Field operators use their eyes, ears, and nose to detect process behavior and to trigger corrective control actions. For instance: in daily practice, the experienced operator in sulfuric acid treatment of phosphate rock may observe froth color or bubble character to control process material in-flow. Or, similarly, (s)he may use acoustic sound of cavitation or boiling/flashing to increase or decrease material flow rates in tank levels. By contrast, process control computers continue to be limited to taking action on P, T, F, and A signals. Yet, there is sufficient evidence from the fields that visual and acoustic information can be used for control and identification. Smart in-situ sensors have facilitated potential mechanism for factory automation with promising industry applicability. In respond to these critical needs, a generic, structured health monitoring approach is proposed. The system assumes a given sensor suite will act as an on-line health usage monitor and at best provide the real-time control autonomy. The sensor suite can incorporate various types of sensory devices, from vibration accelerometers, directional microphones, machine vision CCDs, pressure gauges to temperature indicators. The decision can be shown in a visual on-board display or fed to the control block to invoke controller reconfigurration.