Engineers often meet function regression problems in manufacturing. In this work, we use artifical neural network to solve this problem. We choose a typical function as the target function. Since the input value of the function is continuous, the output of the regression model should also have a continuous value range. We implement the feed forward neural network with back propagation learning algorithm, investigate different network parameters, and compare several different training algorithms. The performance assessment based on the test dataset is also discussed.