40,894 research outputs found

    Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

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    The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system

    Why and How Your Traceability Should Evolve: Insights from an Automotive Supplier

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    Traceability is a key enabler of various activities in automotive software and systems engineering and required by several standards. However, most existing traceability management approaches do not consider that traceability is situated in constantly changing development contexts involving multiple stakeholders. Together with an automotive supplier, we analyzed how technology, business, and organizational factors raise the need for flexible traceability. We present how traceability can be evolved in the development lifecycle, from early elicitation of traceability needs to the implementation of mature traceability strategies. Moreover, we shed light on how traceability can be managed flexibly within an agile team and more formally when crossing team borders and organizational borders. Based on these insights, we present requirements for flexible tool solutions, supporting varying levels of data quality, change propagation, versioning, and organizational traceability.Comment: 9 pages, 3 figures, accepted in IEEE Softwar

    Performance analysis and optimization of automotive GPUs

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    © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) have drastically increased the performance demands of automotive systems. Suitable highperformance platforms building upon Graphic Processing Units (GPUs) have been developed to respond to this demand, being NVIDIA Jetson TX2 a relevant representative. However, whether high-performance GPU configurations are appropriate for automotive setups remains as an open question. This paper aims at providing light on this question by modelling an automotive GPU (Jetson TX2), analyzing its microarchitectural parameters against relevant benchmarks, and identifying specific configurations able to meaningfully increase performance within similar cost envelopes, or to decrease costs preserving original performance levels. Overall, our analysis opens the door to the optimization of automotive GPUs for further system efficiency.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (MINECO) under grant TIN2015-65316-P, the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 772773) and the HiPEAC Network of Excellence. Pedro Benedicte and Jaume Abella have been partially supported by the MINECO under FPU15/01394 grant and Ramon y Cajal postdoctoral fellowship number RYC-2013-14717 respectively and Leonidas Kosmidis under Juan de la Cierva-Formacin postdoctoral fellowship (FJCI-2017-34095).Peer ReviewedPostprint (author's final draft

    Do not forget the strategic architecture of your manufacturing network while offshoring

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    Offshoring manufacturing to low labor cost countries has become trendy. Nearly everyday one sees an announcement in the business press of companies moving to China or India. Whilst production cost is an important consideration in choosing a location for the factory, we argue that one should not become victim of a herd effect and that other parameters e.g. quality, flexibility, transportation and energy costs, etc. need to be taken into consideration in the determination of the optimal manufacturing network. Relocating a factory is changing the strategic architecture of the company's manufacturing network and requires a long term view and a good model to design the architecture of the manufacturing network. Based on empirical survey research and a set of case studies we provide such a model to think about the roles of factories in the strategic manufacturing network of the firm. But we go beyond a classification and a descriptive model and we provide a set of six managerial issues that require senior management's attention in determining the optimal manufacturing network and its dynamic evolution. We argue for example that senior management needs to build a balanced portfolio of different types of factories, has to have a performance measurement system adapted to the type of factory, as well as the appropriate leadership for each of the different types of factories and needs to actively manage the dynamics and the flows of innovation in the factory network. Key words: international manufacturing, network management, outsourcin
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