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Industrial Image Processing Applications as Orchestration of Web Services

机译:工业图像处理应用程序作为编排的Web服务

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Contemporary production lines often make extensive use of image recognition to achieve high levels of automation. Shorter product life cycles and smaller lot sizes force companies to adapt their processes very quickly. Still, industrial image processing algorithms typically run on dedicated computer systems next to the cameras, which is rather inflexible and leads to high costs for hardware and maintenance. In this paper, we propose a service-based architecture to tackle these problems. We divide image processing applications into universal building blocks, each of which is implemented as web service. The recognition application is conceived as a composition of these services, orchestrated using the Business Process Execution Language (BPEL). The composed application is provided with a standard industrial interface (OPC UA) for easy integration into the production process. This concept is evaluated by assessing proof-of-concept implementations. Main advantages (among others) are the flexible reuse of existing image processing operations and applications, and the freedom to implement services independently using the preferred language, framework and platform. Challenges are real-time constraints, which can be alleviated by emerging technologies like Time Sensitive Networking (TSN).
机译:当代生产线往往广泛利用图像识别以实现高度自动化。更短的产品寿命周期和较小的批量强制公司,以非常快速地调整他们的流程。尽管如此,工业图像处理算法通常在相机旁边的专用计算机系统上运行,这相当不灵活,并导致硬件和维护的高成本。在本文中,我们提出了一种基于服务的架构来解决这些问题。我们将图像处理应用程序划分为通用构建块,每个块都以Web服务实现。识别申请被认为是使用业务流程执行语言(BPEL)策划的这些服务的组成。组成的应用程序提供标准工业接口(OPC UA),便于集成到生产过程中。通过评估概念证明实现来评估该概念。主要优点(其中)是现有图像处理操作和应用的灵活重用,以及使用首选语言,框架和平台独立实施服务的自由度。挑战是实时限制,可以通过新兴技术等待时敏感网络(TSN)。

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