Effectively addressing the Order Acceptance and Production Planning (OAP) problem is crucial for industrial robot manufacturers, particularly considering the rapid expansion of the industrial robot market. A bi-level programming model is structured to enhance synergies in response to department reformation within an industrial robot manufacturer. The upper-level model focuses on order acceptance, considering rejection and delay penalty costs, aiming to maximize enterprise profit. The lower-level model concentrates on product production, aiming to minimize the total sum of production costs and Work-In-Progress (WIP) holding costs. Detailed constraints related to material readiness, including inventory levels and procurement lead times, are comprehensively examined. Given the NP-hard complexity of this multi-objective problem, a meta-heuristic algorithm Whale Optimization Algorithm (WOA) is implemented. To enhance WOA’s optimization capabilities, two heuristic algorithms, Solution Improvement policy (I-algorithm) and Heuristic-based acceleration strategy (H-algorithm), are introduced, resulting in the development of WOA-IH. The experimental evidence suggests that the proposed model facilitates decision coordination for manufacturers, particularly in order management, production planning, and material procurement. Furthermore, this study contributes to applying bi-level programming theory in managing supply chains for industrial robotics.