从AutomationML到AutomationQL: CPPS工程模型的实例查询语言

M. Wimmer, Alexandra Mazak
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引用次数: 10

摘要

基于模型的工程是一种新兴的处理CPPS项目中多学科工程复杂性的范式。在这样的项目中,在生产系统的生命周期中会创建不同类型的模型。Automa-tionML是一种很有前途的标准,它提供了一种统一的格式来表示和连接不同的工程模型。在过去的几年中,已经为AutomationML开发了专门的工具支持来创建和发展模型。然而,在查询AutomationML模型时,必须当前使用与实现相关的查询语言。这些语言具有一定的复杂性,因为它们不是直接基于AutomationML的概念,而是基于AutomationML的底层技术概念和编码。这通常会妨碍领域专家制定自动执行的查询。在本文中,我们为AutomationML提出了一种专用的查询语言,称为自动化查询语言(Au-tomationQL),它直接派生自AutomationML。使用这种查询语言,可以按例定义查询,这允许工程师根据AutomationML概念制定查询,而不是切换到面向实现的查询语言。我们将说明如何定义AutomationQL,如何制定查询,以及如何提供工具支持来自动评估查询并表示其结果。最后,我们将我们的解决方案与现有的查询语言进行了对比,并为AutomationQL的未来研究制定了路线图。
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From AutomationML to AutomationQL: A By-Example Query Language for CPPS Engineering Models
Model-based engineering is an emerging paradigm to deal with the complexity of multi-disciplinary engineering in CPPS projects. In such projects, different kinds of models are created during the lifecycle of a production system. Automa-tionML is a promising standard to provide a unifying format to represent and connect the different engineering models. Dedicated tool support has been developed for AutomationML in the last years to create and evolve models. However, when it comes to querying AutomationML models, implementation-related query languages have to be currently used. These languages have a certain complexity as they are not directly based on the concepts of AutomationML but on the underlying technological concepts and encodings of AutomationML. This often hinders the formulation of automatically executable queries by domain experts. In this paper, we propose a dedicated query language for AutomationML called Automation Query Language (Au-tomationQL) which is directly derived from AutomationML. Using this query language, queries can be defined in a by-example manner which allows engineers to formulate queries in terms of AutomationML concepts instead of switching to an implementation-oriented query language. We illustrate how AutomationQL is defined, how queries can be formulated as well as how tool support is provided to automatically evaluate the queries and represent their results. Finally, we contrast our solution with existing query languages and derive a roadmap for future research on AutomationQL.
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