As a part of the smart factory industries, condition-based maintenance (CBM) is developed for monitoring the status of production systems. While existing maintenance technologies predict a certain period of replacement or repair time, CBM diagnoses the real-time status of objects according to the measurement obtained from sensors. Due to the property of manufacturing facilities that their performance degrades over operating time, the system should be maintained as in-control status. In this paper, we propose CBM methodology based on stochastic partial differential equation (SPDE) for production equipment by monitoring the status of products. By modeling the time-series photography of products into SPDE, the estimated results describe the degrading patterns of images in terms of space and time. The application of images in real industry shows that the proposed approach can be effectively conducted for monitoring and detecting the abnormal status.