With the development of advanced manufacturing technologies, the manufacturing environment becomes complex, dynamic, and filled with human-machine collaboration. To improve manufacturing performance, the efficiency of collaboration is critical. Nudging, a concept in behavioral economics, is employed to indirectly encourage individuals to act or believe in a certain way through subtle interventions. In the manufacturing context, nudging aims to alter or influence operators’ behaviors to better work with technology during their interactions. Meanwhile, the research of manufacturing nudging design is to investigate the theoretical foundation of design for human behaviors. To solve this problem, this paper conducts system analysis for smart manufacturing nudging design and identifies four fundamental questions, including manufacturing nudge generation, nudging behavior modeling considering affective cognition, model parameter estimation, and nudging personalization optimization. The paper further proposes a conjoint prospect theory-based approach to nudging behavior modeling. Affective cognition modeling is also discussed for parameter shaping of the nudging behavior model. An example case of nudging for assembly inspection is presented to illustrate the proposed approach.