Quality assurance in flexible manufacturing systems (FMSs) has become a matter of great importance in recent years. The possibility for offering high-quality products at lower costs has become an essential for a manufacturer to keep in a competitive edge. In this paper, all approach to the multi-objective optimization of production planning and inspection planning in flexible manufacturing systems is presented. A multi-objective memetic algorithm MOMA is proposed to solve the problems having six objectives: minimizing total machining time, machine workload unbalance, greatest machine workload, total tool cost, total inspection time and number of inspections. A schemata-guided local search strategy is proposed for enhancing performances of MOMA. High efficiency of MOMA arises from that multiple objectives can be optimized simultaneously without using heuristics and a set of good non-dominated solutions can be obtained providing additional degrees of freedom for the exploitation of resources of FMSs. Experimental results demonstrate effectiveness of the proposed approach using MOMA for production planning and inspection planning of FMSs.