Intelligent manufacturing plays an increasingly important role in improving production efficiency, reducing costs, and improving product quality, and contributes to the sustainable development of the global manufacturing industry. In this paper, a control scheme of dual-arm robot cooperative compliant assembly is designed, which can be applied to industrial intelligent production lines. Taking the thread assembly process as the research object, the task model of the assembly is built. Specifically, the threaded assembly is abstracted into three processes. Aiming at the difficulties that need to be paid attention to in different assembly processes, combined with the force sensor, a phased controller is designed, and its feasibility is verified by simulation. The feasibility of the method is verified by simulation and experiment. In the case of force tracking accuracy of 0.1 N and expected force of 4 N, the experiment successfully assembled a 5 mm thread connector in about 48.54 s, and the force overshoot reached about 9 N.

To reduce high 1× vibration during staged speed-up of a Turbine Power Simulator (TPS) rotor, a staged incremental on-site balancing method based on a Genetic Algorithm–Salp Swarm Algorithm (GA–SSA) is proposed. SSA is a swarm-intelligence optimizer inspired by salps, gelatinous marine organisms that move collectively in chains. A one-dimensional Timoshenko-beam rotor model with lumped disks and equivalent bearing supports is established and validated using a three-dimensional ANSYS model. From meshes M3 to M4, the equivalent speed associated with the first lateral natural frequency changes by 0.23%. The first three critical-speed errors are 6.75–8.80%, while baseline 1× vibration-amplitude errors remain below 10% and phase errors below 7.1%. Speed-specific influence coefficients are then extracted to formulate a staged incremental balancing model based on the current measured vibration and cumulative correction state. In GA–SSA, the final GA population initializes SSA, and the historical GA best is used as the initial Food. Under equal function-evaluation budgets and 30 paired runs, GA–SSA shows search performance comparable to GA and improves the stability of standalone SSA. On-site tests at 10,358, 25,558, and 38,333 rpm reduce 1× vibration at both rotor ends by 79.0–86.4%, confirming the method’s engineering applicability.