The integration of demand response and renewable energy into the operation of integrated energy systems (IES) introduces significant uncertainties and flexibility, increasing the complexity of system operation optimization. To improve the economic efficiency and reliability of IES with renewable energy, this paper investigates the robust operation of IES in industrial parks featuring integrated assembly manufacturing systems. First, the demand response characteristics of such manufacturing systems are thoroughly analyzed, and an optimization model for the industrial park IES is constructed with the objective of minimizing system operating costs. Second, to address the uncertainty of wind and photovoltaic power outputs, a robust bi-level operation model based on multi-objective information gap decision theory (MIGDT) is proposed. A bi-level solution algorithm is designed by combining the stochastic bisection method with the GUROBI solver. Finally, the effectiveness of the proposed model and uncertainty-handling algorithm is verified through case studies. A comparative analysis with deterministic optimization and stochastic optimization methods validate the effectiveness of the proposed model and approach.