In order to solve reconfiguration and optimal scheduling problems of networked collaborative manufacturing resource, a multiobjective optimization mathematical model was provided with four practical important objectives were considered simultaneously, including minimizing the total production working hours, total production working cost, optimization total production processing quality and resource service quality. A reconfiguration and optimal scheduling method for networked collaborative manufacturing resource was presented based on Pareto multi-objective immune genetic algorithm. In order to ensure the groups variety, prevent the premature convergence problem, some key technologies such as population ranking technique, niche technique, Pareto solution set filter were applied. The genetic operators were improved and self-adaptive crossover and mutation operators were proposed by the algorithm, and immune selection could eliminate semblable individuals. Immune memory was adopted to dynamic search near each approximate optimal solution, so it accelerated search and improved quality of solution. Finally the result of simulation indicated the validity of algorithm.