Software reliability is assessed quantitatively by using Software Reliability Growth Model (SRGM) for tracking and measuring the growth of reliability. Reliability of software is the probability of failure-free operation during specified period in specified environment. To improve reliability and quality the execution of software process must be controlled and the accepted choice for monitoring software process is Statistical Process Control (SPC). This helps the professionals to identify anomalies while monitoring the process and take the necessary action. In this paper we present Non Homogeneous Poisson Process (NHPP) based Burr type III software reliability growth model with time domain data. The Maximum Likelihood (ML) estimation method is used for finding unknown parameters in the model on ungrouped data. Applicability of SPC for monitoring software reliability process is given.