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An Analysis and Design of Mobile Business Intelligence System for Productivity Measurement and Evaluation in Tire Curing Production Line

机译:轮胎硫化生产线生产效率评估的移动商务智能系统分析与设计

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Business intelligence (BI) system as an architecture of competencies, processes, technologies, applications and practices to support productivity measurement. It obviously needs a BI that support organization to declare any production constraints that currently or already occurred in such as tire curing industry. Overall Equipment Effectiveness (OEE) is used as a quantitative productivity measurement and become the base of company continuous improvement and evaluation. The objectives of this study are to identify critical parameters of production line in effectiveness measurement and machine utilization, analyze the requirement of information system as an Android based mobile BI System and to integrate the design into a mobile system. System requirement analyzed each interdependent measure in the real world of complexity by using BPMN 2.0. These measures are part of dashboard components in the proposed BI. The acquired data from a National forefront tire industry shows the OEE in three ratio measurement of availability, performance, and quality with 78%, 82.5% and 99.8% of scorecard respectively. In order to determine the status of production, the deployment of k-nearest neighbour (k-NN) gives 67.5% of accuracy rate. The critical parameters identification results to 8 (eight) significant constraints, which calculated using distance-based RELIEF attribute selection. Eventually this approach results big four constraints to be noted: (a) mold repair, (b) mold setting, (c) green tire shortage and (d) defect cure.
机译:商业智能(BI)系统是一种能力,流程,技术,应用程序和实践的体系结构,可支持生产力测量。显然,它需要一个BI支持组织来声明轮胎硫化行业中当前或已经发生的任何生产限制。总体设备效率(OEE)用作定量生产率衡量指标,并成为公司持续改进和评估的基础。这项研究的目的是确定生产线在有效性测量和机器利用率方面的关键参数,分析信息系统作为基于Android的移动BI系统的需求,并将设计集成到移动系统中。系统需求通过使用BPMN 2.0分析了现实世界中每个相互依赖的度量。这些措施是建议的BI中的仪表板组件的一部分。从美国前列轮胎行业获得的数据显示,OEE在可用性,性能和质量的三个比率度量中分别占到了记分卡的78%,82.5%和99.8%。为了确定生产状态,k最近邻(k-NN)的部署给出了67.5%的准确率。关键参数识别导致8(八个)重要约束,这些约束使用基于距离的RELIEF属性选择计算得出。最终,这种方法导致需要注意的四大限制:(a)模具修复,(b)模具设置,(c)轮胎生胎不足和(d)缺陷修复。

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