In recent years, demands for wireless sensing and flexibility of manufacturing environment and systems are increasing and driving an increase in volume and variety of wireless devices in factories. Especially, detection of status and anomaly of systems using sensors is getting a lot of attention in the manufacturing field. In this paper, we introduce two examples in which the state of a manufacturing machine, specifically the wear state of blades in a milling machine, is diagnosed using sensing data which can be collected via a wireless network. It is shown that the volume of data required for reliable diagnosis can be reduced to minimize use of wireless resources by pre-preprocessing of data before sending.