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Industrie 4.0 Readiness: Green Computing in Relation with Key Performance Indicator for a Manufacturing Industry

机译:Industrie 4.0准备:与制造业关键绩效指标相关的绿色计算

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An effective measure of Key Performance Indicators (KPIs) is of great significance to enhance the capabilities of a decision support system (DSS) of any enterprise. Only a properly planned systematic analysis can provide the DSS with enough information in order to reap the associated benefits. This study aims to provide such an information-set on continuous basis for a tile manufacturing industry of medium-size. A discrete-event simulation-based approach is employed in order to continuously analyze the process parameters in real time. A signal-based notification system is used for dynamic mapping of the process parameters to the defined KPIs in order to tweak the overall system performance. A comparative analysis of the existing process with proposed strategy reveals that there is an increase in the daily production rate that consequently reduced the per unit cost significantly without incurring any considerable capital cost. Apart from the present form, the proposed approach is quite useful by carefully extending it to a generalized form for various industries of similar nature. This would not only help the practitioners in the industry to boost the productivity but also the researchers can employ the approach to design, simulate and devise solutions of customized nature for a wide-set of industries.
机译:有效衡量关键绩效指标(KPI)的衡量标准(KPI)具有重要意义,以提高任何企业的决策支持系统(DSS)的能力。只有一个适当计划的系统分析可以提供具有足够信息的DSS,以便获得相关的好处。本研究旨在以持续的基础提供中等大小的瓷砖制造业的信息集。采用离散事件仿真的方法,以便实时地连续分析过程参数。基于信号的通知系统用于将过程参数的动态映射到定义的KPI,以调整整体系统性能。对现有流程的比较分析,拟议策略揭示了日常生产率的增加,从而显着降低了每单位成本,而不会产生任何相当大的资本成本。除了目前的形式之外,所提出的方法非常有用,可以仔细地将其延伸到各种行业的广义形式。这不仅可以帮助行业中的从业者提高生产力,而且研究人员也可以采用这些方法,为广泛的行业设计,模拟和设计定制的自定义解决方案。

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