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Lars Hvam - One of the best experts on this subject based on the ideXlab platform.

  • the documentation of product Configuration Systems
    Advanced Engineering Informatics, 2017
    Co-Authors: Sara Shafiee, Lars Hvam, Anders Haug, Michael Dam, K. Kristjansdottir
    Abstract:

    The process of generating documentation from the PCS based on the available knowledge inside PCS.Display Omitted Lack of documentation degrades the quality of product Configuration Systems.To improve the documentation process, a framework is developed.An IT documentation System based on the Configuration System knowledge is developed.The results indicate improved quality and performance of the Configuration Systems. When designing and maintaining a product Configuration System (PCS), complete and up-to-date documentation of the System is needed in the form of a product model that outlines the structures, attributes, and constraints of the PCS. Furthermore, up-to-date documentation for the PCS is crucial for maintenance, further development, System quality and communication with domain experts. Product models are the main communication and documentation tools used in PCS projects. Recent studies have shown that up-to-date documentation for the PCS is often lacking due to the significant amount of work required to maintain product models. To address these challenges, this paper proposes an approach for documenting the PCS that is based on the structure, attributes, and constraints modelled within the PCS, in which the product model is generated directly from the PCS. The suggested approach avoids knowledge duplication, as knowledge needs to be maintained within the PCS only. It involves two steps: the first is the building of the initial product model, which is used for the programming of the PCS. In the second step, the product model is generated directly from the PCS and is based on the structure, attributes, and constraints inside the PCS. The product model does not need to be maintained, therefore, outside the PCS. This approach meets the demand for agile documentation and efficient communication with domain experts, and uses the fewest resources possible. Furthermore, to support the framework, an IT documentation System is proposed that is capable of retrieving knowledge from the PCS and thus generating the product model. Our framework and IT documentation System were developed and tested at a case company on five different projects. The results confirm that benefits can be achieved by using the proposed IT documentation System, as time and resources are saved, while the quality of the PCS is improved.

  • Product Configuration System and its impact on product's life cycle complexity
    2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), 2016
    Co-Authors: Anna Myrodia, K. Kristjansdottir, Sara Shafiee, Lars Hvam
    Abstract:

    The purpose of this paper is to identify areas throughout a product's lifecycle processes where complexity can be reduced by implementing a product Configuration System (PCS). As discussed in the literature, several benefits are realized by using a PCS in terms of product and process standardization. This also leads to control and reduce of complexity both in products and processes. To this end, this research attempts to quantify and assess these benefits and is supported by empirical evidence. A case study of an engineering company is used and the results indicate significant improvements for the company in several life cycle processes.

  • formal computer aided product family architecture design for mass customization
    Computers in Industry, 2015
    Co-Authors: Martin Bonev, Lars Hvam, John Clarkson, Anja Maier
    Abstract:

    Conventional methods for product family architecture design are informal and limit the support for architecture communication, synthesis and documentation.A formal computational approach requires the integration to Configuration Systems, improved generic models and extended structural analysis methods.Product family architectures can be modelled interchangeably with generic design-structure matrixes, generic node-link diagrams and product variant masters.Supportive tools automate the documentation and formalize the synthesis of architectures, thereby making any decision about a preferred solution explicit and transparent. With product customization companies aim at creating higher customer value and stronger economic benefits. The profitability of the offered variety relies on the quality of the developed product family architectures and their consistent implementation in Configuration Systems. Yet existing methods are informal, providing limited support for domain experts to communicate, synthesize and document architectures effectively. In single product design explicit visual models such as design structure matrices and node-link diagrams have been used in combination with structural analysis methods to overcome the limitation of the informal approach. Drawing on thereto established best practises, this paper evaluates and extends the relevant methods and modelling techniques, to create a consistent and formal approach for the design and customization of entire product families. To validate it's applicability, the approach is tested on a case study at a manufacturing company offering bespoke industrial applications. A generic modelling method termed the integrated design model (IDM) is developed and complemented with a computational structural analysis method, to assist domain experts in their daily work. When combined with a Configuration System, the presented IDM tool automates the documentation and formalizes the synthesis of architectures, thereby making any decision about a preferred solution explicit and transparent.

  • alignment of Configuration and documentation for highly engineered complex product Configuration Systems a demonstration from a case study
    Web Intelligence, 2015
    Co-Authors: Sara Shafiee, Katrin Kristjansdottir, Lars Hvam
    Abstract:

    Adequate documentation is critical for successful implementation, maintenance and further developments of product Configuration System (PCS) specially in companies making complex and highly engineered products. This article is based on experience of modelling and utilizing a PCS from an Engineer-To-Order (ETO), where the main focus is on the challenges concerned with the documentation of the PCS, both in the development and production phase. Aligning the development of the PCS with an automatic documentation System creates value. Using the suggested method for documentation facilitates the following activities: (1) iterative testing of the System during the development, (2) communication with domain experts, (3) documentation and maintenance, and finally (4) updates without spending a lot of time and resources. This article is supplemented with a case study from an ETO company where the method for the automatic documentation was developed and tested.

  • creating a documentation System to support the development and maintenance of product Configuration Systems
    International Conference on Computer Engineering and Applications, 2007
    Co-Authors: Anders Haug, Anders Degn, Bjarne Poulsen, Lars Hvam
    Abstract:

    A product Configuration System (PCS) can be defined as a product-oriented expert System that allows users to specify a product while restricting how different elements and properties may be combined. The use of Configuration technology has in several cases led to improvements of product specification processes, such as shorter lead times, reductions of resources needed, and fewer errors. A procedure for building product Configuration Systems from the Centre for Product Modelling at the Technical University of Denmark has been applied in projects for more than ten years. The CPM-procedure includes three main modelling techniques to support the development and maintenance of PCSs. However, no software, which supports all three techniques in an integrated fashion, currently exists. This means that when developing PCSs based on the CPM-procedure there is no automatic integration between the created models, wherefore some information has to be transferred between models manually. CPM has, therefore, for some years worked on creating a basis for developing a documentation System that supports the development and maintenance of PCSs. Research focusing on the requirements for a documentation System has been produced, and more recently detailed definitions of the included modelling techniques have emerged. This paper describes how these definitions have been converted into a software prototype and what have been learned from the evaluation of the prototype.

Wenfei Wu - One of the best experts on this subject based on the ideXlab platform.

  • Generic and automatic address Configuration for data center networks
    Computer Communication Review, 2010
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Songwu Lu, Haitao Wu, Yan Chen, Wenfei Wu
    Abstract:

    Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint which defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem, and solves it with low time-complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change. We have evaluated DAC via simulation, implementation and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 seconds. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 milliseconds and show that DAC is a viable solution for data center autoConfiguration. ? 2010 ACM.

Kai Chen - One of the best experts on this subject based on the ideXlab platform.

  • NUDT, UCLA,
    2013
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Yan Chen
    Abstract:

    Abstract—Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint which defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem, and solves it with low time-complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change. We have evaluated DAC via simulation, implementation and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 seconds. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 milliseconds and show that DAC is a viable solution for data center autoConfiguration. Index Terms—Data center networks, Address Configuration, Graph isomorphis

  • dac generic and automatic address Configuration for data center networks
    IEEE ACM Transactions on Networking, 2012
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Yan Chen
    Abstract:

    Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require a huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint that defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then, at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem and solves it with low time complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change.We have evaluated DAC via simulation, implementation, and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 s. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 ms and show that DAC is a viable solution for data center autoConfiguration.

  • Generic and automatic address Configuration for data center networks
    Computer Communication Review, 2010
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Songwu Lu, Haitao Wu, Yan Chen, Wenfei Wu
    Abstract:

    Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint which defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem, and solves it with low time-complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change. We have evaluated DAC via simulation, implementation and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 seconds. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 milliseconds and show that DAC is a viable solution for data center autoConfiguration. ? 2010 ACM.

Yan Chen - One of the best experts on this subject based on the ideXlab platform.

  • NUDT, UCLA,
    2013
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Yan Chen
    Abstract:

    Abstract—Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint which defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem, and solves it with low time-complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change. We have evaluated DAC via simulation, implementation and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 seconds. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 milliseconds and show that DAC is a viable solution for data center autoConfiguration. Index Terms—Data center networks, Address Configuration, Graph isomorphis

  • dac generic and automatic address Configuration for data center networks
    IEEE ACM Transactions on Networking, 2012
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Yan Chen
    Abstract:

    Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require a huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint that defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then, at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem and solves it with low time complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change.We have evaluated DAC via simulation, implementation, and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 s. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 ms and show that DAC is a viable solution for data center autoConfiguration.

  • Generic and automatic address Configuration for data center networks
    Computer Communication Review, 2010
    Co-Authors: Kai Chen, Zhenqian Feng, Chuanxiong Guo, Jing Yuan, Songwu Lu, Haitao Wu, Yan Chen, Wenfei Wu
    Abstract:

    Data center networks encode locality and topology information into their server and switch addresses for performance and routing purposes. For this reason, the traditional address Configuration protocols such as DHCP require huge amount of manual input, leaving them error-prone. In this paper, we present DAC, a generic and automatic Data center Address Configuration System. With an automatically generated blueprint which defines the connections of servers and switches labeled by logical IDs, e.g., IP addresses, DAC first learns the physical topology labeled by device IDs, e.g., MAC addresses. Then at the core of DAC is its device-to-logical ID mapping and malfunction detection. DAC makes an innovation in abstracting the device-to-logical ID mapping to the graph isomorphism problem, and solves it with low time-complexity by leveraging the attributes of data center network topologies. Its malfunction detection scheme detects errors such as device and link failures and miswirings, including the most difficult case where miswirings do not cause any node degree change. We have evaluated DAC via simulation, implementation and experiments. Our simulation results show that DAC can accurately find all the hardest-to-detect malfunctions and can autoconfigure a large data center with 3.8 million devices in 46 seconds. In our implementation, we successfully autoconfigure a small 64-server BCube network within 300 milliseconds and show that DAC is a viable solution for data center autoConfiguration. ? 2010 ACM.

Anna Wangmathieson - One of the best experts on this subject based on the ideXlab platform.

  • magnetic resonance imaging guided neurosurgery in the magnetic fringe fields the next step in neuronavigation
    Neurosurgery, 2000
    Co-Authors: Gregory Rubino, Keyvan Farahani, David Mcgill, Barbara Van De Wiele, Pablo J Villablanca, Anna Wangmathieson
    Abstract:

    OBJECTIVE: We describe the development of an alternative approach to intraoperative magnetic resonance imaging (iMR)-guided neurosurgery and report our initial experience with 22 craniotomies and 16 brain biopsies. The advantages and disadvantages of each approach are examined. METHODS: An iMR suite houses a 0.2-T open Configuration System (Siemens Medical Systems, Erlangen, Germany) and is equipped with anesthetic gases and a magnetic resonance imaging (MRI)-compatible anesthesia machine and monitor. Standard operating instruments and equipment were tested for safety and compatibility in the magnetic fringe fields surrounding the open MRI System. We then performed brain biopsies and craniotomies in the iMR suite. RESULTS: Standard operating equipment functioned properly in the 0.5- to 10-mT zone and was not affected by the magnet's attractive force. Twenty-two craniotomies and 16 brain biopsies were performed in the interventional suite, using serial intraoperative MRI guidance, without injury to patients or operating room staff. CONCLUSION: Full neurosurgical procedures may be performed in the weak fringe fields surrounding an MRI System, using standard operating room equipment. This approach to iMR-guided neurosurgery offers a significant cost advantage over retrofitting an entire operative suite with "MRI-compatible" surgical equipment. The surgeon's familiarity with standard equipment and the reliability of the equipment are additional advantages. Neurosurgery in the fringe fields allows the neurosurgeon to utilize serial MRI with a minimum of inconvenience, disruption, and change to the standard neurosurgical procedure. Serial intraoperative imaging to visualize the changes in the brain that are associated with neurosurgical intervention seems to enhance the ability to safely and effectively accomplish neurosurgical goals.