Energy and economic optimization for automobile painting process

Painting is an important process in automobile manufacture and it has many steps. It consumes considerable energy. It also creates environmental impacts such as emission of greenhouse gas and SOx caused in the fossil fuel combustion process. A heat exchanger network (HEN) is added to the process in order to utilize the exhaust heat. Thus energy utilization efficiency is improved. Considering the capital cost of heat exchanger network and operation cost, there exists a best structure which can reach the best economic improvement of the painting process. With less natural gas input in ovens, the lower temperature of exhaust gas, the environmental impact will also be improved. In order to obtain the best heat exchanger network structure. A mathematical model is set up to describe the energy use and its economic status in the process. With the goal of most economic heat exchanger network structure, genetic algorithm is used to solve the optimisation design. The result shows that the installation of heat exchanger network will reach an economic and environmental improvement of the automobile manufacture process.