Have you ever been asked a question starting with: “Can you use R to…“, only to politely interrupt the inquisitor at this point to reply with something similar to “Yes, you can! R probably already has a package for this”.
If this sounds familiar to you, you won’t be overly surprised to hear that R is now making advancements in the field of industrial production processes of the 21st century – respectively to the technological planning of production and maintenance processes.
The catchword in this context is Predictive Maintenance which represents the informatization of production processes away from only reactive repair mechanisms towards the realization of IT-based Smart Factories.
In industrial production, unforeseeable machine failures as well as performance drops or deterioration in quality because of defective system components can lead to severe shortness’ of supplies. In order to prevent this and to be able to survive in the global economy, organizations are increasingly focusing on the improvement, maintenance, and repair of their machinery.
What they need to successfully predict when a machine failure is likely to happen, or how to choose the best possible time to replace a wearing part of a critical production plant without causing a production stop or having to accept other cost disadvantages, is the implementation of a powerful analysis software. This is where R comes into play to put the innovative concept of Predictive Maintenance into practice to realize the hitherto unimaginable potential of a data analysis software for the optimization of industrial maintenance models and thereby changing the way organizations go about their process of machine maintenance.
As one of the best alternatives for e.g. the analysis and visualization of data and many benefits for Data Mining and Predictive Analytics, R can be tailored to the specific requirements of the condition monitoring and diagnostic technologies an organization might need. Weiterlesen