time series with binary data

Hello NG,

I am reflecting the following problem:

Given a set of machines. These machines are assessed each day (say for
90 days) as working (= 1) or not (=0).
Hence I get series of length 90 consisting of 0s and 1s.

For these series I want to calculate a kind of index with the following
properties:

a machine that works every day gets the index 1,
a machine that never works gets the index 0.

(These are the easiest cases).

Furthermore, a machine that works every second day is much better than
a machine that works for 45 days correctly and for the other 45 days
not at all.
Furthermore I want to specify (in advance) a "critical value" for the
longest period of "non-working" that is accceptable (say four days). A
machine that exceeds this number is bad. But not as bad as a machine
that only every third day...

Has anybody any idea?

Thanks in advance

Uli.

.

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