Clearcoat filmbuild is a main concern for coating quality in automotive paint shops. In operation, a thin layer of clearcoat is sprayed on the top of other thin films on the vehicle surface and then baked in an oven for solvent removal, film topology finalization, and crosslinking reactions completion. Because of the complexity of physical and chemical phenomena occurring in operation and the lack of on-line measurement of key process and product parameters, ovens are always operated considerably less than optimally in terms of coating quality and energy consumption. In this report, a dynamic model-embedded ant colony system-based optimization methodology is introduced to tackle this sophisticated industrial problem. It is shown that, by comparing with a traditional Genetic Algorithm, the proposed methodology can provide better solution with reasonable computational effort. A major contribution of this work is that-probably for the first time-the oven energy minimization (process performance) can be achieved based on rigorous coating quality (product performance) constraints in a dynamic domain. This work advances coating quality control from traditional postprocess inspection-based practice (a reactive approach) to in-process on-line defect prevention-focused strategy (a proactive approach). It also provides a scientific basis for redesigning quality-guaranteed energy-efficient ovens. The methodology is, in general, applicable to a variety of industrial dynamic optimization problems, where product and process performance should be simultaneously considered. (c) 2005 American Institute of Chemical Engineers