System Dynamics (SD)-based simulation has gained traction in recent times as a technique to study a system's behavior. It has been employed to model diverse complexes, from reactive chemical assemblages to socio-economic systems. However, SD-based simulation models, like models derived from competing simulation techniques, typically suffer the problem of replicability. There are several sources of variation that could afflict any replication attempt such as software idiosyncrasies, floating point errors, and missing data. Adapting to these often intractable limitations will afford the SD-based technique the ability to be used to model problems of higher complexity, which is what this study seeks to do by suggesting an adaptation protocol. This protocol is tested via the replication of a holistic SD-based simulation model to deal with the eventual effects of the interventions in a quality system on a manufacturing organization's profitability. The study also identifies possible avenues for improvement of the protocol for a better fit to diverse SD-based models.