A Differential Game-Based Approach for School-Enterprise Collaborative R&D Strategy on Digital Twin Technology

Digital twin (DT) technology is an effective way to realize intelligent manufacturing, which has been increasingly received attention in both academia and industry. Thus, it is rather necessary and significant to collaboratively accomplish the research and development (R&D) of DT technology (RDDT). To explore a school-enterprise collaborative R&D strategy on DT technology, this paper proposes a differential game-based approach to compute the optimal R&D effort levels and optimal incomes of both parties in the school-enterprise collaborative innovation (SECI) system. First, using Berman's continuous dynamic programming theory, the optimal R&D effort levels, the optimal incomes of both parties, and total optimal income in the SECI system are calculated in three cases: Nash non-cooperative game, Stackelberg master-slave game and cooperative game. Second, the equilibria of the three game cases are analyzed and compared. Finally, a numerical example is used to verify the validity of the conclusion, and we find that the optimal benefit of two parties in cooperative game are significantly better than those of Nash non-cooperative game and Stackelberg master-slave game, which effectively demonstrates the superiority of school-enterprise collaborative R&D on DT technology.