Biosimilar development of monoclonal antibodies (mAbs) is gaining significant momentum as numerous blockbuster biologics approach their patent expiry in the current decade. A critical challenge in biosimilar development lies in achieving product quality attributes comparable to the innovator product. The product quality attributes (PQAs) in upstream processing are influenced by multiple factors, including cell line selection, media composition, feed strategy, supplements, and bioreactor process parameters, with physical parameter optimization playing a pivotal role in enhancing both product titer and modulating PQAs. In this study, we systematically evaluated the impact of physical process parameters - pH, temperature, and initial seeding density - on N-glycan profiles and charge variants across four biosimilar development projects (Projects 1-4). Prediction models were developed using JMP software to establish parameter-attribute relationships. Our results demonstrated that lowering bioreactor pH reduced % acidic variants and % Afucosylation (AF) while increasing % basic variants and % galactosylation. Similarly, decreased culture temperature resulted in lower % acidic variants and increases % AF. This knowledge base was successfully applied to expedite the development of a fifth mAb biosimilar development (Project 5), substantially reducing experimental iterations and development timelines, exemplifying the practical implementation of Bioprocessing 4.0 principles.