In our illustration, the business problem could be defined as the need to understand the probability of a machine being operational across its lifespan. Did all the machines fail at some point in the period of evaluation? No. The data spans 20 years and we have 55% of the instances when the machines haven't stopped functioning in the given time span. So how can we find the survival rate or hazard rate of machines when they haven't stopped functioning? Well, we could use the data of the machines that did stop functioning. We could maybe look at the common characteristics (such as the manufacturer, functional area the machine has been deployed for, the location of the plant where it has been installed, servicing history, and so on) of the failed and the functioning machines and extrapolate the knowledge gained from analyzing failed machines...
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