The production ramp-up phase is a crucial step in modern manufacturing, involving the shift from prototype to full-scale production. It poses growing challenges for organizations as they face shorter product lifecycles and increasing complexity in achieving efficient operations. Within this context, understanding the relationship between complexity and cost management becomes crucial, particularly as manufacturing evolves towards the human-centric paradigm. We present an optimization model that integrates setup costs, inventory holding, and workforce dynamics, incorporating a three-parameter exponential learning model, the logistic demand growth curve, and complexity adjustments. Through the development and implementation of the model, our research reveals distinct patterns in complexity-cost relationships. The analysis shows that, while learning effects can briefly mitigate complexity impacts, long-term costs are primarily driven by complexity. This underscores the importance of prioritizing complexity reduction over additional learning investments in complex operations, offering key insights for effective production ramp-up management.