The development of an ontology for describing the capabilities of manufacturing resources
The development of an ontology for describing the capabilities of manufacturing resources
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DOI：
10.1007/s10845-018-1427-6
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发表时间：
2019-02-01
影响因子：
8.3
通讯作者：
Lanz, Minna
中科院分区：
文献类型：
--
作者：
Jaervenpaeae, Eeva;Siltala, Niko;Lanz, Minna
当今高度多变的生产环境需要适应性强、反应迅速的生产系统，以适应加工功能、生产能力和订单调度方面的必要变化。人们希望用计算机辅助决策支持系统来支持这种系统的适应和重新配置。为了在多供应商资源环境中实现重新配置决策的自动化，需要一个通用的正式资源模型来表示资源的功能和约束。本文介绍了基于owl的制造资源能力本体（MaRCO）的系统开发过程，该本体用于描述制造资源的能力。与其他现有的资源描述模型相反，MaRCO支持从协作资源的简单能力的表示中对组合能力进行表示和自动推断。资源供应商可以利用MaRCO以类似的方式描述其产品的功能，而系统集成商和最终用户可以使用这些描述来快速识别候选资源和特定生产需求的资源组合。本文按照本体工程方法论的五个阶段：可行性研究、启动、细化、评估、使用和演进，介绍了本体的逐步开发过程。此外，它还提供了模型的内容和结构的细节。
Today's highly volatile production environments call for adaptive and rapidly responding production systems that can adjust to the required changes in processing functions, production capacity and dispatching of orders. There is a desire to support such system adaptation and reconfiguration with computer-aided decision support systems. In order to bring automation to reconfiguration decision making in a multi-vendor resource environment, a common formal resource model, representing the functionalities and constraints of the resources, is required. This paper presents the systematic development process of an OWL-based manufacturing resource capability ontology (MaRCO), which has been developed to describe the capabilities of manufacturing resources. As opposed to other existing resource description models, MaRCO supports the representation and automatic inference of combined capabilities from the representation of the simple capabilities of co-operating resources. Resource vendors may utilize MaRCO to describe the functionality of their offerings in a comparable manner, while the system integrators and end users may use these descriptions for the fast identification of candidate resources and resource combinations for a specific production need. This article presents the step-by-step development process of the ontology by following the five phases of the ontology engineering methodology: feasibility study, kickoff, refinement, evaluation, and usage and evolution. Furthermore, it provides details of the model's content and structure.