面向工业4.0工作流自动化资源的结构化性能分析

A. Kattepur
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引用次数: 5

摘要

自动化和在业务流程中使用机器人组件在零售和制造业中非常流行。然而,分析复杂工作流中自动化所提供的性能改进的结构化方法仍处于初级阶段。在本文中,我们考虑了常见的工业4.0自动化工作流资源模式,并在混合排队网络中对它们进行了建模。排队站被向上扩展、向外扩展和混合扩展自动化模式所取代,以检查端到端流程性能的改进。我们使用均值分析(Mean Value Analysis, MVA)算法详尽地模拟了更高并发下的吞吐量、响应时间、利用率和操作成本。针对具有多个类、批处理/事务处理和负载相关服务需求的情况,对队列进行分析。这些解决方案通过工业4.0仓库自动化工作流中的自动化示例用例进行了演示。自动化工作流性能分析的结构化过程将在整个工业部署中证明是有价值的。
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Towards Structured Performance Analysis of Industry 4.0 Workflow Automation Resources
Automation and the use of robotic components within business processes is in vogue across retail and manufacturing industries. However, a structured way of analyzing performance improvements provided by automation in complex workflows is still at a nascent stage. In this paper, we consider the common Industry 4.0 automation workflow resource patterns and model them within a hybrid queuing network. The queuing stations are replaced by scale up, scale out and hybrid scale automation patterns, to examine improvements in end-to-end process performance. We exhaustively simulate the throughput, response time, utilization and operating costs at higher concurrencies using Mean Value Analysis (MVA) algorithms. The queues are analyzed for cases with multiple classes, batch/transactional processing and load dependent service demands. These solutions are demonstrated over an exemplar use case of automation in Industry 4.0 warehouse automation workflows. A structured process of automation workflow performance analysis will prove valuable across industrial deployments.
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