A predictive schedule model for satellite subsystem hardware delivery in an earned value environment

Category 2 NASA satellite missions involve design, fabrication, assembly, test and integration of numerous complex systems, subsystems, and instruments and require a large team of scientists and engineers. JHU/APL engineers often leverage proven design and technology solutions; however, since JHU/APL fosters a culture of continuous improvement, the design solutions rarely replicate themselves. In this unique environment, the team is constantly challenged with maintaining schedule while managing a plethora of risks for designs that have limited heritage and little relevant historical schedule data. In particular, hardware development is subject to risk factors that are difficult to predict during the planning phases of a program based on current approaches to estimating activity durations. If we can understand and quantify the variation in as-built activity durations for hardware development at the activity level, we may be able to correlate schedule durations with physical hardware characteristics to produce a model that more accurately predicts hardware development timeframes for future programs. A detailed analysis of data was performed at or below the activity level using the project Production Schedule (PS) and the JHU/APL Business Process Management (BPM) system to identify physical characteristics that may be correlated with activity durations. If statistically significant relationships exist between these factors, we can build a model to more accurately predict hardware development durations for future programs and establish an objective baseline to measure earned value performance.