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Predictive maintenance as an internet of things enabled business model: A taxonomy

机译:预测维护作为企业模式的东西互联网:分类

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摘要

Predictive maintenance (PdM) is an important application of the Internet of Things (IoT) discussed in many companies, especially in the manufacturing industry. PdM uses data, usually sensor data, to optimize maintenance activities. We develop a taxonomy to classify PdM business models that enables a comparison and analysis of such models. We use our taxonomy to classify the business models of 113 companies. Based on this classification, we identify six archetypes using cluster analysis and discuss the results. The "hardware development", "analytics provider", and "all-in-one" archetypes are the most frequently represented in the study sample. For cluster analysis, we use a visualization technique that involves an autoencoder. The results of our analysis will help practitioners assess their own business models and those of other companies. Business models can be better differentiated by considering the different levels of IoT architecture, which is also an important implication for further research.
机译:预测维护(PDM)是许多公司讨论的事物互联网(IOT)的重要应用,特别是在制造业。 PDM使用数据,通常传感器数据,优化维护活动。我们开发了分类学,以分类PDM业务模式,可以比较和分析此类模型。我们使用我们的分类法分类113家公司的商业模式。根据此分类,我们使用集群分析确定六个原型并讨论结果。 “硬件开发”,“分析提供商”和“一体化”原型是研究样本中最常表示的。对于群集分析,我们使用涉及AutoEncoder的可视化技术。我们的分析结果将帮助从业者评估自己的商业模式和其他公司的业务模式。通过考虑不同级别的物联网架构,商业模式可以更好地区分,这也是进一步研究的重要意义。

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