Predicting when component will fail having its parameters data
Looks to me like a sequence labeling problem, where the class is binary indicating whether the component is still working or failed. In this option you should build a training dataset which each cycle which looks like this:

No_of_runs    Para1    Para2    Para3    Para4    Para5    status
1              100      32        45      230       86       ok
2              101      34        65      234       90       ok
3              120      24        32      242       80       ok
4              105      45        40      213       75       ok
5              90       42        54      200       77       ok
...            ...      ...       ...     ...       ...
1234           ..       ..        ..      ..        ..       fail


The order of the instances matters. After training, the model can tell you the probability of failing for an instance given its sequence of runs.

Conditional Random Fields are a standard option for such problems.