工业数据科学项目中基于能力的协作的需求驱动方法

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Marius Syberg, Nikolai West, Jörn Schwenken, Rebekka Adams, Jochen Deuse
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引用次数: 0

摘要

在线学习资源的不断数字化导致特定应用领域和学科的合作平台激增。与此同时,特别是制造企业需要获得和确保工业数据科学(IDS)领域的知识,并与合作伙伴合作形成具有竞争力的价值链。本文将应用工业数据分析的协作和基于能力的要求调整为实施协作平台的规范。本文定义了 IDS 项目目前不存在的要求,并将其转化为平台的特定功能。在一个正在进行的研究项目中,这些功能被应用于一个在线平台。在动态价值网络系统中的使用验证了在实际环境中定义的要求。该平台的创新之处在于明确关注 IDS 项目从业人员,他们通常由多个不同领域的人员组成。该平台可确保在工业环境中长期使用已部署的数据分析解决方案。已开发的协作平台第一版已上线,目前仍在验证中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A requirement-driven approach for competency-based collaboration in industrial data science projects
The ongoing digitization of online learning resources has led to a proliferation of collaboration platforms for specific areas of application and disciplines. Simultaneously, especially manufacturing companies need to gain and secure knowledge in the field of Industrial Data Science (IDS) and to collaborate with partners to form a competitive value chain. In this paper, collaborative and competency-based requirements for applying industrial data analytics are adapted into specifications for implementing a collaboration platform. The currently absent requirements of IDS projects are defined and then turned into platform-specific functions. In an ongoing research project the functions are applied in an online platform. The usage in a system of dynamic value networks validates the defined requirements in a practical environment. The innovation of the platform is its clear focus on IDS project practitioners, who are typically comprised of several different domains. It secures a long-term use of deployed data analytics solutions in the industrial environment. The first version of the developed collaboration platform is available online and still in validation.
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来源期刊
CiteScore
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
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