Frequent and Automatic Monitoring of Resource Data via the Internet of Things

Thomas Schmitt, Pavani Sakaray,Lars Hanson,Matias Urenda Moris, Kaveh Amouzgar

SPS 2022(2022)

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摘要
The Internet of Things (IoT) offers potential for developing an intelligent and sustainable manufacturing system, allowing for better and more informed decisions that increase efficiency and cut down waste in production processes. The insights are generated from automatically collected data coming from machines and devices. While process data are already reported and support a close to real-time monitoring and evaluation of process efficiencies, data about resource consumption in manufacturing environments is more scarce but crucial for becoming more resource efficient. Through connected hardware and software applications, data from resource consumption of energy, water, and waste can be automatically collected. To achieve this, this study presents an IoT framework for monitoring resource efficiency in an automatic and frequent manner. Thus, the eco-efficiency and productivity of the process can be measured and integrated into the decision-making processes by sharing the data with shop floor and production management personnel via dashboards.
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关键词
Data-driven,Eco-efficiency,Manufacturing,Internet of Things
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