  The need to monitor industrial processes, detecting changes in process
parameters in order to promptly correct problems that may arise, generates a
particular area of interest. This is particularly critical and complex when the
measured value falls below the sensitivity limits of the measuring system or
below detection limits, causing much of their observations are incomplete. Such
observations to be called incomplete observations or left censored data. With a
high level of censorship, for example greater than 70%, the application of
traditional methods for monitoring processes is not appropriate. It is required
to use appropriate data analysis statistical techniques, to assess the actual
state of the process at any time. This paper proposes a way to estimate process
parameters in such cases and presents the corresponding control chart, from an
algorithm that is also presented.
