The integration of collaborative robots (cobots) into assembly systems has transformed manufacturing by enabling flexible, adaptive, and human-centered production environments. However, designing and managing human–robot collaborative assembly lines remain a complex task, as multiple objectives must be balanced simultaneously. This paper addresses three interrelated dimensions: time efficiency, safety, and energy consumption. Time remains a critical drive of productivity, where synchronization of human and robot tasks directly influences cycle time and throughput. Safety is essential due to the shared workspace in which task allocation, interaction mode, and robot end effector and speed can either mitigate or intensify physical and mental risks to workers. Although cobots are typically more energy-efficient than traditional industrial robots, their cumulative energy use becomes significant at scale, particularly when deployed across multiple stations or operating continuously. Moreover, energy consumption is not independent: shorter cycle times often require higher accelerations and power demands, while slower, safety-oriented operations may reduce energy use but extend production duration. These interdependencies highlight the importance of considering energy not as a marginal factor, but as part of a broader trade-off with time and safety. Building on this perspective, a mathematical model is developed to integrate these objectives into a unified framework for human–robot collaborative assembly. The contribution lies in advancing beyond single-objective optimization to capture the inherent trade-offs, offering insights that are aligned with emerging sustainability and safety standards. This approach provides a basis for future empirical validation and supports the development of resilient and sustainable human–robot collaborative systems.