plan is then converted into a series of event-driven function blocks and then dispatched to function block enabled CNC controllers. The machine-specific resources are then applied at the controller level. 

  • 69. Givehchi, Mohammad
    et al.
    Ng, Amos H.C.
    Wang, Lihui
    University of Skövde, Sweden.
    Evolutionary optimization of robotic assembly operation sequencing with collision-free paths2011In: Journal of manufacturing systems, ISSN 0278-6125, E-ISSN 1878-6642, Vol. 30, no 4, p. 196-203Article in journal (Refereed)
    Abstract [en]

    Many problems in the lifecycle of product and production development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and virtual manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described.

  • 70. Givehchi, Mohammad
    et al.
    Ng, Amos
    Wang, Lihui
    A Rule-Based Assembly Planning Method Applied in Sequence Optimization2010Conference paper (Refereed)
  • 71. Givehchi, Mohammad
    et al.
    Ng, Amos
    Wang, Lihui
    University of Skövde.
    An Evolutionary Operation Sequence Optimization Tool for Robotic Spot Welding Based on Collision-Free Path Planner in Virtual Manufacturing2011In: Transactions of the North American Manufacturing Research Institution of SME, 2011, Vol. 39Conference paper (Refereed)
    Abstract [en]

    Many problems in the lifecycle of Product and Production Development (PPD) can be formulated as optimization problems. But in most of the real-world cases, they are too complex to be solved by analytical models or classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed to create virtual representation of products and processes before any physical realization is conducted. Synergy of these two domains is of interest in this paper where planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product is desired. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. Accordingly, a novel toolset with integration of evolutionary optimization and a commercial VM environment is developed. More specifically, the latest feature which takes advantage of the collision avoidant segment path planning functionality of the VM tool and integrates it with the sequence optimizer is described.

  • 72. Givehchi, Mohammad
    et al.
    Ng, Amos
    Wang, Lihui
    University of Skövde.
    An Integrated Approach to Spot Welding Sequence Planning and Optimization2010Conference paper (Refereed)
    Abstract [en]

    Almost in every discipline involved in Product and Production Development (PPD), optimization problems arrive. These real-world problems are too complex to be solved by analytical models and classical optimization methods. CAx and Virtual Manufacturing (VM) tools are on the other hand being employed more and more to create virtual representation models of the products under development and their related production facilities, processes, and systems in a virtual environment before any physical realization is conducted. Synergy of these two domains is of interest in this paper where a PPD problem requiring planning a process with the minimum cycle-time for assembling a spot welded sheet-metal product was solved. The methodology suggests an extendible virtual manufacturing-based optimization approach using evolutionary algorithms. The methodology is also required to be partially compliant to the concept of integrated Product-Process-Resource planning and optimization. An optimization tool is developed accordingly for operation sequence optimization integrated with a commercial VM environment.

  • 73. Givehchi, Mohammad
    et al.
    Ng, Amos
    Wang, Lihui
    Operation Sequence Optimization Using an Extended Virtual Manufacturing Tool2011Conference paper (Refereed)
  • 74. Givehchi, Mohammad
    et al.
    Schmidt, Bernard
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Knowledge-based Operation Planning and Machine Control by Function Blocks in Web-DPP2013In: Advances in Sustainable and Competitive Manufacturing Systems: 23rd International Conference on Flexible Automation & Intelligent Manufacturing, Springer International Publishing , 2013, p. 665-679Conference paper (Refereed)
    Abstract [en]

    Today, the dynamic market requires manufacturing firms to possess high degree of adaptability and flexibility to deal with shop-floor uncertainties. Specifically, targeting SMEs active in the machining and metal cutting sector who normally deal with complex and intensive process planning problems, researchers have tried to address the subject. Among proposed solutions, Web-DPP elaborates a two-layer distributed adaptive process planning system based on function-block technology. Function-block enabled machine controllers are one of the elements of this system. In addition, intensive reasoning based on the features data of the products models, machining knowledge, and resource data is needed to be performed inside the function blocks in machine controller side. This paper reports the current state of design and implementation of a knowledge-based operation planning module using a rule-engine embedded in machining feature function blocks, and also the design and implementation of a common interface (for CNC milling machine controller and its specific implementation for a specific commercial controller) embedded in the machining feature function blocks for controlling the machine. The developed prototype is validated through a case-study.

  • 75.
    Givehchi, Mohammad
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Human-system interaction in factory of future: A case study about using new generation of hand-held devices in industry2014Conference paper (Refereed)
    Abstract [en]

    Motivated by the requirements, paradigm shifts, and system design trends in different system engineering disciplines, high beneficiary potentials for using new trends in industrial automation on shop floors is sited. In general, production systems of future from conceptual research perspective of this research are envisioned as context-aware ubiquitous sociotechnical systems among elements of Internet of Things that are cloud-enabled and have the purpose of processing materials and production. In this paper, usage of new generation of off-theshelf general-purpose smart hand-held devices as enabling technology in such an envisioned system is investigated through a case study. The case study involves design and development of a prototype system for demonstration and testing purposes. It shows how the user can take advantage of a general-purpose tablet to interact with the system. The interaction starts by finding the context of a machine or resource in proximity of the user on shop floor and invoking available services such as monitoring and control. A natural intuitive interaction with the system enabled by the built-in sensors of the tablet in control of a robot is also demonstrated.

  • 76.
    Gu, Song
    et al.
    Chengdu Aeronaut Polytech, Dept Aeronaut Engn, Chengdu 610100, Sichuan, Peoples R China..
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Hao, Wei
    Chengdu Aeronaut Polytech, Dept Aeronaut Engn, Chengdu 610100, Sichuan, Peoples R China..
    Du, Yingjie
    Chengdu Aeronaut Polytech, Dept Aeronaut Engn, Chengdu 610100, Sichuan, Peoples R China..
    Wang, Jian
    Chengdu Aeronaut Polytech, Dept Aeronaut Engn, Chengdu 610100, Sichuan, Peoples R China..
    Zhang, Weirui
    Chengdu Aeronaut Polytech, Dept Aeronaut Engn, Chengdu 610100, Sichuan, Peoples R China..
    Online Video Object Segmentation via Boundary-Constrained Low-Rank Sparse Representation2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 53520-53533Article in journal (Refereed)
    Abstract [en]

    Graphcut-based algorithm is adopted in many video object segmentation systems because different terms can be probabilistically fused together in a framework. Constructing spatio-temporal coherences is an important stage in segmentation systems. However, many steps are involved when computing a key term with good discriminative power. If the cascade steps are adopted, the inaccurate output of the previous step will definitely affect the next step, leading to inaccurate segmentation. In this paper, a key term that is computed by a single framework referred to as boundary-constrained low-rank sparse representation (BCLRSR) is proposed to achieve the accurate segmentation. By treating the elements as linear combinations of dictionary templates, low-rank sparse optimization is adopted to achieve the spatio-temporal saliency. For adding the spatial information to the low-rank sparse model, a boundary constraint is adopted in the framework as a Laplacian regularization. A BCLRSR saliency is then obtained by the represented coefficients, which measure the similarity between the elements in the current frame and the ones in the dictionary. At last, the object is segmented by minimizing the energy function, which is formalized by the spatio-temporal coherences. The experiments on some public datasets show that our proposed algorithm outperforms the state-of-the-art methods.

  • 77. Gustavsson, P.
    et al.
    Holm, M.
    Syberfeldt, A.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Human-robot collaboration - Towards new metrics for selection of communication technologies2018In: Procedia CIRP, Elsevier, 2018, Vol. 72, p. 123-128Conference paper (Refereed)
    Abstract [en]

    Industrial robot manufacturers have in recent years developed collaborative robots and these gains more and more interest within the manufacturing industry. Collaborative robots ensure that humans and robots can work together without the robot being dangerous for the human. However, collaborative robots themselves are not enough to achieve collaboration between a human and a robot; collaboration is only possible if a proper communication between the human and the robot can be achieved. The aim of this paper is to identify and categorize technologies that can be used to enable such communication between a human and an industrial robot.

  • 78. Hao, Qi
    et al.
    Shen, Weiming
    Stecca, G.
    Wang, Lihui
    Towards an Internet Enabled Cooperative Manufacturing Management Framework2003In: Processes and Foundations for Virtual Organizations, Boston: Kluwer Academic Publishers , 2003, p. 191-200Chapter in book (Refereed)
  • 79. Hao, Qi
    et al.
    Shen, Weiming
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council of Canada .
    Collaborative Manufacturing Resource Scheduling Using Agent-Based Web Services2006In: International Journal of Manufacturing Technology and Management (IJMTM), ISSN 1368-2148, E-ISSN 1741-5195, Vol. 9, no 3-4, p. 309-327Article in journal (Refereed)
    Abstract [en]

    The rapidly changing needs and opportunities of today's global market require unprecedented levels of inter-operability to integrate diverse information systems to share knowledge and collaborate among organisations. The combination of web services and software agents opens up a sophisticated computing paradigm for meeting such requirements. This paper proposes a component called Agent-based Web Service (AWS) to provide manufacturing scheduling services for enterprise collaboration. A unique property of this AWS-based integration approach is that the scheduling process of an order is orchestrated on the internet through negotiation among AWSs. Moreover, the bid proposed by an AWS is supported by the dynamic scheduling results of manufacturing resources inside the enterprise. A prototype system for AWS-based manufacturing scheduling is implemented and connected to the backend multiagent dynamic manufacturingscheduling system.

  • 80. Hao, Qi
    et al.
    Shen, Weiming
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council Canada.
    Towards a Cooperative Distributed Manufacturing Management Framework2005In: Computers in industry (Print), ISSN 0166-3615, E-ISSN 1872-6194, Vol. 56, no 1, p. 71-84Article in journal (Refereed)
    Abstract [en]

    Advanced manufacturing systems need to be developed for enterprises to cooperate with each other in order to survive in the increasingly competitive global market. In this paper, manufacturing management issues are addressed at three levels: virtual enterprise (inter-enterprise), enterprise (intra-enterprise) and shop floor levels. An Internet enabled framework based on Web Services and agents for cooperative manufacturing management is proposed. An integration environment consisting of an agent based scheduling system, a Web based remote monitoring and control system, and corresponding services is designed and developed for the management, monitoring and control of the shop floor. Implementation details of the shop floor management environment are presented and some future work is prospected.

  • 81. Hao, Qi
    et al.
    Shen, Weiming
    Wang, Lihui
    National Research Council of Canada.
    Lang, Sherman Y. T.
    Cooperative Scheduling for Inter-Enterprise Manufacturing Resources Sharing2003Conference paper (Refereed)
    Abstract [en]

    This paper presents a cooperative virtual enterprise approach targeting the manufacturing resource sharing among small and medium enterprises. With intelligent agents and Web Services technologies being adopted, the proposed approach possesses a number of distinguishing characteristics, such as loosely-coupled distributed architecture, internal privacy protection, secure separation of information and autonomous operation. An enterprise model, partner search and selection mechanisms, coordination modes and operation monitoring mechanisms are presented in details. The proposed approach emphasizes the enterprise to maximize its profitability, which is always regarded as a higher priority over other concerns.

  • 82. Hao, Qi
    et al.
    Wang, Lihui
    Shen, Weiming
    Chou, Y.-C.
    Function Block Based Shop Floor Integration2004Conference paper (Refereed)
  • 83. Helgoson, M.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Karlsson, R.
    Givehchi, Mohammad
    Tedeborg, M.
    Concept for function block enabled process planning towards multi-site cloud collaboration2014In: ASME 2014 International Manufacturing Science and Engineering Conference, MSEC 2014 Collocated with the JSME 2014 International Conference on Materials and Processing and the 42nd North American Manufacturing Research Conference, New York: ASME Press, 2014Conference paper (Refereed)
    Abstract [en]

    In global enterprises an essential challenge is how to enable efficient sharing of knowledge, capacity, and resources in order to meet demands on speed, flexibility and adaptability. This paper highlights challenges and aspects regarding framework and technical platform for process planning that enable global multi-site collaboration. To get an industrial perspective, this topic is discussed in the context of Sandvik Coromant's globally distributed application centers. Further on, function block technology as enabling technology to achieve flexible and adaptable process planning as a part of the framework is presented and discussed together with results from the on-going research work.

  • 84. Holm, M.
    et al.
    Adamson, G.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Enhancing adaptive production using IEC 61499 event-driven function blocks2013In: 41st north american manufacturing research conference, Society of Manufacturing Engineers , 2013, p. 420-429Conference paper (Refereed)
    Abstract [en]

    Reduction of production costs and the ability to continuously improve is a must for every manufacturer. High availability in a dynamic and complex production environment demands adaptability to recurring changes. Each device within the production systems holds more and more intelligence and computing power which supports an approach implementing the standard of IEC 61499 to enhance adaptive production by enabling a distributed automation system with improved productivity. Research approaching IEC 61499 is investigated and reported in this paper, covering both control of manufacturing equipment and adaptive process planning. The objective is to develop methodologies for process planning as well as machine control and monitoring for machining and assembly operations in a dynamic, adaptive and distributed environment using event-driven function blocks.

  • 85. Holm, M.
    et al.
    Garcia, A. C.
    Adamson, G.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Adaptive decision support for shop-floor operators in automotive industry2014In: Procedia CIRP, 2014, p. 440-445Conference paper (Refereed)
    Abstract [en]

    Today's operators on factory shop-floors are often not stationed, dealing with a single or few tasks but have increasing responsibilities demanding enhanced skills and knowledge in a production environment where any disturbance must be settled with adequate actions without delay to keep optimum output. To be able to respond to these demands, the operators need dynamic, distributed and adaptive decision support in real-Time, helping them to distinguish decision options and maximizing productivity despite incoming stochastic events. The minimum of time and option for operators to consider appropriate action both during normal production and when facing unexpected or unscheduled events point out the need of adaptive decision support for operators. When initiating this research project the question from the industry partner was the following: In what ways is it possible to support operators in making decisions for optimal productivity? By targeting this problem this paper introduces a novel framework for an adaptive decision-support system enabled by event-driven function blocks and based on decision logics. The proposed decision support systems' ability to adapt to the actual conditions on the shop-floor is validated through a case study, and its capability is compared to the voice message system installed on-site.

  • 86. Holm, M.
    et al.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Adamson, G.
    Moore, P.
    Framework for an adaptive decision support system for industrial shop-floor operators2014In: 12th Annual Industrial Simulation Conference, ISC 2014, 2014, p. 75-80Conference paper (Refereed)
    Abstract [en]

    Today's shop-floor operators' working tasks often stretches over a broad spectra of jobs; from ordinary production assignments to handling errors and performing maintenance. Demands for enhanced skills and knowledge are constantly raised to limit the consequences of tool breakage, machine down time and other stochastic events negatively affecting the production. To be able to meet these increasing demands a framework for a distributed and adaptive decision support system is proposed. It will help the shop-floor operator to distinguish between decision options and minimize time to consider appropriate actions to maximize productivity both during normal production and when facing unexpected or unscheduled events. "In what ways is it possible to support operators in making decisions for optimal productivity?" was the opening question from the industry partner when beginning this research. Targeting this question a novel framework for an adaptive decision support system (DSS) enabled by event- driven function blocks, based on decision logics is proposed. Its ability to adapt to the actual conditions on the shop-floor is compared to a currently used voice message system in a test case.

  • 87. Holm, Magnus
    et al.
    Adamson, Goran
    Moore, Philip
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Univ Skövde, Sweden.
    Why I want to be a future Swedish shop-floor operator2016In: 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. 1101-1106Conference paper (Refereed)
    Abstract [en]

    When looking in rear view mirrors the Swedish as well as the international production industries can overview several years of progress covering all aspects of production. Production methodologies and machines etc. have changed and evolved, and so has the environment of the shop-floor operator. The demands on the shop-floor operators have grown from simple monotonic tasks with low complexity to pro-active team work requiring flexibility, continuous improvements and a holistic approach. With a base in a study where production and HR-managers at six Swedish manufacturing industries have been interviewed this paper identifies the role of today's and the future Swedish shop-floor operator. The response to the described role of the future operator is compiled from the ones who will become the future Swedish shop-floor operators - today's teenagers attending technical high-school. Their views of the environment of the future shop-floor operator are described by accuracy, development, a good working environment and team work. The paper also reveals what the offer should include to make these teenagers say: I want to be a future Swedish shop-floor operator.

  • 88. Holm, Magnus
    et al.
    Adamson, Göran
    Wang, Lihui
    An IEC 61499 Function Block based Approach for CNC Machining Operations2012Conference paper (Refereed)
    Abstract [en]

    In order to create an adaptive and interoperable CNC control system to explore the full functionality of CNC machine tools and to surpass the shortcomings and restrictions of the current CNC control standard using G-codes, an IEC 61499 function block based control system model has been developed. Basic machining operations are identified and classified as machining features, which are wrapped into Machining Feature Function Blocks (MF-FBs) with algorithms. For the machining of a part, the required MF-FBs are selected and combined into a Composite Function Block, comprising the correct control instructions for machining the part.The event-driven nature of these function blocks enables the run-time selection of appropriate algorithms and control of their correct behavior and dynamic execution, supporting the system’s ability to act in response to actual conditions and manufacturing requirements. Being truly adaptive makes it possible that different available machine tools be selected to machine a part with the appropriate control code generated at runtime. This eliminates the tedious CNC programming effort, and therefore no predefined, machine-specific control code has to be generated in advance. The use of generic function blocks for encapsulation of machining know-how in algorithms makes machines and CNC systems independent and therefore portable, reusable and interoperable.

  • 89. Holm, Magnus
    et al.
    Adamson, Göran
    Wang, Lihui
    IEC 61499 – Enabling Control of Distributed Systems beyond IEC 61131-32012Conference paper (Refereed)
  • 90. Holm, Magnus
    et al.
    Adamson, Göran
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Moore, Philip
    The Future Swedish Shop-Floor Operator - Interviews with Production Managers2014Conference paper (Refereed)
    Abstract [en]

    This paper is based on a study in which production and HR managers at six Swedish manufacturing industries have been interviewed about the role of the shop-floor operator, taking off in today’s situation in trying to identify the future one. As well as the production methods and the machines etc. in the production system continuously evolve, so does the environment of the shop-floor operator. Increasing complexity in the production systems raises demands on the operators’ ability to handle ICT-tools to gain decision support and knowledge needed in the future shop-floor environment. 

  • 91. Holm, Magnus
    et al.
    Danielsson, Oscar
    Syberfeldt, Anna
    Moore, Philip
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems.
    Adaptive instructions to novice shop-floor operators using Augmented Reality2017In: JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING, ISSN 2168-1015, Vol. 34, no 5, p. 362-374Article in journal (Refereed)
    Abstract [en]

    This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators' ability to learn and master new tasks.

  • 92. Holm, Magnus
    et al.
    Givehchi, Mohammad
    Mohammed, Abdullah
    Wang, Lihui
    Web Based Monitoring and Control of Distant Robotic Operations2012Conference paper (Refereed)
    Abstract [en]

    In order to improve the production efficiency while facing today’s manufacturing uncertainty, responsive and adaptive capabilities for rapid production changes are essential. This paper presents how dynamic control and real-time monitoring (embedded in a web-based Wise-ShopFloor framework) can integrate virtual models with real shop floors. Wise-ShopFloor (Web-based integrated sensor-driven e-ShopFloor) uses Java technologies (e.g., Java Servlet and Java3D) for implementing the system. It allows the operators, both remote and on-site, to monitor and control machines, devices and operations on a shop floor, based on run-time information from the connected machines, devices and their sensors. Two case studies are presented to demonstrate the approach towards web-based adaptive manufacturing. The first demonstrating how OPC-technology is used to improve the monitoring and control capabilities of the production and the second one focusing on remote control of a robot eliminating the need of motion planning and tedious robot programming.

  • 93. Hoshi, T.
    et al.
    Wang, Lihui
    Block Machining Pilot Shop1996Conference paper (Refereed)
  • 94. Huang, Ying
    et al.
    Wang, Lihui
    Machining Feature Based Clamping Force Optimization2000Conference paper (Refereed)
  • 95. Huang, Ying
    et al.
    Wang, Lihui
    Integrated Manufacturing Technologies Institute, National Research Council Canada.
    Realizing High Accuracy Machining by Applying Optimal Clamping Forces2004In: International journal of computer applications in technology, ISSN 0952-8091, E-ISSN 1741-5047, Vol. 19, no 2, p. 107-118Article in journal (Refereed)
    Abstract [en]

    In this research, appropriate magnitudes of clamping forces and their applying methods are studied to improve machining accuracy. The objective of this study is to find a minimum-clamping load that must be applied to keep a workpiece in static equilibrium and to assure that the total workpiece deformation is minimized in a machining process. In particular, a machining feature-based clamping force optimization model is presented for this purpose. Through cutting experiments, it is observed that the maximum cutting forces occur in different directions for each machining feature. These maximum cutting forces are measured and integrated into a machining feature-based cutting force database. The deformation of a workpiece is then estimated using finite element analysis, when clamping force and cutting force along tool path are loaded. By combining the results of the above two steps, a mathematical optimization model is formulated. This model not only makes it possible to minimize the workpiece's deformation under several cutting operations in one machining process, but also finds optimum clamping forces exerted at the contact regions. The results of the case study demonstrate the effectiveness and validity of the methodology, which shows promise of improving the quality of machined products based on the optimized fixture design and set-up.

  • 96. Huang, Ying
    et al.
    Wang, Lihui
    Hoshi, T.
    Development of Fixture CAD System with High Performance1996Conference paper (Refereed)
  • 97. Ji, W.
    et al.
    Liu, X.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Wang, G.
    Research on modelling of ball-nosed end mill with chamfered cutting edge for 5-axis grinding2016In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 87, no 9-12Article in journal (Refereed)
    Abstract [en]

    This paper presents models related to the manufacturing of ball-nosed end mills of solid carbide (BEMSC) with a chamfered cutting edge (CCE). A parallel grinding wheel (PGW) is selected, and the relationship between CCE face and PGW working face is determined. Based on the geometry models of BEMSC established in our previous work, the centre and axis vectors of PGW are calculated for the grinding of CCE face on bath the ball-nosed end and the cylinder, which is validated through a numerical simulation. In order to produce the tool, a grinding machine, SAACKE UMIF, is chosen. Targeting the grinding data of BEMSC, the transformations are carried out between the coordinate systems of workpiece and the NC programme according to the structural features of the machine. An algorithm is derived for dispersing grinding paths. As a result, the centre data and axis vector are generated with respect to the grinding machine. The BEMSC with CCE is machined using the selected machine, which demonstrates the correctness of the established models. Finally, the performance of the machined cutting tool is validated in comparison with a common BEMSC without CCE in the milling of a mould of a multi-hardness joint structure.

  • 98.
    Ji, Wei
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Li, Y.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    A task-oriented cyber-physical system in manufacturing2018In: Proceedings of International Conference on Computers and Industrial Engineering, CIE, Curran Associates Inc. , 2018Conference paper (Refereed)
    Abstract [en]

    Towards automatic operations on a shop floor, this paper proposes a task-oriented cyber-physical system (CPS) concept, called holonic CPS. Within the context, operation processes are separated and modelled independently, and machines are also divided into hardware and basic controllers. The elementary distributed entities from operation processes and machines are represented by holons including “Cyber” and “Physical” parts. A holon is designed in hierarchical structure involving agent, FB, controller and hardware from top to bottom, and a holarchy, a holonic network including relevant holons, is able to represent a task or a function on the shop floor. To show how the proposed holonic CPS works, a robotic application is designed, in which both assembly tasks and machining (grinding and polishing) tasks can be performed. Where a set of relevant holons and holarchies are presented, which provide a “library” as the basis to represent an ordered task. A microkernel architecture is designed to implement the holonic CPS. A major benefit under the holonic CPS allows the partial manufacturing operation to be transferred into computing issues.

  • 99.
    Ji, Wei
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering. Harbin University of Science and Technology, China.
    Liu, X.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering, Production Systems. Harbin University of Science and Technology, Harbin, China.
    Meng, Y.
    Wu, X.
    A study on geometry modelling of a ball-end mill with chamfered cutting edge2015In: Journal of Manufacturing Processes, ISSN 1526-6125, Vol. 19, p. 205-211, article id 279Article in journal (Refereed)
    Abstract [en]

    This paper presents a geometry modelling approach to cross-section parameters of chamfered cutting edge on a ball-end mill of solid carbide (BEMSC). Both the cutting edge curve and the CR (chamfer in rake face) face models are derived. Based on the CR face model, a new method for CR face grinding path generation is proposed. By determining the relationship between the length and the angle parameters of the CR face equation, its grinding path can be derived. After solving the rake face equation using this method, its grinding path as well as the grinding paths of the LF (land on flank face) face and the second flank face can also be computed. The geometry model has been validated through a series of numerical simulations.

  • 100. Ji, Wei
    et al.
    Liu, X.
    Wang, Lihui
    KTH, School of Industrial Engineering and Management (ITM), Production Engineering.
    Meng, Y.
    Wu, X.
    A study on geometry modelling of ball-end mill with chamfered cutting edge2014In: Transactions of the North American Manufacturing Research Institution of SME, Society of Manufacturing Engineers , 2014, no January, p. 317-324Conference paper (Refereed)
    Abstract [en]

    This paper presents a geometry modelling approach to cross-section parameters of chamfered cutting edge on a ball-end mill of solid carbide (BEMSC). Both the cutting edge curve and the CR (chamfer in rake face) face models are derived. Based on the CR face model, a new method for CR face grinding path generation is proposed. By determining the relationship between the length and the angle parameters of the CR face equation, its grinding path can be derived. After solving the rake face equation using this method, its grinding path as well as the grinding paths of the LF (land on flank face) face and the second flank face can also be computed. The geometry model has been validated through a series of numerical simulations.

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