In the context of preparing data for a machine learning model, feature engineering plays a pivotal role. Consider a scenario where you are working on a predictive maintenance project for manufacturing equipment. The dataset includes raw sensor readings, equipment IDs, timestamps, and maintenance records. The goal is to predict equipment failure before it occurs to minimize downtime. Given the complexity of the data and the critical nature of the predictions, how does feature engineering contribute to framing this machine learning problem? (Choose one correct option)