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The job scheduling problem of aviation maintenance workshop is researched and analyzed deeply. Based on that, an improved Particle Swarm Optimization (PSO) algorithm is presented to solve job scheduling problem. Mathematics model is established by superior maintenance cost and maintenance time. The encoding scheme based on procedure and maintenance equipment allocation is adopted. Then discrete location update formula is designed, also crossover and mutation mechanism are applied to increase capability of global search. An example of job scheduling problem for metalworking workshop is simulated. Comparison with quality and time of the result indicates the algorithm is more efficient than normal PSO and genetic algorithm. So the proposed algorithm is viable and rational, and this paper is practical to use in reality.